From a47bc75063d743ec4428c8e6427e84cfa871805c Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 20 Nov 2023 17:12:17 +0900 Subject: [PATCH 01/12] translated _index --- content/ja/other/_index.md | 6 +- .../1-installation/1-confirmation.md | 306 ++++ .../1-installation/_index.md | 41 + .../2-extensions/1-health.md | 58 + .../2-extensions/2-performance.md | 9 + .../2-extensions/3-zpages.md | 356 +++++ .../2-extensions/_index.md | 37 + .../3-receivers/1-hostmetrics.md | 44 + .../3-receivers/2-prometheus.md | 35 + .../3-receivers/3-other-receivers.md | 155 ++ .../3-receivers/_index.md | 39 + .../4-processors/1-batch-processor.md | 13 + .../4-processors/2-resource-detection.md | 53 + .../4-processors/3-attributes.md | 185 +++ .../4-processors/_index.md | 37 + .../5-exporters/_index.md | 39 + .../5-exporters/otlphttp.md | 183 +++ .../6-service/1-hostmetrics.md | 27 + .../6-service/2-prometheus.md | 27 + .../6-service/3-resourcedetection.md | 27 + .../6-service/4-attributes.md | 27 + 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Ninja Workshops +menuPost: " " weight: 19 --- -{{%children containerstyle="div" style="h3" description="true" %}} +{{%children containerstyle="div" style="h5" description="true" %}} + diff --git a/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md new file mode 100644 index 0000000000..edcbed1059 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md @@ -0,0 +1,306 @@ +--- +title: Installing OpenTelemetry Collector Contrib +linkTitle: 1.1 Confirm Installation +weight: 1 +--- + +## Confirm the Collector is running + +The collector should now be running. We will verify this as root using `systemctl` command. To exit the status just press `q`. + +{{< tabs >}} +{{% tab title="Command" %}} + +``` bash +sudo systemctl status otelcol-contrib +``` + +{{% /tab %}} +{{% tab title="Status Output" %}} + +``` text +● otelcol-contrib.service - OpenTelemetry Collector Contrib + Loaded: loaded (/lib/systemd/system/otelcol-contrib.service; enabled; vendor preset: enabled) + Active: active (running) since Tue 2023-05-16 08:23:23 UTC; 25s ago + Main PID: 1415 (otelcol-contrib) + Tasks: 5 (limit: 1141) + Memory: 22.2M + CPU: 125ms + CGroup: /system.slice/otelcol-contrib.service + └─1415 /usr/bin/otelcol-contrib --config=/etc/otelcol-contrib/config.yaml + +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: NumberDataPoints #0 +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: Data point attributes: +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: -> exporter: Str(logging) +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: -> service_instance_id: Str(df8a57f4-abdc-46b9-a847-acd62db1001f) +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: -> service_name: Str(otelcol-contrib) +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: -> service_version: Str(0.75.0) +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: StartTimestamp: 2023-05-16 08:23:39.006 +0000 UTC +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: Timestamp: 2023-05-16 08:23:39.006 +0000 UTC +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: Value: 0.000000 +May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: {"kind": "exporter", "data_type": "metrics", "name": "logging"} +``` + +{{% /tab %}} +{{< /tabs >}} + +As will be running the rest of the workshop using the `otelcol-contrib` standalone binary, we will stop the service and then disable it from starting on boot: + +{{< tabs >}} +{{% tab title="Command" %}} + +``` bash +sudo systemctl stop otelcol-contrib +``` + +{{% /tab %}} +{{< /tabs >}} + +{{< tabs >}} +{{% tab title="Command" %}} + +``` bash +sudo systemctl disable otelcol-contrib +``` + +{{% /tab %}} +{{< /tabs >}} + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Build your own collector using Open Telemetry Collector Builder (ocb){{% /badge %}}" %}} +For this part we will require the following installed on your system: + +- Golang (latest version) + + ``` bash + cd /tmp + wget https://golang.org/dl/go1.20.linux-amd64.tar.gz + sudo tar -C /usr/local -xzf go1.20.linux-amd64.tar.gz + ``` + + Edit `.profile` and add the following environment variables: + + ``` bash + export GOROOT=/usr/local/go + export GOPATH=$HOME/go + export PATH=$GOPATH/bin:$GOROOT/bin:$PATH + ``` + + Renew your shell session: + + ``` bash + source ~/.profile + ``` + + Check Go version: + + ``` bash + go version + ``` + +- ocb installed + - Download the ocb binary from the [project releases](https://github.com/open-telemetry/opentelemetry-collector/releases/tag/cmd%2Fbuilder%2Fv0.80.0) + and run the following commands: + + ```bash + mv ocb_0.80.0_darwin_arm64 /usr/bin/ocb + chmod 755 /usr/bin/ocb + ``` + + An alternative approach would be to use the golang tool chain to build the binary locally by doing: + + ```bash + go install go.opentelemetry.io/collector/cmd/builder@v0.80.0 + mv $(go env GOPATH)/bin/builder /usr/bin/ocb + ``` + +- (Optional) Docker + +## Why build your own collector? + +The default distribution of the collector (core and contrib) either contain too much or too little in what they have to offer. + +It is also not advised to run the contrib collector in your production environments due to the amount of components installed which more than likely are not needed by your deployment. + +## Benefits of building your own collector? + +When creating your own collector binaries, (commonly referred to as distribution), means you build what you need. + +The benefits of this are: + +1. Smaller sized binaries +2. Can use existing go scanners for vulnerabilities +3. Include internal components that can tie in with your organisation + +## Considerations for building your own collector? + +Now, this would not be a 🥷 Ninja zone if it didn't come with some draw backs: + +1. Go experience is recommended if not required +1. **No** Splunk support +1. Responsibility of distribution and lifecycle management + +It is important to note that project is working towards stability but it does not mean changes made will not break your workflow. The team at Splunk provide increased support and a higher level of stability so they can provide a curated experience helping you with your deployment needs. + +## The Ninja Zone + +Once you have all the required tools installed to get started, you will need to create a new file named `otelcol-builder.yaml` and we will follow this directory structure: + +``` bash +. +└── otelcol-builder.yaml +``` + +Once we have the file created, we need to add a list of components for it to install with some additional metadata. + +For this example, we are going to create a builder manifest that will install only the components we need for the introduction config: + +```yaml +dist: + name: otelcol-ninja + description: A custom build of the Open Telemetry Collector + output_path: ./dist + +extensions: +- gomod: go.opentelemetry.io/collector/extension/ballastextension v0.80.0 +- gomod: go.opentelemetry.io/collector/extension/zpagesextension v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/extension/httpforwarder v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/extension/healthcheckextension v0.80.0 + +exporters: +- gomod: go.opentelemetry.io/collector/exporter/loggingexporter v0.80.0 +- gomod: go.opentelemetry.io/collector/exporter/otlpexporter v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/exporter/splunkhecexporter v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/exporter/signalfxexporter v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/exporter/sapmexporter v0.80.0 + +processors: +- gomod: go.opentelemetry.io/collector/processor/batchprocessor v0.80.0 +- gomod: go.opentelemetry.io/collector/processor/memorylimiterprocessor v0.80.0 + +receivers: +- gomod: go.opentelemetry.io/collector/receiver/otlpreceiver v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/hostmetricsreceiver v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/jaegerreceiver v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/prometheusreceiver v0.80.0 +- gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/zipkinreceiver v0.80.0 +``` + +Once the yaml file has been updated for the _ocb_, then run the following command: + +```shell +ocb --config=otelcol-builder.yaml +``` + +Which leave you with the following directory structure: + +``` text +├── dist +│   ├── components.go +│   ├── components_test.go +│   ├── go.mod +│   ├── go.sum +│   ├── main.go +│   ├── main_others.go +│   ├── main_windows.go +│   └── otelcol-ninja +└── otelcol-builder.yaml +``` + +### References + +1. [https://opentelemetry.io/docs/collector/custom-collector/](https://opentelemetry.io/docs/collector/custom-collector/) + +{{% /expand %}} + +--- + +## Default configuration + +OpenTelemetry is configured through YAML files. These files have default configurations that we can modify to meet our needs. Let's look at the default configuration that is supplied: + +{{< tabs >}} +{{% tab title="Command" %}} + +```bash +cat /etc/otelcol-contrib/config.yaml +``` + +{{% /tab %}} +{{% tab title="config.yaml" %}} + +```yaml { lineNos="table" wrap="true"} +extensions: + health_check: + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + +exporters: + logging: + verbosity: detailed + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [otlp, opencensus, prometheus] + processors: [batch] + exporters: [logging] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{< /tabs >}} + +Congratulations! You have successfully downloaded and installed the OpenTelemetry Collector. You are well on your way to becoming an OTel Ninja. But first lets walk through configuration files and different distributions of the OpenTelemetry Collector. + +{{% notice style="note" %}} + +Splunk does provide its own, fully supported, distribution of the OpenTelemetry Collector. This distribution is available to install from the [Splunk GitHub Repository](https://github.com/signalfx/splunk-otel-collector) or via a wizard in Splunk Observability Cloud that will build out a simple installation script to copy and paste. This distribution includes a number of additional features and enhancements that are not available in the OpenTelemetry Collector Contrib distribution. + +- The Splunk Distribution of the OpenTelemetry Collector is production tested; it is in use by the majority of customers in their production environments. +- Customers that use our distribution can receive direct help from official Splunk support within SLA's. +- Customers can use or migrate to the Splunk Distribution of the OpenTelemetry Collector without worrying about future breaking changes to its core configuration experience for metrics and traces collection (OpenTelemetry logs collection configuration is in beta). There may be breaking changes to the Collector's own metrics. + +{{% /notice %}} + +We will now walk through each section of the configuration file and modify it to send host metrics to Splunk Observability Cloud. diff --git a/content/ja/other/opentelemetry-collector/1-installation/_index.md b/content/ja/other/opentelemetry-collector/1-installation/_index.md new file mode 100644 index 0000000000..4e7bae1abe --- /dev/null +++ b/content/ja/other/opentelemetry-collector/1-installation/_index.md @@ -0,0 +1,41 @@ +--- +title: Installing OpenTelemetry Collector Contrib +linkTitle: 1. Installation +weight: 1 +--- + +## Download the OpenTelemetry Collector Contrib distribution + +The first step in installing the Open Telemetry Collector is downloading it. For our lab we will use the `wget` command to download the `.deb` package from the OpenTelemetry Github repository. + +Obtain the `.deb` package for your platform from the [OpenTelemetry Collector Contrib releases page](https://github.com/open-telemetry/opentelemetry-collector-releases/releases) + +``` bash +wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v0.80.0/otelcol-contrib_0.80.0_linux_amd64.deb +``` + +## Install the OpenTelemetry Collector Contrib distribution + +Install the `.deb` package using `dpkg`. Take a look at the **dpkg Output** tab below to see what the example output of a successful install will look like: + +{{< tabs >}} +{{% tab title="Install" %}} + +``` bash +sudo dpkg -i otelcol-contrib_0.80.0_linux_amd64.deb +``` + +{{% /tab %}} +{{% tab title="dpkg Output" %}} + +``` text +Selecting previously unselected package otelcol-contrib. +(Reading database ... 64218 files and directories currently installed.) +Preparing to unpack otelcol-contrib_0.75.0_linux_amd64.deb ... +Unpacking otelcol-contrib (0.75.0) ... +Setting up otelcol-contrib (0.75.0) ... +Created symlink /etc/systemd/system/multi-user.target.wants/otelcol-contrib.service → /lib/systemd/system/otelcol-contrib.service. +``` + +{{% /tab %}} +{{< /tabs >}} diff --git a/content/ja/other/opentelemetry-collector/2-extensions/1-health.md b/content/ja/other/opentelemetry-collector/2-extensions/1-health.md new file mode 100644 index 0000000000..f34cfddc5d --- /dev/null +++ b/content/ja/other/opentelemetry-collector/2-extensions/1-health.md @@ -0,0 +1,58 @@ +--- +title: OpenTelemetry Collector Extensions +linkTitle: 2.1 Health Check +weight: 1 +--- + +## Health Check + +Extensions are configured in the same `config.yaml` file that we referenced in the installation step. Let's edit the `config.yaml` file and configure the extensions. Note that the **pprof** and **zpages** extensions are already configured in the default `config.yaml` file. For the purpose of this workshop, we will only be updating the **health_check** extension to expose the port on all network interfaces on which we can access the health of the collector. + +{{% tab title="Command" %}} + +``` bash +sudo vi /etc/otelcol-contrib/config.yaml +``` + +{{% /tab %}} + +{{% tab title="Extensions Configuration" %}} + +```yaml {hl_lines="3"} +extensions: + health_check: + endpoint: 0.0.0.0:13133 +``` + +{{% /tab %}} + +Start the collector: + +{{% tab title="Command" %}} + +``` bash +otelcol-contrib --config=file:/etc/otelcol-contrib/config.yaml +``` + +{{% /tab %}} + +This extension enables a HTTP URL that can be probed to check the status of the OpenTelemetry Collector. This extension can be used as a liveness and/or readiness probe on Kubernetes. To learn more about the `curl` command, check out the [curl man page](https://curl.se/docs/manpage.html). + +Open a new terminal session and SSH into your instance to run the following command: + +{{< tabs >}} +{{% tab title="curl Command" %}} + +```bash +curl http://localhost:13133 +``` + +{{% /tab %}} +{{% tab title="curl Output" %}} + +``` text +{"status":"Server available","upSince":"2023-04-27T10:11:22.153295874+01:00","uptime":"16m24.684476004s"} +``` + +{{% /tab %}} +{{< /tabs >}} diff --git a/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md b/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md new file mode 100644 index 0000000000..b29172f14c --- /dev/null +++ b/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md @@ -0,0 +1,9 @@ +--- +title: OpenTelemetry Collector Extensions +linkTitle: 2.2 Performance Profiler +weight: 2 +--- + +## Performance Profiler + +[**Performance Profiler**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/extension/pprofextension/README.md) extension enables the golang net/http/pprof endpoint. This is typically used by developers to collect performance profiles and investigate issues with the service. **We will not be covering this in this workshop**. diff --git a/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md new file mode 100644 index 0000000000..b586f0fd78 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md @@ -0,0 +1,356 @@ +--- +title: OpenTelemetry Collector Extensions +linkTitle: 2.3 zPages +weight: 3 +--- + +## zPages + +[**zPages**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/extension/zpagesextension/README.md) are an in-process alternative to external exporters. When included, they collect and aggregate tracing and metrics information in the background; this data is served on web pages when requested. zPages are an extremely useful diagnostic feature to ensure the collector is running as expected. + +{{< tabs >}} +{{% tab title="ServiceZ" %}} + +**ServiceZ** gives an overview of the collector services and quick access to the pipelinez, extensionz, and featurez zPages. The page also provides build and runtime information. + +Example URL: [http://localhost:55679/debug/servicez](http://localhost:55679/debug/servicez) (change `localhost` to reflect your own environment). + +![ServiceZ](../../images/servicez.png) + +{{% /tab %}} +{{% tab title="PipelineZ" %}} + +**PipelineZ** provides insights on the running pipelines running in the collector. You can find information on type, if data is mutated, and you can also see information on the receivers, processors and exporters that are used for each pipeline. + +Example URL: [http://localhost:55679/debug/pipelinez](http://localhost:55679/debug/pipelinez) (change `localhost` to reflect your own environment). + +![PipelineZ](../../images/pipelinez.png) + +{{% /tab %}} +{{% tab title="ExtensionZ" %}} + +**ExtensionZ** shows the extensions that are active in the collector. + +Example URL: [http://localhost:55679/debug/extensionz](http://localhost:55679/debug/extensionz) (change `localhost` to reflect your own environment). + +![ExtensionZ](../../images/extensionz.png) + +{{% /tab %}} +{{% /tabs %}} + +{{% notice style="info" %}} +If you are not following along, you can use your browser to access a test environment emitting zPages information at: + +- **ServiceZ:** [http://63.33.64.193:55679/debug/servicez](http://63.33.64.193:55679/debug/servicez) +- **PipelineZ:** [http://63.33.64.193:55679/debug/pipelinez](http://63.33.64.193:55679/debug/pipelinez) +- **ExtensionZ:** [http://63.33.64.193:55679/debug/extensionz](http://63.33.64.193:55679/debug/extensionz) +{{% /notice %}} + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Improve data durability with storage extension{{% /badge %}}" %}} + +For this, we will need to validate that our distribution has the `file_storage` extension installed. This can be done by running the command `otelcol-contrib components` which should show results like: + +{{< tabs >}} +{{% tab title="Truncated Output" %}} + +```yaml +# ... truncated for clarity +extensions: + - file_storage +``` + +{{% /tab %}} +{{% tab title="Full Output" %}} + +```yaml +buildinfo: + command: otelcol-contrib + description: OpenTelemetry Collector Contrib + version: 0.80.0 +receivers: + - prometheus_simple + - apache + - influxdb + - purefa + - purefb + - receiver_creator + - mongodbatlas + - vcenter + - snmp + - expvar + - jmx + - kafka + - skywalking + - udplog + - carbon + - kafkametrics + - memcached + - prometheus + - windowseventlog + - zookeeper + - otlp + - awsecscontainermetrics + - iis + - mysql + - nsxt + - aerospike + - elasticsearch + - httpcheck + - k8sobjects + - mongodb + - hostmetrics + - signalfx + - statsd + - awsxray + - cloudfoundry + - collectd + - couchdb + - kubeletstats + - jaeger + - journald + - riak + - splunk_hec + - active_directory_ds + - awscloudwatch + - sqlquery + - windowsperfcounters + - flinkmetrics + - googlecloudpubsub + - podman_stats + - wavefront + - k8s_events + - postgresql + - rabbitmq + - sapm + - sqlserver + - redis + - solace + - tcplog + - awscontainerinsightreceiver + - awsfirehose + - bigip + - filelog + - googlecloudspanner + - cloudflare + - docker_stats + - k8s_cluster + - pulsar + - zipkin + - nginx + - opencensus + - azureeventhub + - datadog + - fluentforward + - otlpjsonfile + - syslog +processors: + - resource + - batch + - cumulativetodelta + - groupbyattrs + - groupbytrace + - k8sattributes + - experimental_metricsgeneration + - metricstransform + - routing + - attributes + - datadog + - deltatorate + - spanmetrics + - span + - memory_limiter + - redaction + - resourcedetection + - servicegraph + - transform + - filter + - probabilistic_sampler + - tail_sampling +exporters: + - otlp + - carbon + - datadog + - f5cloud + - kafka + - mezmo + - skywalking + - awsxray + - dynatrace + - loki + - prometheus + - logging + - azuredataexplorer + - azuremonitor + - instana + - jaeger + - loadbalancing + - sentry + - splunk_hec + - tanzuobservability + - zipkin + - alibabacloud_logservice + - clickhouse + - file + - googlecloud + - prometheusremotewrite + - awscloudwatchlogs + - googlecloudpubsub + - jaeger_thrift + - logzio + - sapm + - sumologic + - otlphttp + - googlemanagedprometheus + - opencensus + - awskinesis + - coralogix + - influxdb + - logicmonitor + - signalfx + - tencentcloud_logservice + - awsemf + - elasticsearch + - pulsar +extensions: + - zpages + - bearertokenauth + - oidc + - host_observer + - sigv4auth + - file_storage + - memory_ballast + - health_check + - oauth2client + - awsproxy + - http_forwarder + - jaegerremotesampling + - k8s_observer + - pprof + - asapclient + - basicauth + - headers_setter +``` + +{{% /tab %}} +{{< /tabs >}} + +This extension provides exporters the ability to queue data to disk in the event that exporter is unable to send data to the configured endpoint. + +In order to configure the extension, you will need to update your config to include the information below. First, be sure to create a /tmp/otel-data directory and give it read/write permissions: + +```yaml +extensions: +... + file_storage: + directory: /tmp/otel-data + timeout: 10s + compaction: + directory: /tmp/otel-data + on_start: true + on_rebound: true + rebound_needed_threshold_mib: 5 + rebound_trigger_threshold_mib: 3 + +# ... truncated for clarity + +service: + extensions: [health_check, pprof, zpages, file_storage] +``` + +## Why queue data to disk? + +This allows the collector to weather network interruptions (and even collector restarts) to ensure data is sent to the upstream provider. + +## Considerations for queuing data to disk? + +There is a potential that this could impact data throughput performance due to disk performance. + +### References + +1. [https://community.splunk.com/t5/Community-Blog/Data-Persistence-in-the-OpenTelemetry-Collector/ba-p/624583](https://community.splunk.com/t5/Community-Blog/Data-Persistence-in-the-OpenTelemetry-Collector/ba-p/624583) +2. [https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/storage/filestorage](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/storage/filestorage) + +{{% /expand %}} + +--- + +## Configuration Check-in + +Now that we've covered extensions, let's check our configuration changes. + +--- + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{< tabs >}} +{{% tab title="config.yaml" %}} + +```yaml { lineNos="table" wrap="true" hl_lines="3" } +extensions: + health_check: + endpoint: 0.0.0.0:13133 + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + +exporters: + logging: + verbosity: detailed + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [otlp, opencensus, prometheus] + processors: [batch] + exporters: [logging] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{< /tabs >}} +{{% /expand %}} + +--- + +Now that we have reviewed extensions, let's dive into the data pipeline portion of the workshop. A pipeline defines a path the data follows in the Collector starting from reception, moving to further processing or modification, and finally exiting the Collector via exporters. + +The data pipeline in the OpenTelemetry Collector is made up of receivers, processors, and exporters. We will first start with receivers. diff --git a/content/ja/other/opentelemetry-collector/2-extensions/_index.md b/content/ja/other/opentelemetry-collector/2-extensions/_index.md new file mode 100644 index 0000000000..d04111e890 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/2-extensions/_index.md @@ -0,0 +1,37 @@ +--- +title: OpenTelemetry Collector Extensions +linkTitle: 2. Extensions +weight: 2 +--- + +Now that we have the OpenTelemetry Collector installed, let's take a look at extensions for the OpenTelemetry Collector. Extensions are optional and available primarily for tasks that do not involve processing telemetry data. Examples of extensions include health monitoring, service discovery, and data forwarding. + +{{< mermaid >}} +%%{ + init:{ + "theme": "base", + "themeVariables": { + "primaryColor": "#ffffff", + "clusterBkg": "#eff2fb", + "defaultLinkColor": "#333333" + } + } +}%% + +flowchart LR; + style E fill:#e20082,stroke:#333,stroke-width:4px,color:#fff + subgraph Collector + A[OTLP] --> M(Receivers) + B[JAEGER] --> M(Receivers) + C[Prometheus] --> M(Receivers) + end + subgraph Processors + M(Receivers) --> H(Filters, Attributes, etc) + E(Extensions) + end + subgraph Exporters + H(Filters, Attributes, etc) --> S(OTLP) + H(Filters, Attributes, etc) --> T(JAEGER) + H(Filters, Attributes, etc) --> U(Prometheus) + end +{{< /mermaid >}} diff --git a/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md b/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md new file mode 100644 index 0000000000..ab62add059 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md @@ -0,0 +1,44 @@ +--- +title: OpenTelemetry Collector Receivers +linkTitle: 1. Host Metrics +weight: 1 +--- + +## Host Metrics Receiver + +[**The Host Metrics Receiver**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/receiver/hostmetricsreceiver/README.md) generates metrics about the host system scraped from various sources. This is intended to be used when the collector is deployed as an agent which is what we will be doing in this workshop. + +Let's update the `/etc/otel-contrib/config.yaml` file and configure the **hostmetrics** receiver. Insert the following YAML under the **receivers** section, taking care to indent by two spaces. + +``` bash +sudo vi /etc/otelcol-contrib/config.yaml +``` + +{{% tab title="Host Metrics Receiver Configuration" %}} + +```yaml {hl_lines="2-22"} +receivers: + hostmetrics: + collection_interval: 10s + scrapers: + # CPU utilization metrics + cpu: + # Disk I/O metrics + disk: + # File System utilization metrics + filesystem: + # Memory utilization metrics + memory: + # Network interface I/O metrics & TCP connection metrics + network: + # CPU load metrics + load: + # Paging/Swap space utilization and I/O metrics + paging: + # Process count metrics + processes: + # Per process CPU, Memory and Disk I/O metrics. Disabled by default. + # process: +``` + +{{% /tab %}} diff --git a/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md new file mode 100644 index 0000000000..5d86d934a5 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md @@ -0,0 +1,35 @@ +--- +title: OpenTelemetry Collector Receivers +linkTitle: 2. Prometheus +weight: 2 +--- + +## Prometheus Receiver + +You will also notice another receiver called **prometheus**. [Prometheus](https://prometheus.io/docs/introduction/overview/) is an open-source toolkit used by the OpenTelemetry Collector. This receiver is used to scrape metrics from the OpenTelemetry Collector itself. These metrics can then be used to monitor the health of the collector. + +Let's modify the **prometheus** receiver to clearly show that it is for collecting metrics from the collector itself. By changing the name of the receiver from **prometheus** to **prometheus/internal**, it is now much clearer as to what that receiever is doing. Update the configuration file to look like this: + +{{% tab title="Prometheus Receiver Configuration" %}} + +```yaml {hl_lines="1"} +prometheus/internal: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] +``` + +{{% /tab %}} + +## Example Dashboard - Prometheus metrics + +The following screenshot shows an example dashboard of spme of the metrics the Prometheus internal receiver collects from the OpenTelemetry Collector. Here, we can see accepted and sent spans, metrics and log records. + +{{% notice style="note" %}} +The following screenshot is an out-of-the-box (OOTB) dashboard from Splunk Observability Cloud that allows you to easily monitor your Splunk OpenTelemetry Collector install base. +{{% /notice %}} + +![otel-charts](../../images/otel-charts.png) diff --git a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md new file mode 100644 index 0000000000..38e0d61a53 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md @@ -0,0 +1,155 @@ +--- +title: OpenTelemetry Collector Receivers +linkTitle: 3. Other Receivers +weight: 3 +--- + +## Other Receivers + +You will notice in the default configuration there are other receivers: **otlp**, **opencensus**, **jaeger** and **zipkin**. These are used to receive telemetry data from other sources. We will not be covering these receivers in this workshop and they can be left as they are. + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Create receivers dynamically{{% /badge %}}" %}} + +To help observe short lived tasks like docker containers, kubernetes pods, or ssh sessions, we can use the [receiver creator](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator) with [observer extensions](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/observer) to create a new receiver as these services start up. + +## What do we need? + +In order to start using the receiver creator and its associated observer extensions, they will need to be part of your collector build manifest. + +See [installation](../1-installation/) for the details. + +## Things to consider? + +Some short lived tasks may require additional configuration such as _username_, and _password_. +These values can be referenced via [environment variables](https://opentelemetry.io/docs/collector/configuration/#configuration-environment-variables), +or use a scheme expand syntax such as `${file:./path/to/database/password}`. +Please adhere to your organisation's secret practices when taking this route. + +## The Ninja Zone + +There are only two things needed for this ninja zone: + +1. Make sure you have added receiver creater and observer extensions to the builder manifest. +2. Create the config that can be used to match against discovered endpoints. + +To create the templated configurations, you can do the following: + +```yaml +receiver_creator: + watch_observers: [host_observer] + receivers: + redis: + rule: type == "port" && port == 6379 + config: + password: ${env:HOST_REDIS_PASSWORD} +``` + +For more examples, refer to these [receiver creator's examples](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator#examples). + +{{% /expand %}} + +--- + +## Configuration Check-in + +We've now covered receivers, so let's now check our configuration changes. + +--- + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{< tabs >}} +{{% tab title="config.yaml" %}} + +```yaml {lineNos="table" wrap="true" hl_lines="10-30 39"} +extensions: + health_check: + endpoint: 0.0.0.0:13133 + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + hostmetrics: + collection_interval: 10s + scrapers: + # CPU utilization metrics + cpu: + # Disk I/O metrics + disk: + # File System utilization metrics + filesystem: + # Memory utilization metrics + memory: + # Network interface I/O metrics & TCP connection metrics + network: + # CPU load metrics + load: + # Paging/Swap space utilization and I/O metrics + paging: + # Process count metrics + processes: + # Per process CPU, Memory and Disk I/O metrics. Disabled by default. + # process: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus/internal: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + +exporters: + logging: + verbosity: detailed + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [otlp, opencensus, prometheus/internal] + processors: [batch] + exporters: [logging] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{< /tabs >}} +{{% /expand %}} + +--- + +Now that we have reviewed how data gets into the OpenTelemetry Collector through receivers, let's now take a look at how the Collector processes the received data. + +{{% notice style="warning" %}} +As the `/etc/otelcol-contrib/config.yaml` is not complete, please **do not** attempt to restart the collector at this point. +{{% /notice %}} diff --git a/content/ja/other/opentelemetry-collector/3-receivers/_index.md b/content/ja/other/opentelemetry-collector/3-receivers/_index.md new file mode 100644 index 0000000000..622ead0253 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/3-receivers/_index.md @@ -0,0 +1,39 @@ +--- +title: OpenTelemetry Collector Receivers +linkTitle: 3. Receivers +weight: 3 +--- + +Welcome to the receiver portion of the workshop! This is the starting point of the data pipeline of the OpenTelemetry Collector. Let's dive in. + +A receiver, which can be push or pull based, is how data gets into the Collector. Receivers may support one or more data sources. Generally, a receiver accepts data in a specified format, translates it into the internal format and passes it to processors and exporters defined in the applicable pipelines. + +{{< mermaid >}} +%%{ + init:{ + "theme":"base", + "themeVariables": { + "primaryColor": "#ffffff", + "clusterBkg": "#eff2fb", + "defaultLinkColor": "#333333" + } + } +}%% + +flowchart LR; + style M fill:#e20082,stroke:#333,stroke-width:4px,color:#fff + subgraph Collector + A[OTLP] --> M(Receivers) + B[JAEGER] --> M(Receivers) + C[Prometheus] --> M(Receivers) + end + subgraph Processors + M(Receivers) --> H(Filters, Attributes, etc) + E(Extensions) + end + subgraph Exporters + H(Filters, Attributes, etc) --> S(OTLP) + H(Filters, Attributes, etc) --> T(JAEGER) + H(Filters, Attributes, etc) --> U(Prometheus) + end +{{< /mermaid >}} diff --git a/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md b/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md new file mode 100644 index 0000000000..33584d31ad --- /dev/null +++ b/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md @@ -0,0 +1,13 @@ +--- +title: OpenTelemetry Collector Processors +linkTitle: 4.1 Batch +weight: 1 +--- + +## Batch Processor + +By default, only the **batch** processor is enabled. This processor is used to batch up data before it is exported. This is useful for reducing the number of network calls made to exporters. For this workshop we will accept the defaults: + +- `send_batch_size` (default = 8192): Number of spans, metric data points, or log records after which a batch will be sent regardless of the timeout. send_batch_size acts as a trigger and does not affect the size of the batch. If you need to enforce batch size limits sent to the next component in the pipeline see send_batch_max_size. +- `timeout` (default = 200ms): Time duration after which a batch will be sent regardless of size. If set to zero, send_batch_size is ignored as data will be sent immediately, subject to only send_batch_max_size. +- `send_batch_max_size` (default = 0): The upper limit of the batch size. 0 means no upper limit of the batch size. This property ensures that larger batches are split into smaller units. It must be greater than or equal to send_batch_size. diff --git a/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md b/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md new file mode 100644 index 0000000000..8663a69bb2 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md @@ -0,0 +1,53 @@ +--- +title: OpenTelemetry Collector Processors +linkTitle: 4.2 Resource Detection +weight: 2 +--- + +## Resource Detection Processor + +The **resourcedetection** processor can be used to detect resource information from the host and append or override the resource value in telemetry data with this information. + +By default, the hostname is set to the FQDN if possible, otherwise the hostname provided by the OS is used as a fallback. This logic can be changed from using using the `hostname_sources` configuration option. To avoid getting the FQDN and use the hostname provided by the OS, we will set the `hostname_sources` to `os`. + +{{% tab title="System Resource Detection Processor Configuration" %}} + +``` yaml {hl_lines="3-7"} +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] +``` + +{{% /tab %}} + +If the workshop instance is running on an AWS/EC2 instance we can gather the following tags from the EC2 metadata API (this is not available on other platforms). + +- `cloud.provider ("aws")` +- `cloud.platform ("aws_ec2")` +- `cloud.account.id` +- `cloud.region` +- `cloud.availability_zone` +- `host.id` +- `host.image.id` +- `host.name` +- `host.type` + +We will create another processor to append these tags to our metrics. + +{{% tab title="EC2 Resource Detection Processor Configuration" %}} + +``` yaml {hl_lines="7-8"} +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] + resourcedetection/ec2: + detectors: [ec2] +``` + +{{% /tab %}} diff --git a/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md new file mode 100644 index 0000000000..a7d8cb2ddb --- /dev/null +++ b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md @@ -0,0 +1,185 @@ +--- +title: OpenTelemetry Collector Processors +linkTitle: 4.3 Attributes +weight: 3 +--- + +## Attributes Processor + +The attributes processor modifies attributes of a span, log, or metric. This processor also supports the ability to filter and match input data to determine if they should be included or excluded for specified actions. + +It takes a list of actions which are performed in order specified in the config. The supported actions are: + +- `insert`: Inserts a new attribute in input data where the key does not already exist. +- `update`: Updates an attribute in input data where the key does exist. +- `upsert`: Performs insert or update. Inserts a new attribute in input data where the key does not already exist and updates an attribute in input data where the key does exist. +- `delete`: Deletes an attribute from the input data. +- `hash`: Hashes (SHA1) an existing attribute value. +- `extract`: Extracts values using a regular expression rule from the input key to target keys specified in the rule. If a target key already exists, it will be overridden. + +We are going to create an attributes processor to `insert` a new attribute to all our host metrics called `participant.name` with a value of your own name e.g. `marge_simpson`. + +{{% notice style="warning" %}} + +Ensure you replace `INSERT_YOUR_NAME_HERE` with your own name and also ensure you **do not** use spaces in your name. + +{{% /notice %}} + +Later on in the workshop we will use this attribute to filter our metrics in Splunk Observability Cloud. + +{{% tab title="Attributes Processor Configuration" %}} + +``` yaml {hl_lines="9-13"} +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] + resourcedetection/ec2: + detectors: [ec2] + attributes/conf: + actions: + - key: participant.name + action: insert + value: "INSERT_YOUR_NAME_HERE" +``` + +{{%/ tab %}} + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Using connectors to gain internal insights{{% /badge %}}" %}} + +One of the most recent additions to the collector was the notion of a [connector](https://opentelemetry.io/docs/collector/configuration/#connectors), which allows you to join output of one pipeline to input of another pipeline. + +An example of how this is beneficial is that some services emit metrics based on the amount of datapoints being exported, number of logs containing an error status, +or the amount of data being sent from one deployment environment. The count connector helps address this for you out of the box. + +## Why a connector instead of a processor? + +A processor is limited in what additional data it can produce considering it has to pass on the data it has processed making it hard to expose additional information. Connectors do not have to emit the data they received which means they provide an opportunity to create those insights we are after. + +For example, a connector could be made to count the number of logs, metrics, and traces that do not have the deployment environment attribute. + +A very simple example with the output of being able to break down data usage by deployment environment. + +## Considerations with connectors + +A connector only accepts data exported from one pipeline and receiver by another pipeline, this means you may have to consider how you construct your collector config to take advantage of it. + +## References + +1. [https://opentelemetry.io/docs/collector/configuration/#connectors](https://opentelemetry.io/docs/collector/configuration/#connectors) +2. [https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/connector/countconnector](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/connector/countconnector) + +{{% /expand %}} + +--- + +## Configuration Check-in + +That's processors covered, let's check our configuration changes. + +--- + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{< tabs >}} +{{% tab title="config.yaml" %}} + +```yaml {lineNos="table" wrap="true" hl_lines="58-68"} +extensions: + health_check: + endpoint: 0.0.0.0:13133 + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + hostmetrics: + collection_interval: 10s + scrapers: + # CPU utilization metrics + cpu: + # Disk I/O metrics + disk: + # File System utilization metrics + filesystem: + # Memory utilization metrics + memory: + # Network interface I/O metrics & TCP connection metrics + network: + # CPU load metrics + load: + # Paging/Swap space utilization and I/O metrics + paging: + # Process count metrics + processes: + # Per process CPU, Memory and Disk I/O metrics. Disabled by default. + # process: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus/internal: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] + resourcedetection/ec2: + detectors: [ec2] + attributes/conf: + actions: + - key: participant.name + action: insert + value: "INSERT_YOUR_NAME_HERE" + +exporters: + logging: + verbosity: detailed + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [otlp, opencensus, prometheus] + processors: [batch] + exporters: [logging] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{< /tabs >}} +{{% /expand %}} + +--- diff --git a/content/ja/other/opentelemetry-collector/4-processors/_index.md b/content/ja/other/opentelemetry-collector/4-processors/_index.md new file mode 100644 index 0000000000..087dfba62a --- /dev/null +++ b/content/ja/other/opentelemetry-collector/4-processors/_index.md @@ -0,0 +1,37 @@ +--- +title: OpenTelemetry Collector Processors +linkTitle: 4. Processors +weight: 4 +--- + +[**Processors**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/processor/README.md) are run on data between being received and being exported. Processors are optional though some are recommended. There are [a large number of processors](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor) included in the OpenTelemetry contrib Collector. + +{{< mermaid >}} +%%{ + init:{ + "theme":"base", + "themeVariables": { + "primaryColor": "#ffffff", + "clusterBkg": "#eff2fb", + "defaultLinkColor": "#333333" + } + } +}%% + +flowchart LR; + style Processors fill:#e20082,stroke:#333,stroke-width:4px,color:#fff + subgraph Collector + A[OTLP] --> M(Receivers) + B[JAEGER] --> M(Receivers) + C[Prometheus] --> M(Receivers) + end + subgraph Processors + M(Receivers) --> H(Filters, Attributes, etc) + E(Extensions) + end + subgraph Exporters + H(Filters, Attributes, etc) --> S(OTLP) + H(Filters, Attributes, etc) --> T(JAEGER) + H(Filters, Attributes, etc) --> U(Prometheus) + end +{{< /mermaid >}} diff --git a/content/ja/other/opentelemetry-collector/5-exporters/_index.md b/content/ja/other/opentelemetry-collector/5-exporters/_index.md new file mode 100644 index 0000000000..f1dddb55ed --- /dev/null +++ b/content/ja/other/opentelemetry-collector/5-exporters/_index.md @@ -0,0 +1,39 @@ +--- +title: OpenTelemetry Collector Exporters +linkTitle: 5. Exporters +weight: 5 +--- + +An exporter, which can be push or pull based, is how you send data to one or more backends/destinations. Exporters may support one or more data sources. + +For this workshop, we will be using the [**otlphttp**](https://opentelemetry.io/docs/specs/otel/protocol/exporter/) exporter. The OpenTelemetry Protocol (OTLP) is a vendor-neutral, standardised protocol for transmitting telemetry data. The OTLP exporter sends data to a server that implements the OTLP protocol. The OTLP exporter supports both [**gRPC**](https://grpc.io/) and [**HTTP**](https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview)/[**JSON**](https://www.json.org/json-en.html) protocols. + +{{< mermaid >}} +%%{ + init:{ + "theme":"base", + "themeVariables": { + "primaryColor": "#ffffff", + "clusterBkg": "#eff2fb", + "defaultLinkColor": "#333333" + } + } +}%% + +flowchart LR; + style Exporters fill:#e20082,stroke:#333,stroke-width:4px,color:#fff + subgraph Collector + A[OTLP] --> M(Receivers) + B[JAEGER] --> M(Receivers) + C[Prometheus] --> M(Receivers) + end + subgraph Processors + M(Receivers) --> H(Filters, Attributes, etc) + E(Extensions) + end + subgraph Exporters + H(Filters, Attributes, etc) --> S(OTLP) + H(Filters, Attributes, etc) --> T(JAEGER) + H(Filters, Attributes, etc) --> U(Prometheus) + end +{{< /mermaid >}} diff --git a/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md b/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md new file mode 100644 index 0000000000..cd497f5451 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md @@ -0,0 +1,183 @@ +--- +title: OpenTelemetry Collector Exporters +linkTitle: 5.1 OTLP HTTP +weight: 1 +--- + +## OTLP HTTP Exporter + +In order to send metrics over HTTP to Splunk Observability Cloud, we will need to configure the **otlphttp** exporter. + +Let's edit our `/etc/otelcol-contrib/config.yaml` file and configure the **otlphttp** exporter. Insert the following YAML under the **exporters** section, taking care to indent by two spaces e.g. + +We will also change the verbosity of the logging exporter to prevent the disk filling up. The default of `detailed` is very noisy. + +```yaml {hl_lines="3-4"} +exporters: + logging: + verbosity: normal + otlphttp/splunk: +``` + +Next we need to define the `metrics_endpoint` and configure the target URL. + +{{% notice style="note" %}} +If you are an attendee to a Splunk hosted workshop, the instance your are using has already been configured with a Realm environment variable. We will reference that environment variable in our configuration file. Otherwise, you will need to create a new environment variable and set the Realm e.g. + +``` bash +export REALM="us1" +``` + +{{% /notice %}} + +The URL to use is `https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp`. (Splunk has Realms in key geographical locations around the world for data residency). + +The **otlphttp** exporter can also be configured to send traces and logs by defining a target URL for `traces_endpoint` and `logs_endpoint` respectively. Configuring these is outside the scope of this workshop. + +```yaml {hl_lines="5"} +exporters: + logging: + verbosity: normal + otlphttp/splunk: + metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp +``` + +By default, `gzip` compression is enabled for all endpoints. This can be disabled by setting `compression: none` in the exporter configuration. We will leave compression enabled for this workshop and accept the default as this is the most efficient way to send data. + +In order to send metrics to Splunk Observability Cloud, we need to use an Access Token. This can be done by creating a new token in the Splunk Observability Cloud UI. For more information on how to create a token, see [Create a token](https://docs.splunk.com/Observability/admin/authentication-tokens/org-tokens.html). The token needs to be of type **INGEST**. + +{{% notice style="note" %}} +If you are an attendee to a Splunk hosted workshop, the instance your are using has already been configured with an Access Token (which has been set as an environment variable). We will reference that environment variable in our configuration file. Otherwise, you will need to create a new token and set it as an environment variable e.g. + +``` bash +export ACCESS_TOKEN= +``` + +{{% /notice %}} + +The token is defined in the configuration file by inserting `X-SF-TOKEN: ${env:ACCESS_TOKEN}` under a `headers:` section: + +```yaml {hl_lines="6-8"} +exporters: + logging: + verbosity: normal + otlphttp/splunk: + metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp + headers: + X-SF-TOKEN: ${env:ACCESS_TOKEN} +``` + +## Configuration Check-in + +Now that we've covered exporters, let's check our configuration changes: + +--- + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{< tabs >}} +{{% tab title="config.yaml" %}} + +```yaml {lineNos="table" wrap="true" hl_lines="72-76"} +extensions: + health_check: + endpoint: 0.0.0.0:13133 + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + hostmetrics: + collection_interval: 10s + scrapers: + # CPU utilization metrics + cpu: + # Disk I/O metrics + disk: + # File System utilization metrics + filesystem: + # Memory utilization metrics + memory: + # Network interface I/O metrics & TCP connection metrics + network: + # CPU load metrics + load: + # Paging/Swap space utilization and I/O metrics + paging: + # Process count metrics + processes: + # Per process CPU, Memory and Disk I/O metrics. Disabled by default. + # process: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus/internal: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] + resourcedetection/ec2: + detectors: [ec2] + attributes/conf: + actions: + - key: participant.name + action: insert + value: "INSERT_YOUR_NAME_HERE" + +exporters: + logging: + verbosity: normal + otlphttp/splunk: + metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp + headers: + X-SF-TOKEN: ${env:ACCESS_TOKEN} + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [otlp, opencensus, prometheus] + processors: [batch] + exporters: [logging] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{< /tabs >}} +{{% /expand %}} + +--- + +Of course, you can easily configure the `metrics_endpoint` to point to any other solution that supports the **OTLP** protocol. + +Next, we need to enable the receivers, processors and exporters we have just configured in the service section of the `config.yaml`. diff --git a/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md b/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md new file mode 100644 index 0000000000..70d028dac6 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md @@ -0,0 +1,27 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6.1 Host Metrics +weight: 1 +--- + +## Hostmetrics Receiver + +If you recall from the Receivers portion of the workshop, we defined the [Host Metrics Receiver](../3-receivers/#host-metrics-receiver) to generate metrics about the host system, which are scraped from various sources. To enable the receiver, we must include the `hostmetrics` receiver in the metrics pipeline. + +In the `metrics` pipeline, add `hostmetrics` to the metrics `receivers` section. + +```yaml {hl_lines="11"} +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus] + processors: [batch] + exporters: [logging] +``` diff --git a/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md b/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md new file mode 100644 index 0000000000..761c95b795 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md @@ -0,0 +1,27 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6.2 Prometheus +weight: 2 +--- + +## Prometheus Internal Receiver + +Earlier in the workshop, we also renamed the `prometheus` receiver to reflect that is was collecting metrics internal to the collector, renaming it to `prometheus/internal`. + + We now need to enable the `prometheus/internal` receiver under the metrics pipeline. Update the `receivers` section to include `prometheus/internal` under the `metrics` pipeline: + +```yaml {hl_lines="11"} +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus/internal] + processors: [batch] + exporters: [logging] +``` diff --git a/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md b/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md new file mode 100644 index 0000000000..8d4b1fe367 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md @@ -0,0 +1,27 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6.3 Resource Detection +weight: 3 +--- + +## Resource Detection Processor + +We also added `resourcedetection/system` and `resourcedetection/ec2` processors so that the collector can capture the instance hostname and AWS/EC2 metadata. We now need to enable these two processors under the metrics pipeline. + +Update the `processors` section to include `resourcedetection/system` and `resourcedetection/ec2` under the `metrics` pipeline: + +```yaml {hl_lines="12"} +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus/internal] + processors: [batch, resourcedetection/system, resourcedetection/ec2] + exporters: [logging] +``` diff --git a/content/ja/other/opentelemetry-collector/6-service/4-attributes.md b/content/ja/other/opentelemetry-collector/6-service/4-attributes.md new file mode 100644 index 0000000000..661a403dd6 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/4-attributes.md @@ -0,0 +1,27 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6.4 Attributes +weight: 4 +--- + +## Attributes Processor + +Also in the Processors section of this workshop, we added the `attributes/conf` processor so that the collector will inset a new attribute called `participant.name` to all the metrics. We now need to enable this under the metrics pipeline. + +Update the `processors` section to include `attributes/conf` under the `metrics` pipeline: + +```yaml {hl_lines="12"} +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus/internal] + processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf] + exporters: [logging] +``` diff --git a/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md b/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md new file mode 100644 index 0000000000..6095fbb0a2 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md @@ -0,0 +1,248 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6.5 OTLP HTTP +weight: 5 +--- + +## OTLP HTTP Exporter + +In the Exporters section of the workshop, we configured the `otlphttp` exporter to send metrics to Splunk Observability Cloud. We now need to enable this under the metrics pipeline. + +Update the `exporters` section to include `otlphttp/splunk` under the `metrics` pipeline: + +```yaml {hl_lines="13"} +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus/internal] + processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf] + exporters: [logging, otlphttp/splunk] +``` + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Observing the collector internals{{% /badge %}}" %}} + +The collector captures internal signals about its behavior this also include additional signals from running components. +The reason for this is that components that make decisions about the flow of data need a way to surface that information +as metrics or traces. + +## Why monitor the collector? + +This is somewhat of a chicken and egg problem of, "Who is watching the the watcher?", but it is important that we can surface this information. Another interesting part of the collector's history is that it existed before the Go metrics' SDK was considered stable so the collector exposes a prometheus endpoint to provide this functionality for the time being. + +## Considerations + +Monitoring the internal usage of each running collector in your organisation can contribute a significant amount of new Metric Time Series (MTS). The Splunk distribution has curated these metrics for you and would be able to to help forcast the expected increases. + +## The Ninja Zone + +To expose the internal observability of the collector, there are some additional settings that can be adjusted: + +{{< tabs >}} +{{% tab title="telemetry schema" %}} + +```yaml +service: + telemetry: + logs: + level: + development: + encoding: + disable_caller: + disable_stacktrace: + output_paths: [, paths...] + error_output_paths: [, paths...] + initial_fields: + key: value + metrics: + level: + # Address binds the promethues endpoint to scrape + address: +``` + +{{% /tab %}} +{{% tab title="example-config.yml" %}} + +```yaml +service: + telemetry: + logs: + level: info + encoding: json + disable_stacktrace: true + initial_fields: + instance.name: ${env:INSTANCE} + metrics: + address: localhost:8888 +``` + +{{% /tab %}} +{{< /tabs >}} + +## References + +1. [https://opentelemetry.io/docs/collector/configuration/#service](https://opentelemetry.io/docs/collector/configuration/#service) + +{{% /expand %}} + +--- + +## Final configuration + +--- + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your final configuration{{% /badge %}}" %}} +{{< tabs >}} +{{% tab title="config.yaml" %}} + +``` yaml {lineNos="table" wrap="true"} +extensions: + health_check: + endpoint: 0.0.0.0:13133 + pprof: + endpoint: 0.0.0.0:1777 + zpages: + endpoint: 0.0.0.0:55679 + +receivers: + hostmetrics: + collection_interval: 10s + scrapers: + # CPU utilization metrics + cpu: + # Disk I/O metrics + disk: + # File System utilization metrics + filesystem: + # Memory utilization metrics + memory: + # Network interface I/O metrics & TCP connection metrics + network: + # CPU load metrics + load: + # Paging/Swap space utilization and I/O metrics + paging: + # Process count metrics + processes: + # Per process CPU, Memory and Disk I/O metrics. Disabled by default. + # process: + otlp: + protocols: + grpc: + http: + + opencensus: + + # Collect own metrics + prometheus/internal: + config: + scrape_configs: + - job_name: 'otel-collector' + scrape_interval: 10s + static_configs: + - targets: ['0.0.0.0:8888'] + + jaeger: + protocols: + grpc: + thrift_binary: + thrift_compact: + thrift_http: + + zipkin: + +processors: + batch: + resourcedetection/system: + detectors: [system] + system: + hostname_sources: [os] + resourcedetection/ec2: + detectors: [ec2] + attributes/conf: + actions: + - key: participant.name + action: insert + value: "INSERT_YOUR_NAME_HERE" + +exporters: + logging: + verbosity: normal + otlphttp/splunk: + metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp + headers: + X-SF-TOKEN: ${env:ACCESS_TOKEN} + +service: + + pipelines: + + traces: + receivers: [otlp, opencensus, jaeger, zipkin] + processors: [batch] + exporters: [logging] + + metrics: + receivers: [hostmetrics, otlp, opencensus, prometheus/internal] + processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf] + exporters: [logging, otlphttp/splunk] + + extensions: [health_check, pprof, zpages] +``` + +{{% /tab %}} +{{% /tabs %}} + +{{% /expand %}} + +--- + +{{% notice style="tip" %}} +It is recommended that you validate your configuration file before restarting the collector. You can do this by using the built-in `validate` command: + +{{< tabs >}} +{{% tab title="Command" %}} + +``` bash +otelcol-contrib validate --config=file:/etc/otelcol-contrib/config.yaml +``` + +{{% /tab %}} +{{% tab title="Example error output" %}} + +``` text +Error: failed to get config: cannot unmarshal the configuration: 1 error(s) decoding: + +* error decoding 'processors': error reading configuration for "attributes/conf": 1 error(s) decoding: + +* 'actions[0]' has invalid keys: actions +2023/06/29 09:41:28 collector server run finished with error: failed to get config: cannot unmarshal the configuration: 1 error(s) decoding: + +* error decoding 'processors': error reading configuration for "attributes/conf": 1 error(s) decoding: + +* 'actions[0]' has invalid keys: actions +``` + +{{% /tab %}} +{{< /tabs >}} +{{% /notice %}} + +Now that we have a working configuration, let's start the collector and then check to see what [zPages](../2-extensions/#zpages) is reporting. + +{{% tab title="Command" %}} + +``` bash +otelcol-contrib --config=file:/etc/otelcol-contrib/config.yaml +``` + +{{% /tab %}} + +![pipelinez-full-config](../../images/pipelinez-full-config.png) diff --git a/content/ja/other/opentelemetry-collector/6-service/_index.md b/content/ja/other/opentelemetry-collector/6-service/_index.md new file mode 100644 index 0000000000..0ac2319593 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/6-service/_index.md @@ -0,0 +1,26 @@ +--- +title: OpenTelemetry Collector Service +linkTitle: 6. Service +weight: 6 +--- + +The **Service** section is used to configure what components are enabled in the Collector based on the configuration found in the receivers, processors, exporters, and extensions sections. + +{{% notice style="info" %}} +If a component is configured, but not defined within the **Service** section then it is **not** enabled. +{{% /notice %}} + +The service section consists of three sub-sections: + +- extensions +- pipelines +- telemetry + +In the default configuration, the extension section has been configured to enable `health_check`, `pprof` and `zpages`, which we configured in the Extensions module earlier. + +``` yaml +service: + extensions: [health_check, pprof, zpages] +``` + +So lets configure our Metric Pipeline! diff --git a/content/ja/other/opentelemetry-collector/7-visualisation/index.files/dashboard_OTel-Contrib-Dashboard.json b/content/ja/other/opentelemetry-collector/7-visualisation/index.files/dashboard_OTel-Contrib-Dashboard.json new file mode 100644 index 0000000000..672c86cad5 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/7-visualisation/index.files/dashboard_OTel-Contrib-Dashboard.json @@ -0,0 +1,1418 @@ +{ + "chartExports": [ + { + "chart": { + "autoDetectRelatedDetectorIds": [], + "created": 0, + "creator": null, + "customProperties": {}, + "description": "", + "id": "FybsAETAwAI", + "importOf": "FwPCYY8AIB0", + "lastUpdated": 0, + "lastUpdatedBy": null, + "name": "Disk free", + "options": { + "colorBy": "Dimension", + "colorScale2": null, + "hideMissingValues": false, + "legendOptions": { + "fields": [ + { + "enabled": false, + "property": "dsname" + }, + { + "enabled": false, + "property": "host" + }, + { + "enabled": false, + "property": "sf_originatingMetric" + }, + { + "enabled": false, + "property": "sf_metric" + }, + { + "enabled": false, + "property": "plugin" + }, + { + "enabled": true, + "property": "plugin_instance" + }, + { + "enabled": false, + "property": "fs_type" + }, + { + "enabled": 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"programText": "A = data('system.cpu.load_average.1m').mean().publish(label='A')\nB = data('system.cpu.load_average.5m').mean().publish(label='B')\nC = data('system.cpu.load_average.15m').mean().publish(label='C')", + "relatedDetectorIds": [], + "tags": null + } + } + ], + "crossLinkExports": [], + "dashboardExports": [ + { + "dashboard": { + "authorizedWriters": null, + "chartDensity": "DEFAULT", + "charts": [ + { + "chartId": "FybsAETAwAY", + "column": 3, + "height": 1, + "row": 0, + "width": 3 + }, + { + "chartId": "FybsAETAwAw", + "column": 6, + "height": 1, + "row": 0, + "width": 3 + }, + { + "chartId": "FybsAETAwAk", + "column": 9, + "height": 1, + "row": 0, + "width": 3 + }, + { + "chartId": "FybsAETAwAM", + "column": 0, + "height": 1, + "row": 0, + "width": 3 + }, + { + "chartId": "FybsAETAwAo", + "column": 0, + "height": 1, + "row": 1, + "width": 6 + }, + { + "chartId": "FybsAETAwA0", + "column": 6, + "height": 1, + "row": 1, + "width": 6 + }, + { + "chartId": "FybsAETAwAU", + "column": 0, + "height": 1, + "row": 2, + "width": 6 + }, + { + "chartId": "FybsAETAwAQ", + "column": 6, + "height": 1, + "row": 2, + "width": 6 + }, + { + "chartId": "FybsAETAwAs", + "column": 0, + "height": 1, + "row": 3, + "width": 6 + }, + { + "chartId": "FybsAETAwAI", + "column": 6, + "height": 1, + "row": 3, + "width": 6 + }, + { + "chartId": "FybsAETAwAc", + "column": 0, + "height": 1, + "row": 4, + "width": 6 + }, + { + "chartId": "FybsAETAwAg", + "column": 6, + "height": 1, + "row": 4, + "width": 6 + } + ], + "created": 0, + "creator": null, + "customProperties": null, + "description": "", + "discoveryOptions": null, + "eventOverlays": null, + "filters": { + "sources": null, + "time": { + "end": "Now", + "start": "-5m" + }, + "variables": [ + { + "alias": "host", + "applyIfExists": false, + "description": "Host running collectd", + "preferredSuggestions": [], + "property": "host", + "propertyMappings": [ + "host", + "host.name" + ], + "replaceOnly": false, + "required": true, + "restricted": false, + "value": [ + "*" + ] + } + ] + }, + "groupId": "FybsAETAwAE", + "groupName": "OpenTelemetry Contrib", + "id": "FybsAETAwA4", + "importOf": "FwPCYY8AICQ", + "lastUpdated": 0, + "lastUpdatedBy": null, + "maxDelayOverride": null, + "name": "OTel Contrib Dashboard", + "permissions": null, + "selectedEventOverlays": [], + "tags": null + } + } + ], + "groupExport": { + "group": { + "authorizedWriters": null, + "created": 0, + "creator": null, + "dashboardConfigs": [ + { + "configId": "FwPCYY8AICU", + "dashboardId": "FybsAETAwA4", + "descriptionOverride": null, + "filtersOverride": null, + "nameOverride": null + } + ], + "dashboards": [ + "FybsAETAwA4" + ], + "description": "", + "email": null, + "id": "FybsAETAwAE", + "importDetails": { + "hashCode": -1470956163, + "importOf": "FwOxtI_AEB4", + "importTime": 1686585381165 + }, + "importOf": "FwOxtI_AEB4", + "lastUpdated": 0, + "lastUpdatedBy": null, + "name": "OpenTelemetry Contrib", + "permissions": null, + "teams": null + } + }, + "hashCode": 390745185, + "id": "FybsAETAwAE", + "modelVersion": 1, + "packageType": "GROUP" +} \ No newline at end of file diff --git a/content/ja/other/opentelemetry-collector/7-visualisation/index.md b/content/ja/other/opentelemetry-collector/7-visualisation/index.md new file mode 100644 index 0000000000..58223c5680 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/7-visualisation/index.md @@ -0,0 +1,44 @@ +--- +title: Data Visualisations +linkTitle: 7. Visualisation +weight: 7 +--- + +## Splunk Observability Cloud + +Now that we have configured the OpenTelemetry Collector to send metrics to Splunk Observability Cloud, let's take a look at the data in Splunk Observability Cloud. If you have not received an invite to Splunk Observability Cloud, your instructor will provide you with login credentials. + +Before that, lets make things a little more interesting and run a stress test on the instance. This in turn will light up the dashboards. + +``` bash +sudo apt install stress +while true; do stress -c 2 -t 40; stress -d 5 -t 40; stress -m 20 -t 40; done +``` + +Once you are logged into Splunk Observability Cloud, using the left-hand navigation, navigate to **Dashboards**: + +![menu-dashboards](../images/menu-dashboards.png) + +In the search box, search for **OTel Contrib**: + +![search-dashboards](../images/search-dashboards.png) + +{{% notice style="info" %}} +If the dashboard does not exist, then your instructor will be able to quickly add it. If you are not attending a Splunk hosted version of this workshop then the Dashboard Group to import can be found at the bottom of this page. +{{% /notice %}} + +Click on the **OTel Contrib Dashboard** dashboard to open it: + +![otel-dashboard](../images/otel-dashboard.png) + +In the **Filter** box, at the top of the dashboard, type in **participant** and select **participant.name**: + +![search-filter](../images/search-filter.png) + +You can either start typing in your name you configured for `participant.name` in the `config.yaml` or you can select your name from the list: + +![select-conf-attendee-name](../images/select-participant-name.png) + +You can now see the host metrics for the host upon which you configured the OpenTelemetry Collector. + +{{% attachments sort="asc" style="info" title="Download Dashboard JSON for importing" /%}} diff --git a/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md b/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md new file mode 100644 index 0000000000..d8d0263b9c --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md @@ -0,0 +1,35 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8.1 Project Setup +weight: 9 +--- + +## Project Setup {{% badge style=primary icon=user-ninja %}}**Ninja**{{% /badge %}} + +{{% notice style="note" %}} + +The time to finish this section of the workshop can vary depending on experience. + +A complete solution can be found [here](https://github.com/splunk/collector-workshop-example) incase you're stuck or want to follow +along with the instructor. + +{{% /notice %}} + +To get started developing a the new _Jenkins CI_ receiver, we first need to set up a Golang project. +The steps to create your new Golang project is: + +1. Create a new directoy named `${HOME}/go/src/jenkinscireceiver` and change into it + 1. The actual directory name or location is not strict, you can choose your own development directory to make it in. +1. Initialise the golang module by going `go mod init splunk.conf/workshop/example/jenkinscireceiver` + 1. This will create a file named `go.mod` which is used to track our direct and indirect dependencies + 1. Eventually there will be a `go.sum` which is the checksum values of the depedancies being imported. + +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your go.mod{{% /badge %}}" %}} + +``` text +module splunk.conf/workshop/example/jenkinscireceiver + +go 1.20 +``` + +{{% /expand %}} diff --git a/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md b/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md new file mode 100644 index 0000000000..a6093af4fa --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md @@ -0,0 +1,98 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8.2 Configuration +weight: 10 +--- + +## Building The Configuration + +The configuration portion of the component is how the user is able to have their inputs over the component, +so the values that is used for the configuration need to be: + +1. Intuitive for users to understand what that field controls +1. Be explicit in what is required and what is optional +1. Reuse common names and fields +1. Keep the options simple + +{{% tabs %}} +{{% tab title="bad config" %}} + +```yaml +--- +jenkins_server_addr: hostname +jenkins_server_api_port: 8089 +interval: 10m +filter_builds_by: + - name: my-awesome-build + status: amber +track: + values: + example.metric.1: yes + example.metric.2: yes + example.metric.3: no + example.metric.4: no +``` + +{{% /tab %}} +{{% tab title="good config" %}} + +``` yaml +--- +# Required Values +endpoint: http://my-jenkins-server:8089 +auth: + authenticator: basicauth/jenkins +# Optional Values +collection_interval: 10m +metrics: + example.metric.1: + enabled: true + example.metric.2: + enabled: true + example.metric.3: + enabled: true + example.metric.4: + enabled: true +``` + +{{% /tab %}} +{{% /tabs %}} + +The bad configuration highlights how doing the opposite of the recommendations of configuration practices impacts the usability +of the component. It doesn't make it clear what field values should be, it includes features that can be pushed to existing processors, +and the field naming is not consistent with other components that exist in the collector. + +The good configuration keeps the required values simple, reuses field names from other components, and ensures the component focuses on +just the interaction between Jenkins and the collector. + +The code tab shows how much is required to be added by us and what is already provided for us by shared libraries within the collector. +These will be explained in more detail once we get to the business logic. The configuration should start off small and will change +once the business logic has started to include additional features that is needed. + +## Write the code + +In order to implement the code needed for the configuration, we are going to create a new file named `config.go` with the following content: + +``` go +package jenkinscireceiver + +import ( + "go.opentelemetry.io/collector/config/confighttp" + "go.opentelemetry.io/collector/receiver/scraperhelper" + + "splunk.conf/workshop/example/jenkinscireceiver/internal/metadata" +) + +type Config struct { + // HTTPClientSettings contains all the values + // that are commonly shared across all HTTP interactions + // performed by the collector. + confighttp.HTTPClientSettings `mapstructure:",squash"` + // ScraperControllerSettings will allow us to schedule + // how often to check for updates to builds. + scraperhelper.ScraperControllerSettings `mapstructure:",squash"` + // MetricsBuilderConfig contains all the metrics + // that can be configured. + metadata.MetricsBuilderConfig `mapstructure:",squash"` +} +``` diff --git a/content/ja/other/opentelemetry-collector/8-develop/3-component.md b/content/ja/other/opentelemetry-collector/8-develop/3-component.md new file mode 100644 index 0000000000..91951c0b7b --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/3-component.md @@ -0,0 +1,70 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8.3 Component Review +weight: 11 +--- + +## Component Review + +To recap the type of component we will need to in order to capture metrics from Jenkins: + +{{% tabs %}} +{{% tab title="Extension" %}} +The business use case an extension helps solves for are: + +1. Having shared functionality that requires runtime configuration +1. Indirectly helps with observing the runtime of the collector + +See [Extensions Overview](../2-extensions) for more details. +{{% /tab %}} +{{% tab title="Receiver" %}} +The business use case a receiver solves for: + +- Fetching data from a remote source +- Receiving data from remote source(s) + +This are commonly referred to _pull_ vs _push_ based data collection, and you read more about the details in the [Receiver Overview](../3-receivers). +{{% /tab %}} +{{% tab title="Processor" %}} +The business use case a processor solves for is: + +- Adding or removing data, fields, or values +- Observing and making decisions on the data +- Buffering, queueing, and reordering + +The thing to keep in mind that the data type flowing through a processor needs to use the forward +the same data type to its downstream components. +Read through [Processor Overview](../4-processors) for the details. +{{% /tab %}} +{{% tab title="Exporter" %}} +The business use case an exporter solves for: + +- Send the data to a tool, service, or storage + +The OpenTelemetry collector does not want to be "backend", an all in one observability suite, but rather +keep to the principles that founded OpenTelemetry to begin with; A vendor agnostic Observability for all. +To help revisit the details, please read through [Exporter Overview](../5-exporters). + +{{% /tab %}} +{{% tab title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Connectors{{% /badge %}}" %}} + +This is a component type that was missed in the workshop since it is a relatively new addition to the collector, +but the best way to think about a connector is that it is like a processor that allows to be used across different +telemetry types, and pipelines. Meaning that a connector can accept data as logs, and output metrics, or accept +metrics from one pipeline and provide metrics on the data it has observed. + +The business case that a connector solves for: + +- Converting from different telemetry types + - logs to metrics + - traces to metrics + - metrics to logs +- Observing incoming data and producing its own data + - Accepting metrics and generating analytical metrics of the data. + +There was a brief overview within the **Ninja** section as part of the [Processor Overview](../4-processors), +and be sure what the project for updates for new connector components. +{{% /tab %}} +{{% /tabs %}} + +From the component overviews, it is clear that developing a pull based receiver for Jenkins. diff --git a/content/ja/other/opentelemetry-collector/8-develop/4-design.md b/content/ja/other/opentelemetry-collector/8-develop/4-design.md new file mode 100644 index 0000000000..50bba23807 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/4-design.md @@ -0,0 +1,250 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8.4 Designing the Metrics +weight: 12 +--- + +### Designing The Metrics + +To help define and export the metrics captured by our receiver, we will be using, [mdatagen](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/cmd/mdatagen), a tool developed for the collector that turns yaml defined metrics into code. + +{{% tabs %}} +{{% tab title="metadata.yaml"%}} + +``` yaml +--- +# Type defines the name to reference the component +# in the configuration file +type: jenkins + +# Status defines the component type and the stability level +status: + class: receiver + stability: + development: [metrics] + +# Attributes are the expected fields reported +# with the exported values. +attributes: + job.name: + description: The name of the associated Jenkins job + type: string + job.status: + description: Shows if the job had passed, or failed + type: string + enum: + - failed + - success + - unknown + +# Metrics defines all the pontentially exported values from this receiver. +metrics: + jenkins.jobs.count: + enabled: true + description: Provides a count of the total number of configured jobs + unit: "{Count}" + gauge: + value_type: int + jenkins.job.duration: + enabled: true + description: Show the duration of the job + unit: "s" + gauge: + value_type: int + attributes: + - job.name + - job.status + jenkins.job.commit_delta: + enabled: true + description: The calculation difference of the time job was finished minus commit timestamp + unit: "s" + gauge: + value_type: int + attributes: + - job.name + - job.status +``` + +{{% /tab %}} +{{% tab title="gen.go" %}} + +``` go +// To generate the additional code needed to capture metrics, +// the following command to be run from the shell: +// go generate -x ./... + +//go:generate go run github.com/open-telemetry/opentelemetry-collector-contrib/cmd/mdatagen@v0.80.0 metadata.yaml +package jenkinscireceiver + +// There is no code defined within this file. +``` + +{{% /tab%}} +{{% /tabs %}} + +Create these files within the project folder before continuing onto the next section. + +## Building The Factory + +The Factory is a software design pattern that effectively allows for an object, in this case a `jenkinscireceiver`, to be created +dynamically with the provided configuration. To use a more real world example, it would be going to a phone store, asking for a phone +that matches your exact description, and then provides it to you. + +Run the following command `go generate -x ./...` , it will create a new folder, `jenkinscireceiver/internal/metadata`, +that contains all code required to export the defined metrics. The required code is: + +{{% tabs %}} +{{% tab title="factory.go" %}} + +``` go +package jenkinscireceiver + +import ( + "errors" + + "go.opentelemetry.io/collector/component" + "go.opentelemetry.io/collector/config/confighttp" + "go.opentelemetry.io/collector/receiver" + "go.opentelemetry.io/collector/receiver/scraperhelper" + + "splunk.conf/workshop/example/jenkinscireceiver/internal/metadata" +) + +func NewFactory() receiver.Factory { + return receiver.NewFactory( + metadata.Type, + newDefaultConfig, + receiver.WithMetrics(newMetricsReceiver, metadata.MetricsStability), + ) +} + +func newMetricsReceiver(_ context.Context, set receiver.CreateSettings, cfg component.Config, consumer consumer.Metrics) (receiver.Metrics, error) { + // Convert the configuration into the expected type + conf, ok := cfg.(*Config) + if !ok { + return nil, errors.New("can not convert config") + } + sc, err := newScraper(conf, set) + if err != nil { + return nil, err + } + return scraperhelper.NewScraperControllerReceiver( + &conf.ScraperControllerSettings, + set, + consumer, + scraperhelper.AddScraper(sc), + ) +} +``` + +{{% /tab %}} +{{% tab title="config.go" %}} + +``` go +package jenkinscireceiver + +import ( + "go.opentelemetry.io/collector/config/confighttp" + "go.opentelemetry.io/collector/receiver/scraperhelper" + + "splunk.conf/workshop/example/jenkinscireceiver/internal/metadata" +) + +type Config struct { + // HTTPClientSettings contains all the values + // that are commonly shared across all HTTP interactions + // performed by the collector. + confighttp.HTTPClientSettings `mapstructure:",squash"` + // ScraperControllerSettings will allow us to schedule + // how often to check for updates to builds. + scraperhelper.ScraperControllerSettings `mapstructure:",squash"` + // MetricsBuilderConfig contains all the metrics + // that can be configured. + metadata.MetricsBuilderConfig `mapstructure:",squash"` +} + +func newDefaultConfig() component.Config { + return &Config{ + ScraperControllerSettings: scraperhelper.NewDefaultScraperControllerSettings(metadata.Type), + HTTPClientSettings: confighttp.NewDefaultHTTPClientSettings(), + MetricsBuilderConfig: metadata.DefaultMetricsBuilderConfig(), + } +} +``` + +{{% /tab %}} +{{% tab title="scraper.go" %}} + +``` go +package jenkinscireceiver + +type scraper struct {} + +func newScraper(cfg *Config, set receiver.CreateSettings) (scraperhelper.Scraper, error) { + // Create a our scraper with our values + s := scraper{ + // To be filled in later + } + return scraperhelper.NewScraper(metadata.Type, s.scrape) +} + +func (scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { + // To be filled in + return pmetrics.NewMetrics(), nil +} +``` + +{{% /tab %}} +{{% tab title="build-config.yaml" %}} + +``` yaml +--- +dist: + name: otelcol + description: "Conf workshop collector" + output_path: ./dist + version: v0.0.0-experimental + +extensions: + - gomod: github.com/open-telemetry/opentelemetry-collector-contrib/extension/basicauthextension v0.80.0 + - gomod: github.com/open-telemetry/opentelemetry-collector-contrib/extension/healthcheckextension v0.80.0 + +receivers: + - gomod: go.opentelemetry.io/collector/receiver/otlpreceiver v0.80.0 + - gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/jaegerreceiver v0.80.0 + - gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/prometheusreceiver v0.80.0 + - gomod: splunk.conf/workshop/example/jenkinscireceiver v0.0.0 + path: ./jenkinscireceiver + +processors: + - gomod: go.opentelemetry.io/collector/processor/batchprocessor v0.80.0 + +exporters: + - gomod: go.opentelemetry.io/collector/exporter/loggingexporter v0.80.0 + - gomod: go.opentelemetry.io/collector/exporter/otlpexporter v0.80.0 + - gomod: go.opentelemetry.io/collector/exporter/otlphttpexporter v0.80.0 + +# This replace is a go directive that allows for redefine +# where to fetch the code to use since the default would be from a remote project. +replaces: +- splunk.conf/workshop/example/jenkinscireceiver => ./jenkinscireceiver +``` + +{{% /tab %}} +{{% tab title="project layout" %}} + +``` text +├── build-config.yaml +└── jenkinscireceiver + ├── go.mod + ├── config.go + ├── factory.go + ├── scraper.go + └── internal + └── metadata +``` + +{{% /tab %}} +{{% /tabs %}} + +Once you have written these file into the project with the expected contents then run, `go mod tidy`, which will fetch all the remote depedancies and update `go.mod` and generate the `go.sum` files. diff --git a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md new file mode 100644 index 0000000000..ee2eee3edb --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md @@ -0,0 +1,237 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8.5 Building Business Logic +weight: 13 +--- + +## Building The Business Logic + +At this point, we have a custom component that currently does nothing so we need to add in the required +logic to capture this data from Jenkins. + +From this point, the steps that we need to take are: + +1. Create a client that connect to Jenkins +1. Capture all the configured jobs +1. Report the status of the last build for the configured job +1. Calculate the time difference between commit timestamp and job completion. + +The changes will be made to `scraper.go`. + +{{% tabs %}} +{{% tab title="1. Add Jenkins client" %}} + +To be able to connect to the Jenkins server, we will be using the package, +["github.com/yosida95/golang-jenkins"](https://pkg.go.dev/github.com/yosida95/golang-jenkins), +which provides the functionality required to read data from the jenkins server. + +Then we are going to utilise some of the helper functions from the, +["go.opentelemetry.io/collector/receiver/scraperhelper"](https://pkg.go.dev/go.opentelemetry.io/collector/receiver/scraperhelper) , +library to create a start function so that we can connect to the Jenkins server once component has finished starting. + +```go +package jenkinscireceiver + +import ( + "context" + + jenkins "github.com/yosida95/golang-jenkins" + "go.opentelemetry.io/collector/component" + "go.opentelemetry.io/collector/pdata/pmetric" + "go.opentelemetry.io/collector/receiver" + "go.opentelemetry.io/collector/receiver/scraperhelper" + + "splunk.conf/workshop/example/jenkinscireceiver/internal/metadata" +) + +type scraper struct { + mb *metadata.Metricsbuilder + client *jenkins.Jenkins +} + +func newScraper(cfg *Config, set receiver.CreateSettings) (scraperhelper.Scraper, error) { + s := &scraper{ + mb : metadata.NewMetricsBuilder(cfg.MetricsBuilderConfig, set), + } + + return scraperhelper.NewScraper( + metadata.Type, + s.scrape, + scarperhelper.WithStart(func(ctx context.Context, h component.Host) error { + client, err := cfg.ToClient(h, set) + if err != nil { + return err + } + // The collector provides a means of injecting authentication + // on our behalf, so this will ignore the libraries approach + // and use the configured http client with authentication. + s.client = jenkins.NewJenkins(nil, cfg.Endpoint) + s.client.SetHTTPClient(client) + return nil + }) + ) +} + +func (scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { + // To be filled in + return pmetric.NewMetrics(), nil +} + +``` + +This finishes all the setup code that is required in order to initialise a Jenkins receiver. +{{% /tab%}} +{{% tab title="2. Capture all configured jobs" %}} + +From this point on, we will be focuses on the `scrape` method that has been waiting to be filled in. +This method will be run on each interval that is configured within the configuration (by default, every minute). + +The reason we want to capture the number of jobs configured so we can see the growth of our Jenkins server, +and measure of many projects have onboarded. To do this we will call the jenkins client to list all jobs, +and if it reports an error, return that with no metrics, otherwise, emit the data from the metric builder. + +```go +func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { + jobs, err := s.client.GetJobs() + if err != nil { + return pmetric.Metrics{}, err + } + + // Recording the timestamp to ensure + // all captured data points within this scrape have the same value. + now := pcommon.NewTimestampFromTime(time.Now()) + + // Casting to an int64 to match the expected type + s.mb.RecordJenkinsJobsCountDataPoint(now, int64(len(jobs))) + + // To be filled in + + return s.mb.Emit(), nil +} +``` + +{{% /tab%}} +{{% tab title="3. Report the status of each job" %}} + +In the last step, we were able to capture all jobs ands report the number of jobs +there was. Within this step, we are going to examine each job and use the report values +to capture metrics. + +```go +func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { + jobs, err := s.client.GetJobs() + if err != nil { + return pmetric.Metrics{}, err + } + + // Recording the timestamp to ensure + // all captured data points within this scrape have the same value. + now := pcommon.NewTimestampFromTime(time.Now()) + + // Casting to an int64 to match the expected type + s.mb.RecordJenkinsJobsCountDataPoint(now, int64(len(jobs))) + + for _, job := range jobs { + // Ensure we have valid results to start off with + var ( + build = job.LastCompletedBuild + status = metadata.AttributeJobStatusUnknown + ) + + // This will check the result of the job, however, + // since the only defined attributes are + // `success`, `failure`, and `unknown`. + // it is assume that anything did not finish + // with a success or failure to be an unknown status. + + switch build.Result { + case "aborted", "not_built", "unstable": + status = metadata.AttributeJobStatusUnknown + case "success": + status = metadata.AttributeJobStatusSuccess + case "failure": + status = metadata.AttributeJobStatusFailed + } + + s.mb.RecordJenkinsJobDurationDataPoint( + now, + int64(job.LastCompletedBuild.Duration), + job.Name, + status, + ) + } + + return s.mb.Emit(), nil +} +``` +{{% /tab%}} +{{% tab title="4. Report the delta" %}} + +The final step is to calculate how long it took from +commit to job completion to help infer our DORA metrics. + +```go +func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { + jobs, err := s.client.GetJobs() + if err != nil { + return pmetric.Metrics{}, err + } + + // Recording the timestamp to ensure + // all captured data points within this scrape have the same value. + now := pcommon.NewTimestampFromTime(time.Now()) + + // Casting to an int64 to match the expected type + s.mb.RecordJenkinsJobsCountDataPoint(now, int64(len(jobs))) + + for _, job := range jobs { + // Ensure we have valid results to start off with + var ( + build = job.LastCompletedBuild + status = metadata.AttributeJobStatusUnknown + ) + + // Previous step here + + // Ensure that the `ChangeSet` has values + // set so there is a valid value for us to reference + if len(build.ChangeSet.Items) == 0 { + continue + } + + // Making the assumption that the first changeset + // item is the most recent change. + change := build.ChangeSet.Items[0] + + // Record the difference from the build time + // compared against the change timestamp. + s.mb.RecordJenkinsJobCommitDeltaDataPoint( + now, + int64(build.Timestamp-change.Timestamp), + job.Name, + status, + ) + } + + return s.mb.Emit(), nil +} +``` + +{{% /tab%}} +{{% /tabs %}} + +Once all of these steps have been completed, you now have built a custom Jenkins CI receiver! + +## Whats next? + +There are more than likely features that would be desired from component that you can think of, like: + +- Can I include the branch name that the job used? +- Can I include the project name for the job? +- How I calculate the collective job durations for project? +- How do I validate the changes work? + +Please take this time to play around, break it, change things around, or even try to capture logs from the builds. + + +[^1]: [DORA Metrics](https://cloud.google.com/blog/products/devops-sre/using-the-four-keys-to-measure-your-devops-performance) diff --git a/content/ja/other/opentelemetry-collector/8-develop/_index.md b/content/ja/other/opentelemetry-collector/8-develop/_index.md new file mode 100644 index 0000000000..ac314df769 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/8-develop/_index.md @@ -0,0 +1,39 @@ +--- +title: OpenTelemetry Collector Development +linkTitle: 8. Develop +weight: 8 +--- + +## Developing a custom component + +Building a component for the Open Telemetry Collector requires three key parts: + +1. The Configuration - _What values are exposed to the user to configure_ +1. The Factory - _Make the component using the provided values_ +1. The Business Logic - _What the component needs to do_ + +For this, we will use the example of building a component that works with Jenkins so that we can track important DevOps metrics of our project(s). + +The metrics we are looking to measure are: + +1. Lead time for changes - _"How long it takes for a commit to get into production"_ +1. Change failure rate - _"The percentage of deployments causing a failure in production"_ +1. Deployment frequency - _"How often a [team] successfully releases to production"_ +1. Mean time to recover - _"How long does it take for a [team] to recover from a failure in production"_ + +These indicators were identified Google's DevOps Research and Assesment (DORA)[^1] team to help +show performance of a software development team. The reason for choosing _Jenkins CI_ is that we remain in the same Open Source Software ecosystem which we can serve as the example for the vendor managed CI tools to adopt in future. + +## Instrument Vs Component + +There is something to consider when improving level of Observability within your organisation +since there are some trade offs that get made. + +| | Pros | Cons | +| ----- | ----- | ----- | +| **(Auto) Instrumented** | Does not require an external API to be monitored in order to observe the system. | Changing instrumentation requires changes to the project. | +| | Gives system owners/developers to make changes in their observability. | Requires additional runtime dependancies. | +| | Understands system context and can corrolate captured data with _Exemplars_. | Can impact performance of the system. | +| **Component** | - Changes to data names or semantics can be rolled out independently of the system's release cycle. | Breaking API changes require a coordinated release between system and collector. | +| | Updating/extending data collected is a seemless user facing change. | Captured data semantics can unexpectedly break that does not align with a new system release. | +| | Does not require the supporting teams to have a deep understanding of observability practice. | Strictly external / exposed information can be surfaced from the system. | diff --git a/content/ja/other/opentelemetry-collector/_index.md b/content/ja/other/opentelemetry-collector/_index.md new file mode 100644 index 0000000000..a09ced7ba7 --- /dev/null +++ b/content/ja/other/opentelemetry-collector/_index.md @@ -0,0 +1,77 @@ +--- +title: OpenTelemetryでクラウドネイティブ環境のオブザーバビリティを実現する +linkTitle: OpenTelemetry Collector +weight: 10 +alwaysopen: false +description: OpenTelemetry Collectorのコンセプトを学び、Splunk Observability Cloudにデータを送信する方法を理解しましょう。 +--- + +## 概要 + +OpenTelemetry を使い始める場合は、バックエンドに直接データを送ることから始めるかもしれません。最初のステップとしてはよいですが、OpenTelemetry Collectorをオブザーバビリティのアーキテクチャとして使用するのは多くの利点があり、本番環境ではCollectorを使ったデプロイを推奨しています。 + +このワークショップでは、OpenTelemetry Collectorを使用することに焦点を当て、Splunk Observability Cloud で使用するためのレシーバー、プロセッサー、エクスポーターを定義し、実際にテレメトリデータを送信するためのパイプラインを設定することで、環境に合わせてCollectorを活用を学びます。また、分散プラットフォームのビジネスニーズに対応するための、カスタムコンポーネントを追加できるようになるまでの道のりを進むことになります。 + +### Ninja セクション + +ワークショップの途中には、展開できる {{% badge style=primary icon=user-ninja %}}Ninja セクション{{% /badge %}} があります。これらはより実践的で、ワークショップ内または自分の時間でさらに技術的な詳細に取り組むことができます。 + +OpenTelemetryプロジェクトは頻繁に開発されているため、Ninjaセクションの内容が古くなる可能性があることに注意してください。コンテンツが古い場合には更新のリクエストを出すこともできますので、必要なものを見つけた場合はお知らせください。 + +--- + +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** をテストして！{{% /badge %}}" %}} +**このワークショップを完了すると、正式に OpenTelemetry Collector ニンジャになります！** +{{% /expand %}} + +--- + +## 対象者 + +このワークショップは、OpenTelemetry Collectorのアーキテクチャとデプロイメントについてさらに学びたいと考えている開発者やシステム管理者を対象としています。 + +## 前提条件 +- データ収集に関する基本的な理解 +- コマンドラインとvim/viの経験 +- Ubuntu 20.04 LTSまたは22.04 LTSが稼働するインスタンス/ホスト/VM + - 最小要件はAWS/EC2 t2.micro（1 CPU、1GB RAM、8GBストレージ） + +## 学習目標 + +このセッションの終わりまでに、参加者は以下を行うことができるようになります： + +- OpenTelemetryのコンポーネントを理解する +- レシーバー、プロセッサー、エクスポーターを使用してデータを収集・分析する +- OpenTelemetryを使用する利点を特定する +- 自分たちのビジネスニーズに対応するカスタムコンポーネントを構築する + +## OpenTelemetryのアーキテクチャー + +{{< mermaid >}} +%%{ + init:{ + "theme":"base", + "themeVariables": { + "primaryColor": "#ffffff", + "clusterBkg": "#eff2fb", + "defaultLinkColor": "#333333" + } + } +}%% + +flowchart LR; + subgraph Collector + A[OTLP] --> M(Receivers) + B[JAEGER] --> M(Receivers) + C[Prometheus] --> M(Receivers) + end + subgraph Processors + M(Receivers) --> H(Filters, Attributes, etc) + E(Extensions) + end + subgraph Exporters + H(Filters, Attributes, etc) --> S(OTLP) + H(Filters, Attributes, etc) --> T(JAEGER) + H(Filters, Attributes, etc) --> U(Prometheus) + end +{{< /mermaid >}} diff --git a/content/ja/other/opentelemetry-collector/images/extensionz.png 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zY^-WofTx%k&MgZwsY;yl&h$EdE^+MhM12$%dHuH$Ss?uV;@Ws)=p{z}^zrY2)T|JV zn^ThXJj7ai;98BpqP0++-NOS5)S2;^0iRm^VXZG#xbz8t=eU-_3J_8sZKhlP$N&7$ kzl8N)CGgw-$9iWBGx~yyTwXTy_f*@jN6-9%J?x+If9XsbrvLx| literal 0 HcmV?d00001 From eee404860029aef04c5f2ac19036c0c813de8966 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 20 Nov 2023 17:45:36 +0900 Subject: [PATCH 02/12] translated: installing --- .../1-installation/1-confirmation.md | 98 ++++++++++--------- .../1-installation/_index.md | 15 +-- 2 files changed, 58 insertions(+), 55 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md index edcbed1059..a5267833e2 100644 --- a/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md +++ b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md @@ -1,12 +1,12 @@ --- -title: Installing OpenTelemetry Collector Contrib -linkTitle: 1.1 Confirm Installation +title: OpenTelemetry Collector Contribをインストールする +linkTitle: 1.1 インストールを確認する weight: 1 --- -## Confirm the Collector is running +## Collector が動作していることを確認する -The collector should now be running. We will verify this as root using `systemctl` command. To exit the status just press `q`. +これで、Collectorが動いているはずです。root権限で `systemctl` コマンドを使って、それを確かめてみましょう。ステータス表示を中止するには `q` を押してください。 {{< tabs >}} {{% tab title="Command" %}} @@ -44,7 +44,7 @@ May 16 08:23:39 ip-10-0-9-125 otelcol-contrib[1415]: {"kind": "exporter" {{% /tab %}} {{< /tabs >}} -As will be running the rest of the workshop using the `otelcol-contrib` standalone binary, we will stop the service and then disable it from starting on boot: +このワークショップでは、ここで設定した `otelcol-contrib` のスタンドアローンで動作するバイナリーを使っていきます。サービスを停止して、自動起動を無効化するために、次のコマンドを使ってください: {{< tabs >}} {{% tab title="Command" %}} @@ -68,10 +68,11 @@ sudo systemctl disable otelcol-contrib --- -{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Build your own collector using Open Telemetry Collector Builder (ocb){{% /badge %}}" %}} -For this part we will require the following installed on your system: +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Open Telemetry Collector Builder (ocb) を使って、独自のコレクターを作る {{% /badge %}}" %}} -- Golang (latest version) +このパートでは、お使いのシステムに以下のものがインストールされている必要があります： + +- Go (latest version) ``` bash cd /tmp @@ -79,36 +80,36 @@ For this part we will require the following installed on your system: sudo tar -C /usr/local -xzf go1.20.linux-amd64.tar.gz ``` - Edit `.profile` and add the following environment variables: - + `.profile` を編集して、次の環境変数をセットします: + ``` bash export GOROOT=/usr/local/go export GOPATH=$HOME/go export PATH=$GOPATH/bin:$GOROOT/bin:$PATH ``` - Renew your shell session: + そして、シェルのセッションを更新します: ``` bash source ~/.profile ``` - Check Go version: - + Goのバージョンを確認します: + ``` bash go version ``` -- ocb installed - - Download the ocb binary from the [project releases](https://github.com/open-telemetry/opentelemetry-collector/releases/tag/cmd%2Fbuilder%2Fv0.80.0) - and run the following commands: - +- ocb のインストール + - ocbバイナリーを [project releases](https://github.com/open-telemetry/opentelemetry-collector/releases/tag/cmd%2Fbuilder%2Fv0.80.0) + からダウンロードして、次のコマンドを実行します: + ```bash mv ocb_0.80.0_darwin_arm64 /usr/bin/ocb chmod 755 /usr/bin/ocb ``` - An alternative approach would be to use the golang tool chain to build the binary locally by doing: + 別のアプローチとしては、Goのツールチェーンを使ってバイナリをローカルにビルドする方法もあります: ```bash go install go.opentelemetry.io/collector/cmd/builder@v0.80.0 @@ -117,44 +118,45 @@ For this part we will require the following installed on your system: - (Optional) Docker -## Why build your own collector? +## なぜ独自のコレクターをビルドするの？ + +コレクターのデフォルトのディストリビューション（coreおよびcontrib）は、含まれれるコンポーネントが少なすぎたり、もしくは多すぎたりします。 -The default distribution of the collector (core and contrib) either contain too much or too little in what they have to offer. +本番環境でcontribコレクターを実行することはできますが、インストールされているコンポーネントの量が多く、デプロイに必要ではないものも含まれるため、一般的には推奨されません。 -It is also not advised to run the contrib collector in your production environments due to the amount of components installed which more than likely are not needed by your deployment. +## 独自のコレクターをビルドする利点は？ -## Benefits of building your own collector? +独自のコレクターバイナリー（通常は「ディストリビューション」と呼ばれる）を作成することで、必要なものだけをビルドすることができます。 -When creating your own collector binaries, (commonly referred to as distribution), means you build what you need. +メリットは次のとおりです: -The benefits of this are: +1. バイナリーのサイズが小さい +2. 一般的なGoの脆弱性スキャナーを利用できる +3. 組織独自のコンポーネントを組み込むことができる -1. Smaller sized binaries -2. Can use existing go scanners for vulnerabilities -3. Include internal components that can tie in with your organisation +## カスタムコレクターをビルドするときの注意事項は？ -## Considerations for building your own collector? +さて、これは Ninja ゾーンの人たちにあえて言うことではないかもしれませんが: -Now, this would not be a 🥷 Ninja zone if it didn't come with some draw backs: +1. Goの開発経験は、必須ではないが、推奨される +1. Splunkのサポートが **ない** +1. ディストリビューションのライフサイクルを管理しなければならない -1. Go experience is recommended if not required -1. **No** Splunk support -1. Responsibility of distribution and lifecycle management +プロジェクトは安定性に向けて進んでいますが、行われた変更がワークフローを壊す可能性があることに注意してください。Splunkチームは、より高い安定性とサポートを提供し、デプロイメントニーズに対応するためのキュレーションされた経験を提供しています。 -It is important to note that project is working towards stability but it does not mean changes made will not break your workflow. The team at Splunk provide increased support and a higher level of stability so they can provide a curated experience helping you with your deployment needs. +## Ninja ゾーン -## The Ninja Zone +必要なツールをすべてインストールしたら、以下のディレクトリ構造に従い、 `otelcol-builder.yaml` という新しいファイルを作成します: -Once you have all the required tools installed to get started, you will need to create a new file named `otelcol-builder.yaml` and we will follow this directory structure: ``` bash . └── otelcol-builder.yaml ``` -Once we have the file created, we need to add a list of components for it to install with some additional metadata. +ファイルを作成したら、インストールするコンポーネントのリストと追加のメタデータを追加する必要があります。 -For this example, we are going to create a builder manifest that will install only the components we need for the introduction config: +この例では、導入設定に必要なコンポーネントのみをインストールするためのビルダーマニフェストを作成します: ```yaml dist: @@ -187,13 +189,13 @@ receivers: - gomod: github.com/open-telemetry/opentelemetry-collector-contrib/receiver/zipkinreceiver v0.80.0 ``` -Once the yaml file has been updated for the _ocb_, then run the following command: +_ocb_ のためのyamlファイルを作成して更新したら、 次のコマンドを実行します: ```shell ocb --config=otelcol-builder.yaml ``` -Which leave you with the following directory structure: +すると、次のようなディレクトリ構造が作成されます: ``` text ├── dist @@ -208,7 +210,7 @@ Which leave you with the following directory structure: └── otelcol-builder.yaml ``` -### References +### リファレンス 1. [https://opentelemetry.io/docs/collector/custom-collector/](https://opentelemetry.io/docs/collector/custom-collector/) @@ -216,9 +218,9 @@ Which leave you with the following directory structure: --- -## Default configuration +## デフォルト設定 -OpenTelemetry is configured through YAML files. These files have default configurations that we can modify to meet our needs. Let's look at the default configuration that is supplied: +OpenTelemetry Collectorは YAML ファイルを使って設定をしていきます。これらのファイルには、必要に応じて変更できるデフォルト設定が含まれています。提供されているデフォルト設定を見てみましょう: {{< tabs >}} {{% tab title="Command" %}} @@ -291,16 +293,16 @@ service: {{% /tab %}} {{< /tabs >}} -Congratulations! You have successfully downloaded and installed the OpenTelemetry Collector. You are well on your way to becoming an OTel Ninja. But first lets walk through configuration files and different distributions of the OpenTelemetry Collector. +おめでとうございます！OpenTelemetry Collectorのダウンロードとインストールに成功しました。あなたはOTel Ninjaになる準備ができました。しかしまずは、設定ファイルとOpenTelemetry Collectorの異なるディストリビューションについて見ていきましょう。 {{% notice style="note" %}} -Splunk does provide its own, fully supported, distribution of the OpenTelemetry Collector. This distribution is available to install from the [Splunk GitHub Repository](https://github.com/signalfx/splunk-otel-collector) or via a wizard in Splunk Observability Cloud that will build out a simple installation script to copy and paste. This distribution includes a number of additional features and enhancements that are not available in the OpenTelemetry Collector Contrib distribution. +Splunkは、自社で完全にサポートされたOpenTelemetry Collectorのディストリビューションを提供しています。このディストリビューションは、[Splunk GitHub Repository](https://github.com/signalfx/splunk-otel-collector)からインストールするか、Splunk Observability Cloudのウィザードを使用して、簡単なインストールスクリプトを作成し、コピー＆ペーストすることで利用できます。このディストリビューションには、OpenTelemetry Collector Contribディストリビューションにはない追加機能や強化が含まれています。 -- The Splunk Distribution of the OpenTelemetry Collector is production tested; it is in use by the majority of customers in their production environments. -- Customers that use our distribution can receive direct help from official Splunk support within SLA's. -- Customers can use or migrate to the Splunk Distribution of the OpenTelemetry Collector without worrying about future breaking changes to its core configuration experience for metrics and traces collection (OpenTelemetry logs collection configuration is in beta). There may be breaking changes to the Collector's own metrics. +- SplunkのOpenTelemetry Collectorディストリビューションは本番環境でテスト済みであり、多くの顧客が本番環境で使用しています。 +- このディストリビューションを使用する顧客は、SLA内で公式のSplunkサポートから直接支援を受けることができます。 +- メトリクスとトレース収集のコア構成体験に将来的な破壊的変更がないことを心配せずに、SplunkのOpenTelemetry Collectorディストリビューションを使用または移行することができます（OpenTelemetryログ収集の設定はベータ版です）。Collector自身のメトリクスに破壊的変更がある可能性はあります。 {{% /notice %}} -We will now walk through each section of the configuration file and modify it to send host metrics to Splunk Observability Cloud. +このセクションでは、ホストメトリクスをSplunk Observability Cloudに送信するために、設定ファイルの各セクションを詳しく見ていき、変更する方法について説明します。 diff --git a/content/ja/other/opentelemetry-collector/1-installation/_index.md b/content/ja/other/opentelemetry-collector/1-installation/_index.md index 4e7bae1abe..0d72bfaec8 100644 --- a/content/ja/other/opentelemetry-collector/1-installation/_index.md +++ b/content/ja/other/opentelemetry-collector/1-installation/_index.md @@ -1,22 +1,23 @@ --- -title: Installing OpenTelemetry Collector Contrib -linkTitle: 1. Installation +title: OpenTelemetry Collector Contribをインストールする +linkTitle: 1. インストール weight: 1 --- -## Download the OpenTelemetry Collector Contrib distribution +## OpenTelemetry Collectorの Contrib ディストリビューションをダウンロードする -The first step in installing the Open Telemetry Collector is downloading it. For our lab we will use the `wget` command to download the `.deb` package from the OpenTelemetry Github repository. +OpenTelemetry Collectorのインストールのために、まずはダウンロードするのが最初のステップです。このラボでは、 `wget` コマンドを使って OpenTelemetry の GitHub リポジトリから `.deb` パッケージをダウンロードしていきます。 -Obtain the `.deb` package for your platform from the [OpenTelemetry Collector Contrib releases page](https://github.com/open-telemetry/opentelemetry-collector-releases/releases) +[OpenTelemetry Collector Contrib releases page](https://github.com/open-telemetry/opentelemetry-collector-releases/releases) +から、ご利用のプラットフォーム用の `.deb` パッケージを入手してください。 ``` bash wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v0.80.0/otelcol-contrib_0.80.0_linux_amd64.deb ``` -## Install the OpenTelemetry Collector Contrib distribution +## OpenTelemetry Collectorの Contrib ディストリビューションをインストールする -Install the `.deb` package using `dpkg`. Take a look at the **dpkg Output** tab below to see what the example output of a successful install will look like: +`dpkg` を使って、 `.deb` パッケージをインストールします。下記の **dpkg Output** のようになれば、インストールは成功です！ {{< tabs >}} {{% tab title="Install" %}} From d36610417b2073244efeca3da4be1c7119c69cd0 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Wed, 22 Nov 2023 16:48:44 +0900 Subject: [PATCH 03/12] translated Extentions --- .../1-installation/1-confirmation.md | 34 ++++++------- .../1-installation/_index.md | 8 ++-- .../2-extensions/1-health.md | 12 ++--- .../2-extensions/2-performance.md | 6 +-- .../2-extensions/3-zpages.md | 48 +++++++++---------- .../2-extensions/_index.md | 6 +-- .../other/opentelemetry-collector/_index.md | 16 +++---- 7 files changed, 65 insertions(+), 65 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md index a5267833e2..ae9d98e3b9 100644 --- a/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md +++ b/content/ja/other/opentelemetry-collector/1-installation/1-confirmation.md @@ -6,7 +6,7 @@ weight: 1 ## Collector が動作していることを確認する -これで、Collectorが動いているはずです。root権限で `systemctl` コマンドを使って、それを確かめてみましょう。ステータス表示を中止するには `q` を押してください。 +これで、Collector が動いているはずです。root権限で `systemctl` コマンドを使って、それを確かめてみましょう。ステータス表示を中止するには `q` を押してください。 {{< tabs >}} {{% tab title="Command" %}} @@ -94,14 +94,14 @@ sudo systemctl disable otelcol-contrib source ~/.profile ``` - Goのバージョンを確認します: + Go のバージョンを確認します: ``` bash go version ``` - ocb のインストール - - ocbバイナリーを [project releases](https://github.com/open-telemetry/opentelemetry-collector/releases/tag/cmd%2Fbuilder%2Fv0.80.0) + - ocb バイナリーを [project releases](https://github.com/open-telemetry/opentelemetry-collector/releases/tag/cmd%2Fbuilder%2Fv0.80.0) からダウンロードして、次のコマンドを実行します: ```bash @@ -109,7 +109,7 @@ sudo systemctl disable otelcol-contrib chmod 755 /usr/bin/ocb ``` - 別のアプローチとしては、Goのツールチェーンを使ってバイナリをローカルにビルドする方法もあります: + 別のアプローチとして、Go のツールチェーンを使ってバイナリをローカルにビルドする方法もあります: ```bash go install go.opentelemetry.io/collector/cmd/builder@v0.80.0 @@ -120,9 +120,9 @@ sudo systemctl disable otelcol-contrib ## なぜ独自のコレクターをビルドするの？ -コレクターのデフォルトのディストリビューション（coreおよびcontrib）は、含まれれるコンポーネントが少なすぎたり、もしくは多すぎたりします。 +コレクターのデフォルトのディストリビューション（core および contrib）は、含まれれるコンポーネントが少なすぎたり、もしくは多すぎたりします。 -本番環境でcontribコレクターを実行することはできますが、インストールされているコンポーネントの量が多く、デプロイに必要ではないものも含まれるため、一般的には推奨されません。 +本番環境で contrib コレクターを実行することはできますが、インストールされているコンポーネントの量が多く、デプロイに必要ではないものも含まれるため、一般的には推奨されません。 ## 独自のコレクターをビルドする利点は？ @@ -131,18 +131,18 @@ sudo systemctl disable otelcol-contrib メリットは次のとおりです: 1. バイナリーのサイズが小さい -2. 一般的なGoの脆弱性スキャナーを利用できる +2. 一般的な Go の脆弱性スキャナーを利用できる 3. 組織独自のコンポーネントを組み込むことができる ## カスタムコレクターをビルドするときの注意事項は？ さて、これは Ninja ゾーンの人たちにあえて言うことではないかもしれませんが: -1. Goの開発経験は、必須ではないが、推奨される -1. Splunkのサポートが **ない** +1. Go の開発経験を、必須ではないが、推奨される +1. Splunk の **サポートがない** 1. ディストリビューションのライフサイクルを管理しなければならない -プロジェクトは安定性に向けて進んでいますが、行われた変更がワークフローを壊す可能性があることに注意してください。Splunkチームは、より高い安定性とサポートを提供し、デプロイメントニーズに対応するためのキュレーションされた経験を提供しています。 +プロジェクトは安定性に向けて進んでいますが、行われた変更がワークフローを壊す可能性があることに注意してください。Splunk チームは、より高い安定性とサポートを提供し、デプロイメントニーズに対応するためのキュレーションされた経験を提供しています。 ## Ninja ゾーン @@ -220,7 +220,7 @@ ocb --config=otelcol-builder.yaml ## デフォルト設定 -OpenTelemetry Collectorは YAML ファイルを使って設定をしていきます。これらのファイルには、必要に応じて変更できるデフォルト設定が含まれています。提供されているデフォルト設定を見てみましょう: +OpenTelemetry Collector は YAML ファイルを使って設定をしていきます。これらのファイルには、必要に応じて変更できるデフォルト設定が含まれています。提供されているデフォルト設定を見てみましょう: {{< tabs >}} {{% tab title="Command" %}} @@ -293,16 +293,16 @@ service: {{% /tab %}} {{< /tabs >}} -おめでとうございます！OpenTelemetry Collectorのダウンロードとインストールに成功しました。あなたはOTel Ninjaになる準備ができました。しかしまずは、設定ファイルとOpenTelemetry Collectorの異なるディストリビューションについて見ていきましょう。 +おめでとうございます！OpenTelemetry Collector のダウンロードとインストールに成功しました。あなたは OTel Ninja になる準備ができました。しかしまずは、設定ファイルと OpenTelemetry Collector の異なるディストリビューションについて見ていきましょう。 {{% notice style="note" %}} -Splunkは、自社で完全にサポートされたOpenTelemetry Collectorのディストリビューションを提供しています。このディストリビューションは、[Splunk GitHub Repository](https://github.com/signalfx/splunk-otel-collector)からインストールするか、Splunk Observability Cloudのウィザードを使用して、簡単なインストールスクリプトを作成し、コピー＆ペーストすることで利用できます。このディストリビューションには、OpenTelemetry Collector Contribディストリビューションにはない追加機能や強化が含まれています。 +Splunk は、自社で完全にサポートされた OpenTelemetry Collector のディストリビューションを提供しています。このディストリビューションは、[Splunk GitHub Repository](https://github.com/signalfx/splunk-otel-collector) からインストールするか、Splunk Observability Cloud のウィザードを使用して、簡単なインストールスクリプトを作成し、コピー＆ペーストすることで利用できます。このディストリビューションには、OpenTelemetry Collector Contrib ディストリビューションにはない追加機能や強化が含まれています。 -- SplunkのOpenTelemetry Collectorディストリビューションは本番環境でテスト済みであり、多くの顧客が本番環境で使用しています。 -- このディストリビューションを使用する顧客は、SLA内で公式のSplunkサポートから直接支援を受けることができます。 -- メトリクスとトレース収集のコア構成体験に将来的な破壊的変更がないことを心配せずに、SplunkのOpenTelemetry Collectorディストリビューションを使用または移行することができます（OpenTelemetryログ収集の設定はベータ版です）。Collector自身のメトリクスに破壊的変更がある可能性はあります。 +- Splunk の OpenTelemetry Collector ディストリビューションは本番環境でテスト済みであり、多くの顧客が本番環境で使用しています。 +- このディストリビューションを使用する顧客は、公式の Splunk サポートから、SLA の範囲内で直接支援を受けることができます。 +- メトリクスとトレース収集のコア構成体験に将来的な破壊的変更がないことを心配せずに、Splunk の OpenTelemetry Collector ディストリビューションを使用または移行することができます（OpenTelemetry ログ収集の設定はベータ版です）。Collector 自身のメトリクスに破壊的変更がある可能性はあります。 {{% /notice %}} -このセクションでは、ホストメトリクスをSplunk Observability Cloudに送信するために、設定ファイルの各セクションを詳しく見ていき、変更する方法について説明します。 +このセクションでは、ホストメトリクスを Splunk Observability Cloud に送信するために、設定ファイルの各セクションを詳しく見ていき、変更する方法について説明します。 diff --git a/content/ja/other/opentelemetry-collector/1-installation/_index.md b/content/ja/other/opentelemetry-collector/1-installation/_index.md index 0d72bfaec8..59b2615de2 100644 --- a/content/ja/other/opentelemetry-collector/1-installation/_index.md +++ b/content/ja/other/opentelemetry-collector/1-installation/_index.md @@ -1,12 +1,12 @@ --- -title: OpenTelemetry Collector Contribをインストールする +title: OpenTelemetry Collector Contrib をインストールする linkTitle: 1. インストール weight: 1 --- -## OpenTelemetry Collectorの Contrib ディストリビューションをダウンロードする +## OpenTelemetry Collector の Contrib ディストリビューションをダウンロードする -OpenTelemetry Collectorのインストールのために、まずはダウンロードするのが最初のステップです。このラボでは、 `wget` コマンドを使って OpenTelemetry の GitHub リポジトリから `.deb` パッケージをダウンロードしていきます。 +OpenTelemetry Collector のインストールのために、まずはダウンロードするのが最初のステップです。このラボでは、 `wget` コマンドを使って OpenTelemetry の GitHub リポジトリから `.deb` パッケージをダウンロードしていきます。 [OpenTelemetry Collector Contrib releases page](https://github.com/open-telemetry/opentelemetry-collector-releases/releases) から、ご利用のプラットフォーム用の `.deb` パッケージを入手してください。 @@ -15,7 +15,7 @@ OpenTelemetry Collectorのインストールのために、まずはダウンロ wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v0.80.0/otelcol-contrib_0.80.0_linux_amd64.deb ``` -## OpenTelemetry Collectorの Contrib ディストリビューションをインストールする +## OpenTelemetry Collector の Contrib ディストリビューションをインストールする `dpkg` を使って、 `.deb` パッケージをインストールします。下記の **dpkg Output** のようになれば、インストールは成功です！ diff --git a/content/ja/other/opentelemetry-collector/2-extensions/1-health.md b/content/ja/other/opentelemetry-collector/2-extensions/1-health.md index f34cfddc5d..208276c683 100644 --- a/content/ja/other/opentelemetry-collector/2-extensions/1-health.md +++ b/content/ja/other/opentelemetry-collector/2-extensions/1-health.md @@ -1,12 +1,12 @@ --- -title: OpenTelemetry Collector Extensions +title: OpenTelemetry Collector エクステンション linkTitle: 2.1 Health Check weight: 1 --- -## Health Check +## Health Check エクステンション -Extensions are configured in the same `config.yaml` file that we referenced in the installation step. Let's edit the `config.yaml` file and configure the extensions. Note that the **pprof** and **zpages** extensions are already configured in the default `config.yaml` file. For the purpose of this workshop, we will only be updating the **health_check** extension to expose the port on all network interfaces on which we can access the health of the collector. +他のコンポーネントと同様に、エクステンションは `config.yaml` ファイルで設定できます。ここでは実際に `config.yaml` ファイルを編集して、エクステンションを設定していきましょう。デフォルトの `config.yaml` では、すでに **pprof** エクステンションと **zpages** エクステンションが設定されていることを確認してみてください。このワークショップでは、設定ファイルをアップデートして **health_check** エクステンションを追加し、ポートを解放し、外部ネットワークからコレクターのヘルスチェックにアクセスできるようにしていきます。 {{% tab title="Command" %}} @@ -26,7 +26,7 @@ extensions: {{% /tab %}} -Start the collector: +コレクターを起動します: {{% tab title="Command" %}} @@ -36,9 +36,9 @@ otelcol-contrib --config=file:/etc/otelcol-contrib/config.yaml {{% /tab %}} -This extension enables a HTTP URL that can be probed to check the status of the OpenTelemetry Collector. This extension can be used as a liveness and/or readiness probe on Kubernetes. To learn more about the `curl` command, check out the [curl man page](https://curl.se/docs/manpage.html). +このエクステンションはHTTPのURLを公開し、OpenTelemetory Collectorの稼働状況をチェックするプローブを提供します。このエクステンションはKubernetes環境でのLiveness/Readinessプローブとしても使われています。 `curl` コマンドの使い方は、[curl man page](https://curl.se/docs/manpage.html) を参照してください。 -Open a new terminal session and SSH into your instance to run the following command: +ターミナルを開いて、対象インスタンスにSSH接続し、次のコマンドを実行します: {{< tabs >}} {{% tab title="curl Command" %}} diff --git a/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md b/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md index b29172f14c..0024c1504e 100644 --- a/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md +++ b/content/ja/other/opentelemetry-collector/2-extensions/2-performance.md @@ -1,9 +1,9 @@ --- -title: OpenTelemetry Collector Extensions +title: OpenTelemetry Collector エクステンション linkTitle: 2.2 Performance Profiler weight: 2 --- -## Performance Profiler +## Performance Profiler エクステンション -[**Performance Profiler**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/extension/pprofextension/README.md) extension enables the golang net/http/pprof endpoint. This is typically used by developers to collect performance profiles and investigate issues with the service. **We will not be covering this in this workshop**. +[**Performance Profiler**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/extension/pprofextension/README.md) エクステンションは、Go の net/http/pprof エンドポイントを有効化します。これは通常、開発者がパフォーマンスプロファイルを収集し、サービスの問題を調査するために使用します。**このワークショップでは詳しく紹介はしません**。 diff --git a/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md index b586f0fd78..55aa32479c 100644 --- a/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md +++ b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md @@ -1,37 +1,37 @@ --- -title: OpenTelemetry Collector Extensions +title: OpenTelemetry Collector エクステンション linkTitle: 2.3 zPages weight: 3 --- -## zPages +## zPages エクステンション -[**zPages**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/extension/zpagesextension/README.md) are an in-process alternative to external exporters. When included, they collect and aggregate tracing and metrics information in the background; this data is served on web pages when requested. zPages are an extremely useful diagnostic feature to ensure the collector is running as expected. +[**zPages**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/extension/zpagesextension/README.md) は、外部エクスポータに代わるプロセス内部の機能です。有効化すると、バックグラウンドでトレースとメトリクス情報を収集し、集計し、どのようなデータを扱ったかの Web ページを公開します。zpages は、コレクターが期待どおりに動作していることを確認するための非常に便利な診断機能です。 {{< tabs >}} {{% tab title="ServiceZ" %}} -**ServiceZ** gives an overview of the collector services and quick access to the pipelinez, extensionz, and featurez zPages. The page also provides build and runtime information. +**ServiceZ** は、コレクターサービスの概要と、pipelinez、extensionz、featurez zPages へのクイックアクセスを提供します。このページでは、ビルドとランタイムの情報も提供します。 -Example URL: [http://localhost:55679/debug/servicez](http://localhost:55679/debug/servicez) (change `localhost` to reflect your own environment). +URL: [http://localhost:55679/debug/servicez](http://localhost:55679/debug/servicez) (`localhost` は、適切なホスト名に切り替えてください) ![ServiceZ](../../images/servicez.png) {{% /tab %}} {{% tab title="PipelineZ" %}} -**PipelineZ** provides insights on the running pipelines running in the collector. You can find information on type, if data is mutated, and you can also see information on the receivers, processors and exporters that are used for each pipeline. +**PipelineZ** は、コレクターで実行中のパイプラインに関する情報を提供します。タイプ、データが変更されているか、各パイプラインで使用されているレシーバー、プロセッサー、エクスポーターの情報を見ることができます。 -Example URL: [http://localhost:55679/debug/pipelinez](http://localhost:55679/debug/pipelinez) (change `localhost` to reflect your own environment). +URL: [http://localhost:55679/debug/pipelinez](http://localhost:55679/debug/pipelinez) (`localhost` は、適切なホスト名に切り替えてください) ![PipelineZ](../../images/pipelinez.png) {{% /tab %}} {{% tab title="ExtensionZ" %}} -**ExtensionZ** shows the extensions that are active in the collector. +**ExtensionZ** は、コレクターで有効化されたエクステンションを確認できます。 -Example URL: [http://localhost:55679/debug/extensionz](http://localhost:55679/debug/extensionz) (change `localhost` to reflect your own environment). +Example URL: [http://localhost:55679/debug/extensionz](http://localhost:55679/debug/extensionz) (`localhost` は、適切なホスト名に切り替えてください) ![ExtensionZ](../../images/extensionz.png) @@ -39,7 +39,7 @@ Example URL: [http://localhost:55679/debug/extensionz](http://localhost:55679/de {{% /tabs %}} {{% notice style="info" %}} -If you are not following along, you can use your browser to access a test environment emitting zPages information at: +ついていけない場合は、ブラウザーでzPagesの情報を発信しているテスト環境にアクセスしてください： - **ServiceZ:** [http://63.33.64.193:55679/debug/servicez](http://63.33.64.193:55679/debug/servicez) - **PipelineZ:** [http://63.33.64.193:55679/debug/pipelinez](http://63.33.64.193:55679/debug/pipelinez) @@ -48,9 +48,9 @@ If you are not following along, you can use your browser to access a test enviro --- -{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Improve data durability with storage extension{{% /badge %}}" %}} +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** storage エクステンションでデータの耐久性を向上させる{{% /badge %}}" %}} -For this, we will need to validate that our distribution has the `file_storage` extension installed. This can be done by running the command `otelcol-contrib components` which should show results like: +これをこなうには、ディストリビューションに `file_storage` エクステンションモジュールがインストールされていることを確認する必要があります。確認するには、`otelcol-contrib components` コマンドを実行します: {{< tabs >}} {{% tab title="Truncated Output" %}} @@ -236,9 +236,9 @@ extensions: {{% /tab %}} {{< /tabs >}} -This extension provides exporters the ability to queue data to disk in the event that exporter is unable to send data to the configured endpoint. +このエクステンションは、エクスポーターが設定されたエンドポイントにデータを送信できない事象が発生したときに、データをディスクにキューイングする機能をエクスポーターに提供します。 -In order to configure the extension, you will need to update your config to include the information below. First, be sure to create a /tmp/otel-data directory and give it read/write permissions: +このエクステンションを設定するには、以下の情報を含むように設定を更新する必要があります。まず、 /tmp/otel-data ディレクトリを作成し、読み取り/書き込み権限を与えてください： ```yaml extensions: @@ -259,15 +259,15 @@ service: extensions: [health_check, pprof, zpages, file_storage] ``` -## Why queue data to disk? +## なぜキューデータをディスクに書くの？ -This allows the collector to weather network interruptions (and even collector restarts) to ensure data is sent to the upstream provider. +コレクターはネットワークの不調（および、コレクターの再起動）を乗り切って、アップストリームプロバイダーに確実にデータを送信できるようになります。 -## Considerations for queuing data to disk? +## キューデータをディスクに書く時の注意事項は？ -There is a potential that this could impact data throughput performance due to disk performance. +ディスクの性能により、データスループットの性能に影響を与える可能性があります -### References +### 参照 1. [https://community.splunk.com/t5/Community-Blog/Data-Persistence-in-the-OpenTelemetry-Collector/ba-p/624583](https://community.splunk.com/t5/Community-Blog/Data-Persistence-in-the-OpenTelemetry-Collector/ba-p/624583) 2. [https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/storage/filestorage](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/storage/filestorage) @@ -276,13 +276,13 @@ There is a potential that this could impact data throughput performance due to d --- -## Configuration Check-in +## Check-in: エクステンションの設定 -Now that we've covered extensions, let's check our configuration changes. +さて、エクステンションについて説明したので、設定の変更箇所を確認していきましょう。 --- -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}設定ファイルを確認してください{{% /badge %}}" %}} {{< tabs >}} {{% tab title="config.yaml" %}} @@ -351,6 +351,6 @@ service: --- -Now that we have reviewed extensions, let's dive into the data pipeline portion of the workshop. A pipeline defines a path the data follows in the Collector starting from reception, moving to further processing or modification, and finally exiting the Collector via exporters. +さて、エクステンションについて復習したところで、ワークショップのデータパイプラインの部分に飛び込んでみましょう。パイプラインとは、コレクター内でデータがたどる経路を定義するもので、レシーバーから始まり、追加の処理や変更をし、最終的にエクスポーターを経由してコレクターを出ます。 -The data pipeline in the OpenTelemetry Collector is made up of receivers, processors, and exporters. We will first start with receivers. +OpenTelemetry Collector のデータパイプラインは、レシーバー、プロセッサー、エクスポーターで構成されています。まずは、レシーバーから見ていきましょう。 diff --git a/content/ja/other/opentelemetry-collector/2-extensions/_index.md b/content/ja/other/opentelemetry-collector/2-extensions/_index.md index d04111e890..f240384dc2 100644 --- a/content/ja/other/opentelemetry-collector/2-extensions/_index.md +++ b/content/ja/other/opentelemetry-collector/2-extensions/_index.md @@ -1,10 +1,10 @@ --- -title: OpenTelemetry Collector Extensions -linkTitle: 2. Extensions +title: OpenTelemetry Collector エクステンション +linkTitle: 2. エクステンション weight: 2 --- -Now that we have the OpenTelemetry Collector installed, let's take a look at extensions for the OpenTelemetry Collector. Extensions are optional and available primarily for tasks that do not involve processing telemetry data. Examples of extensions include health monitoring, service discovery, and data forwarding. +さて、OpenTelemetry Collector はインストールできました。次は OpenTelemetry Collector のエクステンション（拡張機能）を見てみましょう。エクステンションはオプションで、主にテレメトリーデータの処理を伴わないタスクで使用できます。例としては、ヘルスモニタリング、サービスディスカバリ、データ転送などがあります。 {{< mermaid >}} %%{ diff --git a/content/ja/other/opentelemetry-collector/_index.md b/content/ja/other/opentelemetry-collector/_index.md index a09ced7ba7..8efef69fdb 100644 --- a/content/ja/other/opentelemetry-collector/_index.md +++ b/content/ja/other/opentelemetry-collector/_index.md @@ -8,15 +8,15 @@ description: OpenTelemetry Collectorのコンセプトを学び、Splunk Observa ## 概要 -OpenTelemetry を使い始める場合は、バックエンドに直接データを送ることから始めるかもしれません。最初のステップとしてはよいですが、OpenTelemetry Collectorをオブザーバビリティのアーキテクチャとして使用するのは多くの利点があり、本番環境ではCollectorを使ったデプロイを推奨しています。 +OpenTelemetry を使い始める場合は、バックエンドに直接データを送ることから始めるかもしれません。最初のステップとしてはよいですが、OpenTelemetry Collector をオブザーバビリティのアーキテクチャとして使用するのは多くの利点があり、本番環境では Collector を使ったデプロイを推奨しています。 -このワークショップでは、OpenTelemetry Collectorを使用することに焦点を当て、Splunk Observability Cloud で使用するためのレシーバー、プロセッサー、エクスポーターを定義し、実際にテレメトリデータを送信するためのパイプラインを設定することで、環境に合わせてCollectorを活用を学びます。また、分散プラットフォームのビジネスニーズに対応するための、カスタムコンポーネントを追加できるようになるまでの道のりを進むことになります。 +このワークショップでは、OpenTelemetry Collector を使用することに焦点を当て、Splunk Observability Cloud で使用するためのレシーバー、プロセッサー、エクスポーターを定義し、実際にテレメトリデータを送信するためのパイプラインを設定することで、環境に合わせて Collector を活用を学びます。また、分散プラットフォームのビジネスニーズに対応するための、カスタムコンポーネントを追加できるようになるまでの道のりを進むことになります。 ### Ninja セクション -ワークショップの途中には、展開できる {{% badge style=primary icon=user-ninja %}}Ninja セクション{{% /badge %}} があります。これらはより実践的で、ワークショップ内または自分の時間でさらに技術的な詳細に取り組むことができます。 +ワークショップの途中には、展開できる {{% badge style=primary icon=user-ninja %}}Ninja セクション{{% /badge %}} があります。これらはより実践的で、ワークショップ中、もしくは自分の時間を使って、さらに技術的な詳細に取り組むことができます。 -OpenTelemetryプロジェクトは頻繁に開発されているため、Ninjaセクションの内容が古くなる可能性があることに注意してください。コンテンツが古い場合には更新のリクエストを出すこともできますので、必要なものを見つけた場合はお知らせください。 +OpenTelemetry プロジェクトは頻繁に開発されているため、Ninjaセクションの内容が古くなる可能性があることに注意してください。コンテンツが古い場合には更新のリクエストを出すこともできますので、必要なものを見つけた場合はお知らせください。 --- @@ -28,7 +28,7 @@ OpenTelemetryプロジェクトは頻繁に開発されているため、Ninja ## 対象者 -このワークショップは、OpenTelemetry Collectorのアーキテクチャとデプロイメントについてさらに学びたいと考えている開発者やシステム管理者を対象としています。 +このワークショップは、OpenTelemetry Collector のアーキテクチャとデプロイメントについてさらに学びたいと考えている開発者やシステム管理者を対象としています。 ## 前提条件 - データ収集に関する基本的な理解 @@ -40,12 +40,12 @@ OpenTelemetryプロジェクトは頻繁に開発されているため、Ninja このセッションの終わりまでに、参加者は以下を行うことができるようになります： -- OpenTelemetryのコンポーネントを理解する +- OpenTelemetry のコンポーネントを理解する - レシーバー、プロセッサー、エクスポーターを使用してデータを収集・分析する -- OpenTelemetryを使用する利点を特定する +- OpenTelemetry を使用する利点を特定する - 自分たちのビジネスニーズに対応するカスタムコンポーネントを構築する -## OpenTelemetryのアーキテクチャー +## OpenTelemetry のアーキテクチャー {{< mermaid >}} %%{ From ee85d1a39c3a25a79d50e0c8b5b6bf359f461f05 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 27 Nov 2023 13:03:33 +0900 Subject: [PATCH 04/12] receiver section --- .../3-receivers/1-hostmetrics.md | 8 +-- .../3-receivers/2-prometheus.md | 17 ++++--- .../3-receivers/3-other-receivers.md | 49 +++++++++---------- .../3-receivers/_index.md | 10 ++-- 4 files changed, 44 insertions(+), 40 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md b/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md index ab62add059..b76de000ee 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/1-hostmetrics.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Receivers +title: OpenTelemetry Collector レシーバー linkTitle: 1. Host Metrics weight: 1 --- -## Host Metrics Receiver +## Host Metrics レシーバー -[**The Host Metrics Receiver**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/receiver/hostmetricsreceiver/README.md) generates metrics about the host system scraped from various sources. This is intended to be used when the collector is deployed as an agent which is what we will be doing in this workshop. +[**Host Metrics レシーバー**](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/receiver/hostmetricsreceiver/README.md) は、さまざまなソースからスクレイピングされたホストシステムに関するメトリクスを生成します。これは、コレクターがエージェントとしてデプロイされるときに使用さます。 -Let's update the `/etc/otel-contrib/config.yaml` file and configure the **hostmetrics** receiver. Insert the following YAML under the **receivers** section, taking care to indent by two spaces. +`etc/otel-contrib/config.yaml` ファイルを更新して、**hostmetrics** レシーバーを設定してみましょう。以下の YAML を **receivers** セクションの下に挿入します。 ``` bash sudo vi /etc/otelcol-contrib/config.yaml diff --git a/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md index 5d86d934a5..bb258f54ba 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Receivers +title: OpenTelemetry Collector レシーバー linkTitle: 2. Prometheus weight: 2 --- -## Prometheus Receiver +## Prometheus レシーバー -You will also notice another receiver called **prometheus**. [Prometheus](https://prometheus.io/docs/introduction/overview/) is an open-source toolkit used by the OpenTelemetry Collector. This receiver is used to scrape metrics from the OpenTelemetry Collector itself. These metrics can then be used to monitor the health of the collector. +**prometheus** というレシーバーも、もちろんあります。[Prometheus](https://prometheus.io/docs/introduction/overview/) は OpenTelemetry Collector で使われているオープンソースのツールキットです。このレシーバーは、OpenTelemetry Collector 自身からメトリクスをスクレイピングするためにも使われます。これらのメトリクスは、コレクタの健全性をモニタリングするために使用できる。 -Let's modify the **prometheus** receiver to clearly show that it is for collecting metrics from the collector itself. By changing the name of the receiver from **prometheus** to **prometheus/internal**, it is now much clearer as to what that receiever is doing. Update the configuration file to look like this: +ここでは、**prometheus** レシーバーを変更して、コレクター自身からメトリクスを収集できるようにしてみます。レシーバーの名前を **prometheus** から **prometheus/internal** に変更して、レシーバーが何をしているのかをより明確しましょう。設定ファイルを以下のように更新します： {{% tab title="Prometheus Receiver Configuration" %}} @@ -24,12 +24,15 @@ prometheus/internal: {{% /tab %}} -## Example Dashboard - Prometheus metrics +## ダッシュボード例 - Prometheus メトリクス -The following screenshot shows an example dashboard of spme of the metrics the Prometheus internal receiver collects from the OpenTelemetry Collector. Here, we can see accepted and sent spans, metrics and log records. + + +このスクリーンショットは、 `prometheus/internal` レシーバーが OpenTelemetry Collector から収集したメトリクスの、spmeのダッシュボードの例です。ここではスパン・メトリクス・ログの、それぞれの受信および送信の様子を見ることができます。 {{% notice style="note" %}} -The following screenshot is an out-of-the-box (OOTB) dashboard from Splunk Observability Cloud that allows you to easily monitor your Splunk OpenTelemetry Collector install base. +このダッシュボードはSplunk Observability Cloud にある組み込みダッシュボードで、Splunk OpenTelemetry Collector のインストールの状況を簡単にモニタリングできます。 {{% /notice %}} + ![otel-charts](../../images/otel-charts.png) diff --git a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md index 38e0d61a53..5ac2fce110 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md @@ -1,40 +1,39 @@ --- -title: OpenTelemetry Collector Receivers -linkTitle: 3. Other Receivers +title: OpenTelemetry Collector レシーバー +linkTitle: 3. その他のレシーバー weight: 3 --- -## Other Receivers +## その他のレシーバー -You will notice in the default configuration there are other receivers: **otlp**, **opencensus**, **jaeger** and **zipkin**. These are used to receive telemetry data from other sources. We will not be covering these receivers in this workshop and they can be left as they are. +デフォルトの設定には、他のレシーバーがあることに気づくはずです。 **otlp**、**opencensus**、**jaeger**、**zipkin** が定義されています。これらは他のソースからテレメトリーデータを受信するために使われます。このワークショップでは、これらのレシーバーについては取り上げませんので、そのままにしておきましょう。 --- -{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Create receivers dynamically{{% /badge %}}" %}} +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** レシーバーを動的に生成する{{% /badge %}}" %}} -To help observe short lived tasks like docker containers, kubernetes pods, or ssh sessions, we can use the [receiver creator](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator) with [observer extensions](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/observer) to create a new receiver as these services start up. +dockerコンテナ、kubernetesポッド、sshセッションのような短時間のタスクを観測するために、[receiver creator](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator) レシーバーと [observer](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/extension/observer) エクステンションを使って、対象のサービスが起動するタイミングで新しいレシーバーを作成することができます。 -## What do we need? +## 何が必要なの？ -In order to start using the receiver creator and its associated observer extensions, they will need to be part of your collector build manifest. +receiver creator とそれに関連する observer エクステンションの使用を開始するには、collector build manifest に追加する必要があります。 -See [installation](../1-installation/) for the details. +詳細は [installation](../1-installation/) を参照してください。 -## Things to consider? +## 注意事項はある？ -Some short lived tasks may require additional configuration such as _username_, and _password_. -These values can be referenced via [environment variables](https://opentelemetry.io/docs/collector/configuration/#configuration-environment-variables), -or use a scheme expand syntax such as `${file:./path/to/database/password}`. -Please adhere to your organisation's secret practices when taking this route. +短命なタスクの中には、_username_ や _password_ のような追加設定を必要とするものがあります。それらの値は[環境変数](https://opentelemetry.io/docs/collector/configuration/#configuration-environment-variables) を参照したり、 `${file:./path/to/database/password}` のようなスキーム展開構文を使うこともできます。 -## The Ninja Zone +組織における機密情報の取り扱い規定に従って、どのような方法を取るかを検討してください。 -There are only two things needed for this ninja zone: +## Ninja ゾーン -1. Make sure you have added receiver creater and observer extensions to the builder manifest. -2. Create the config that can be used to match against discovered endpoints. +この Ninja ゾーンに必要なものは2つだけです: -To create the templated configurations, you can do the following: +1. ビbuilder manifestに、 receiver creator レシーバーと observer エクステンションが追加する +2. 検出されたエンドポイントを検出するように、設定を作成する + +次のようにすると、設定をテンプレート化できます: ```yaml receiver_creator: @@ -46,19 +45,19 @@ receiver_creator: password: ${env:HOST_REDIS_PASSWORD} ``` -For more examples, refer to these [receiver creator's examples](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator#examples). +他の例は [receiver creator's examples](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/receiver/receivercreator#examples) にあります。 {{% /expand %}} --- -## Configuration Check-in +## 設定の確認 -We've now covered receivers, so let's now check our configuration changes. +これで、レシーバーをカバーできました。ここで、設定のの変更内容をチェックしてみましょう。 --- -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}設定をレビューしてください{{% /badge %}}" %}} {{< tabs >}} {{% tab title="config.yaml" %}} @@ -148,8 +147,8 @@ service: --- -Now that we have reviewed how data gets into the OpenTelemetry Collector through receivers, let's now take a look at how the Collector processes the received data. +これで、レシーバーを通して OpenTelemetry Collector にデータがどのように取り込まれるかを確認しました。次に、コレクターが受信したデータをどのように処理するかを見てみましょう。 {{% notice style="warning" %}} -As the `/etc/otelcol-contrib/config.yaml` is not complete, please **do not** attempt to restart the collector at this point. +**ここではコレクターを再起動しないでください**！ `/etc/otelcol-contrib/config.yaml` の変更はまだ完了していません。 {{% /notice %}} diff --git a/content/ja/other/opentelemetry-collector/3-receivers/_index.md b/content/ja/other/opentelemetry-collector/3-receivers/_index.md index 622ead0253..cb72ee073f 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/_index.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/_index.md @@ -1,12 +1,14 @@ --- -title: OpenTelemetry Collector Receivers -linkTitle: 3. Receivers +title: OpenTelemetry Collector レシーバー +linkTitle: 3. レシーバー weight: 3 --- -Welcome to the receiver portion of the workshop! This is the starting point of the data pipeline of the OpenTelemetry Collector. Let's dive in. +レシーバーワークショップへようこそ！OpenTelemetry Collectorのデータパイプラインのスタート地点です。さあ、始めましょう。 -A receiver, which can be push or pull based, is how data gets into the Collector. Receivers may support one or more data sources. Generally, a receiver accepts data in a specified format, translates it into the internal format and passes it to processors and exporters defined in the applicable pipelines. +レシーバーはデータをCollectorに取り込む方法で、プッシュベースとプルベースのものがあります。レシーバーは1つ以上のデータソースをサポートします。一般的に、レシーバーは指定されたフォーマットでデータを受け入れ、内部フォーマットに変換し、該当するパイプラインで定義されたプロセッサやエクスポータにデータを渡します。 + +プッシュまたはプルベースのレシーバは、データをCollectorに取り込む方法です。レシーバは 1 つまたは複数のデータソースをサポートします。通常、レシーバは指定されたフォーマットでデータを受け入れ、内部フォーマットに変換し、該当するパイプラインで定義されたプロセッサーや エクスポーターにデータを渡します。 {{< mermaid >}} %%{ From 5cf5ca9f914bbbb046b6212856a69f97231cdf0f Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 27 Nov 2023 18:45:50 +0900 Subject: [PATCH 05/12] prosessor --- .../3-receivers/2-prometheus.md | 2 +- .../4-processors/1-batch-processor.md | 12 ++--- .../4-processors/2-resource-detection.md | 11 ++-- .../4-processors/3-attributes.md | 53 +++++++++---------- .../4-processors/_index.md | 7 +-- 5 files changed, 43 insertions(+), 42 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md index bb258f54ba..a9587ff23c 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/2-prometheus.md @@ -6,7 +6,7 @@ weight: 2 ## Prometheus レシーバー -**prometheus** というレシーバーも、もちろんあります。[Prometheus](https://prometheus.io/docs/introduction/overview/) は OpenTelemetry Collector で使われているオープンソースのツールキットです。このレシーバーは、OpenTelemetry Collector 自身からメトリクスをスクレイピングするためにも使われます。これらのメトリクスは、コレクタの健全性をモニタリングするために使用できる。 +**Prometheus** のレシーバーも、もちろんあります。[Prometheus](https://prometheus.io/docs/introduction/overview/) は OpenTelemetry Collector で使われているオープンソースのツールキットです。このレシーバーは、OpenTelemetry Collector 自身からメトリクスをスクレイピングするためにも使われます。これらのメトリクスは、コレクタの健全性をモニタリングするために使用できる。 ここでは、**prometheus** レシーバーを変更して、コレクター自身からメトリクスを収集できるようにしてみます。レシーバーの名前を **prometheus** から **prometheus/internal** に変更して、レシーバーが何をしているのかをより明確しましょう。設定ファイルを以下のように更新します： diff --git a/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md b/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md index 33584d31ad..e97f2d4cbf 100644 --- a/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md +++ b/content/ja/other/opentelemetry-collector/4-processors/1-batch-processor.md @@ -1,13 +1,13 @@ --- -title: OpenTelemetry Collector Processors +title: OpenTelemetry Collector プロセッサー linkTitle: 4.1 Batch weight: 1 --- -## Batch Processor +## Batch プロセッサー -By default, only the **batch** processor is enabled. This processor is used to batch up data before it is exported. This is useful for reducing the number of network calls made to exporters. For this workshop we will accept the defaults: +デフォルトでは、**batch** プロセッサーだけが有効になっています。このプロセッサーは、データをエクスポートする前にバッチ処理して、エクスポーターへのネットワーク・コールの回数を減らすために使われます。このワークショップではデフォルトの設定を使用します： -- `send_batch_size` (default = 8192): Number of spans, metric data points, or log records after which a batch will be sent regardless of the timeout. send_batch_size acts as a trigger and does not affect the size of the batch. If you need to enforce batch size limits sent to the next component in the pipeline see send_batch_max_size. -- `timeout` (default = 200ms): Time duration after which a batch will be sent regardless of size. If set to zero, send_batch_size is ignored as data will be sent immediately, subject to only send_batch_max_size. -- `send_batch_max_size` (default = 0): The upper limit of the batch size. 0 means no upper limit of the batch size. This property ensures that larger batches are split into smaller units. It must be greater than or equal to send_batch_size. +- `send_batch_size` (デフォルト = 8192): タイムアウトに関係なく、バッチを送信するスパン、メトリクスデータポイント、またはログレコードの数。パイプラインの次のコンポーネントに送信されるバッチサイズを制限する場合には、 `send_batch_max_size` を使います。 +- `timeout` (デフォルト = 200ms): サイズに関係なく、バッチが送信されるまでの時間。ゼロに設定すると、`send_batch_size` の設定を無視して `send_batch_max_size` だけが適用され、データは直ちに送信されます。 +- `send_batch_max_size` (デフォルト = 0): バッチサイズの上限。`0` を設定すると、バッチサイズの上限がないことして扱われます。この設定は、大きなバッチが小さなユニットに分割されることを保証します。`send_batch_size` 以上でなければななりません。 diff --git a/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md b/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md index 8663a69bb2..957c3c469f 100644 --- a/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md +++ b/content/ja/other/opentelemetry-collector/4-processors/2-resource-detection.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Processors +title: OpenTelemetry Collector プロセッサー linkTitle: 4.2 Resource Detection weight: 2 --- -## Resource Detection Processor +## Resource Detection プロセッサー -The **resourcedetection** processor can be used to detect resource information from the host and append or override the resource value in telemetry data with this information. +**resourcedetection** プロセッサーは、ホストからリソース情報を検出して、テレメトリーデータ内のリソース値をこの情報で追加または上書きすることができます。 -By default, the hostname is set to the FQDN if possible, otherwise the hostname provided by the OS is used as a fallback. This logic can be changed from using using the `hostname_sources` configuration option. To avoid getting the FQDN and use the hostname provided by the OS, we will set the `hostname_sources` to `os`. +デフォルトでは、可能であればホスト名を FQDN に設定し、そうでなければ OS が提供するホスト名になります。このロジックは `hostname_sources` オプションを使って変更できます。FQDN を取得せず、OSが提供するホスト名を使用するには、`hostname_sources`を`os`に設定します。 {{% tab title="System Resource Detection Processor Configuration" %}} @@ -24,6 +24,7 @@ processors: {{% /tab %}} If the workshop instance is running on an AWS/EC2 instance we can gather the following tags from the EC2 metadata API (this is not available on other platforms). +ワークショップのインスタンスが AWS/EC2 インスタンスで実行されている場合、EC2 のメタデータ API から以下のタグを収集します（これは他のプラットフォームでは利用できないものもあります）。 - `cloud.provider ("aws")` - `cloud.platform ("aws_ec2")` @@ -35,7 +36,7 @@ If the workshop instance is running on an AWS/EC2 instance we can gather the fol - `host.name` - `host.type` -We will create another processor to append these tags to our metrics. +これらのタグをメトリクスに追加するために、別のプロセッサーとして定義してみましょう。 {{% tab title="EC2 Resource Detection Processor Configuration" %}} diff --git a/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md index a7d8cb2ddb..8dd8847ee7 100644 --- a/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md +++ b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md @@ -1,31 +1,31 @@ --- -title: OpenTelemetry Collector Processors +title: OpenTelemetry Collector プロセッサー linkTitle: 4.3 Attributes weight: 3 --- -## Attributes Processor +## Attributes プロセッサー -The attributes processor modifies attributes of a span, log, or metric. This processor also supports the ability to filter and match input data to determine if they should be included or excluded for specified actions. +attribute プロセッサーを使うと、スパン、ログ、またはメトリクスの属性を変更できます。また、このプロセッサーは、入力データをフィルタリングし、マッチさせ、指定されたアクションに含めるべきか、除外すべきかを決定する機能もサポートしています。 -It takes a list of actions which are performed in order specified in the config. The supported actions are: +アクションを設定するには、指定された順序で実行されるアクションのリストを記述します。サポートされるアクションは以下の通りです： -- `insert`: Inserts a new attribute in input data where the key does not already exist. -- `update`: Updates an attribute in input data where the key does exist. -- `upsert`: Performs insert or update. Inserts a new attribute in input data where the key does not already exist and updates an attribute in input data where the key does exist. -- `delete`: Deletes an attribute from the input data. -- `hash`: Hashes (SHA1) an existing attribute value. -- `extract`: Extracts values using a regular expression rule from the input key to target keys specified in the rule. If a target key already exists, it will be overridden. +- `insert`: その属性がない場合に、新しい属性値を挿入します。 +- `update`: その属性がある場合に、その属性値を更新します。 +- `upsert`: insert または update を実行します。属性がない場合には新しい属性値を挿入し、属性がある場合にはその値を更新します。 +- `delete`: 入力データから属性値を削除します。 +- `hash`: 属性値をハッシュ化 (SHA1) します。 +- `extract`: 入力キーの値を正規表現ルールを使って抽出し、対象キーの値を更新します。対象キーがすでに存在する場合は、その値は上書きされます。 -We are going to create an attributes processor to `insert` a new attribute to all our host metrics called `participant.name` with a value of your own name e.g. `marge_simpson`. +次の例のように、attribute プロセッサーを使って、キーは `participant.name`、あたいはあなたの名前（例: `marge_simpson`）という新しい属性を追加してみましょう。 {{% notice style="warning" %}} -Ensure you replace `INSERT_YOUR_NAME_HERE` with your own name and also ensure you **do not** use spaces in your name. +`INSERT_YOUR_NAME_HERE` の箇所は、自分の名前に置き換えてください。また、自分の名前に **スペースを使わない** ようにしてください。 {{% /notice %}} -Later on in the workshop we will use this attribute to filter our metrics in Splunk Observability Cloud. +このワークショップの後半では、この属性を使用して Splunk Observability Cloud でメトリクスをフィルタリングします。 {{% tab title="Attributes Processor Configuration" %}} @@ -49,26 +49,25 @@ processors: --- -{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Using connectors to gain internal insights{{% /badge %}}" %}} +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** コネクターを使って内部への洞察を加速する{{% /badge %}}" %}} -One of the most recent additions to the collector was the notion of a [connector](https://opentelemetry.io/docs/collector/configuration/#connectors), which allows you to join output of one pipeline to input of another pipeline. +最近追加されたものの一つとして、[connector](https://opentelemetry.io/docs/collector/configuration/#connectors) というコンセプトがあります。これを使うと、あるパイプラインの出力を別のパイプラインの入力に結合できるようになります。 -An example of how this is beneficial is that some services emit metrics based on the amount of datapoints being exported, number of logs containing an error status, -or the amount of data being sent from one deployment environment. The count connector helps address this for you out of the box. +利用シーンとして、送信するデータポイントの量、エラーステータスを含むログの数をメトリクスをとして出力するサービスがあります。他には、あるデプロイ環境から送信されるデータ量のメトリクスを生成するサービスがあります。このような場合に、count コネクターですぐに対応できます。 -## Why a connector instead of a processor? +## プロセッサーではなくコネクターなのはなぜ？ -A processor is limited in what additional data it can produce considering it has to pass on the data it has processed making it hard to expose additional information. Connectors do not have to emit the data they received which means they provide an opportunity to create those insights we are after. +プロセッサーは、処理したデータを次に渡すものであり、追加の情報を出力することはできません。コネクターはレシーバーで受け取ったデータを出力せずに、私たちが求める洞察を作り出す機会を提供します。 -For example, a connector could be made to count the number of logs, metrics, and traces that do not have the deployment environment attribute. +たとえば、count コネクターを使うと、環境変数 `deployment` を持たないログ、メトリクス、トレースの数をカウントすることができます。 -A very simple example with the output of being able to break down data usage by deployment environment. +また、非常にシンプルな例として、`deployment` 別にデータ使用量を分解して出力することもできます。 -## Considerations with connectors +## コネクターの注意事項 -A connector only accepts data exported from one pipeline and receiver by another pipeline, this means you may have to consider how you construct your collector config to take advantage of it. +コネクターは、あるパイプラインからエクスポートされ、別のパイプラインでレシーバーで定義されたデータのみを受け入れます。コレクターをどう構築してどう利用するか、設定を検討する必要があります。 -## References +## 参照 1. [https://opentelemetry.io/docs/collector/configuration/#connectors](https://opentelemetry.io/docs/collector/configuration/#connectors) 2. [https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/connector/countconnector](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/connector/countconnector) @@ -77,13 +76,13 @@ A connector only accepts data exported from one pipeline and receiver by another --- -## Configuration Check-in +## 設定の確認 -That's processors covered, let's check our configuration changes. +これで、プロセッサーがカバーできました。ここで、設定のの変更内容をチェックしてみましょう。 --- -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}設定をレビューしてください{{% /badge %}}" %}} {{< tabs >}} {{% tab title="config.yaml" %}} diff --git a/content/ja/other/opentelemetry-collector/4-processors/_index.md b/content/ja/other/opentelemetry-collector/4-processors/_index.md index 087dfba62a..7181caeca0 100644 --- a/content/ja/other/opentelemetry-collector/4-processors/_index.md +++ b/content/ja/other/opentelemetry-collector/4-processors/_index.md @@ -1,10 +1,11 @@ --- -title: OpenTelemetry Collector Processors -linkTitle: 4. Processors +title: OpenTelemetry Collector プロセッサー +linkTitle: 4. プロセッサー weight: 4 --- -[**Processors**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/processor/README.md) are run on data between being received and being exported. Processors are optional though some are recommended. There are [a large number of processors](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor) included in the OpenTelemetry contrib Collector. + +[**プロセッサー**](https://github.com/open-telemetry/opentelemetry-collector/blob/main/processor/README.md)は、レシーバーとエクスポーターとの間で、データに対して実行される処理です。プロセッサーはオプションですが、いくつかは推奨されています。OpenTelemetry Collector Contrib には[多数のプロセッサー](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor)が含まれています。 {{< mermaid >}} %%{ From dfbe2b5d1345fd99f86712dce7089c412138e8d0 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 27 Nov 2023 19:09:20 +0900 Subject: [PATCH 06/12] exporter --- .../2-extensions/3-zpages.md | 2 +- .../3-receivers/3-other-receivers.md | 2 +- .../5-exporters/_index.md | 9 ++--- .../5-exporters/otlphttp.md | 35 ++++++++++--------- 4 files changed, 25 insertions(+), 23 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md index 55aa32479c..37a801d134 100644 --- a/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md +++ b/content/ja/other/opentelemetry-collector/2-extensions/3-zpages.md @@ -276,7 +276,7 @@ service: --- -## Check-in: エクステンションの設定 +## 設定を確認しましょう さて、エクステンションについて説明したので、設定の変更箇所を確認していきましょう。 diff --git a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md index 5ac2fce110..d272547046 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md @@ -51,7 +51,7 @@ receiver_creator: --- -## 設定の確認 +## 設定を確認しましょう これで、レシーバーをカバーできました。ここで、設定のの変更内容をチェックしてみましょう。 diff --git a/content/ja/other/opentelemetry-collector/5-exporters/_index.md b/content/ja/other/opentelemetry-collector/5-exporters/_index.md index f1dddb55ed..c3a3bfd5e6 100644 --- a/content/ja/other/opentelemetry-collector/5-exporters/_index.md +++ b/content/ja/other/opentelemetry-collector/5-exporters/_index.md @@ -1,12 +1,13 @@ --- -title: OpenTelemetry Collector Exporters -linkTitle: 5. Exporters +title: OpenTelemetry Collector エクスポーター +linkTitle: 5. エクスポーター weight: 5 --- -An exporter, which can be push or pull based, is how you send data to one or more backends/destinations. Exporters may support one or more data sources. +エクスポーターは、プッシュまたはプルベースであり、一つ以上のバックエンド/デスティネーションにデータを送信する方法です。エクスポーターは、一つまたは複数のデータソースをサポートすることがあります。 + +このワークショップでは、[**otlphttp**](https://opentelemetry.io/docs/specs/otel/protocol/exporter/) エクスポーターを使用します。OpenTelemetry Protocol (OTLP) は、テレメトリーデータを伝送するためのベンダーニュートラルで標準化されたプロトコルです。OTLP エクスポーターは、OTLP プロトコルを実装するサーバーにデータを送信します。OTLP エクスポーターは、[**gRPC**](https://grpc.io/) および [**HTTP**](https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview)/[**JSON**](https://www.json.org/json-en.html) プロトコルの両方をサポートします。 -For this workshop, we will be using the [**otlphttp**](https://opentelemetry.io/docs/specs/otel/protocol/exporter/) exporter. The OpenTelemetry Protocol (OTLP) is a vendor-neutral, standardised protocol for transmitting telemetry data. The OTLP exporter sends data to a server that implements the OTLP protocol. The OTLP exporter supports both [**gRPC**](https://grpc.io/) and [**HTTP**](https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview)/[**JSON**](https://www.json.org/json-en.html) protocols. {{< mermaid >}} %%{ diff --git a/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md b/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md index cd497f5451..ad503c015d 100644 --- a/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md +++ b/content/ja/other/opentelemetry-collector/5-exporters/otlphttp.md @@ -1,16 +1,16 @@ --- -title: OpenTelemetry Collector Exporters +title: OpenTelemetry Collector エクスポーター linkTitle: 5.1 OTLP HTTP weight: 1 --- -## OTLP HTTP Exporter +## OTLP HTTP エクスポーター -In order to send metrics over HTTP to Splunk Observability Cloud, we will need to configure the **otlphttp** exporter. +Splunk Observability Cloud へ HTTP 経由でメトリックスを送信するためには、**otlphttp** エクスポーターを設定する必要があります。 -Let's edit our `/etc/otelcol-contrib/config.yaml` file and configure the **otlphttp** exporter. Insert the following YAML under the **exporters** section, taking care to indent by two spaces e.g. +`/etc/otelcol-contrib/config.yaml` ファイルを編集し、**otlphttp** エクスポーターを設定しましょう。以下の YAML を **exporters** セクションの下に挿入し、例えば2スペースでインデントしてください。 -We will also change the verbosity of the logging exporter to prevent the disk filling up. The default of `detailed` is very noisy. +また、ディスクの容量不足を防ぐために、ロギングエクスポーターの詳細度を変更します。デフォルトの `detailed` は非常に詳細です。 ```yaml {hl_lines="3-4"} exporters: @@ -19,10 +19,10 @@ exporters: otlphttp/splunk: ``` -Next we need to define the `metrics_endpoint` and configure the target URL. +次に、`metrics_endpoint` を定義して、ターゲットURLを設定していきます。 {{% notice style="note" %}} -If you are an attendee to a Splunk hosted workshop, the instance your are using has already been configured with a Realm environment variable. We will reference that environment variable in our configuration file. Otherwise, you will need to create a new environment variable and set the Realm e.g. +Splunk 主催のワークショップの参加者である場合、使用しているインスタンスにはすでに Realm 環境変数が設定されています。その環境変数を設定ファイルで参照します。それ以外の場合は、新しい環境変数を作成して Realm を設定する必要があります。例えば： ``` bash export REALM="us1" @@ -30,9 +30,9 @@ export REALM="us1" {{% /notice %}} -The URL to use is `https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp`. (Splunk has Realms in key geographical locations around the world for data residency). +使用するURLは `https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp` です。（Splunkは、データの居住地に応じて世界中の主要地域に Realm を持っています）。 -The **otlphttp** exporter can also be configured to send traces and logs by defining a target URL for `traces_endpoint` and `logs_endpoint` respectively. Configuring these is outside the scope of this workshop. +**otlphttp** エクスポーターは、`traces_endpoint` と `logs_endpoint` それぞれのターゲットURLを定義することにより、トレースとログを送信するようにも設定できますが、そのような設定はこのワークショップの範囲外とします。 ```yaml {hl_lines="5"} exporters: @@ -42,12 +42,12 @@ exporters: metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp ``` -By default, `gzip` compression is enabled for all endpoints. This can be disabled by setting `compression: none` in the exporter configuration. We will leave compression enabled for this workshop and accept the default as this is the most efficient way to send data. +デフォルトでは、すべてのエンドポイントで `gzip` 圧縮が有効になっています。エクスポーターの設定で `compression: none` を設定することにより、圧縮を無効にすることができます。このワークショップでは圧縮を有効にしたままにし、データを送信する最も効率的な方法としてデフォルト設定を使っていきます。 -In order to send metrics to Splunk Observability Cloud, we need to use an Access Token. This can be done by creating a new token in the Splunk Observability Cloud UI. For more information on how to create a token, see [Create a token](https://docs.splunk.com/Observability/admin/authentication-tokens/org-tokens.html). The token needs to be of type **INGEST**. +Splunk Observability Cloud にメトリクスを送信するためには、アクセストークンを使用する必要があります。これは、Splunk Observability Cloud UI で新しいトークンを作成することにより行うことができます。トークンの作成方法についての詳細は、[Create a token](https://docs.splunk.com/Observability/admin/authentication-tokens/org-tokens.html) を参照してください。トークンは **INGEST** タイプである必要があります。 {{% notice style="note" %}} -If you are an attendee to a Splunk hosted workshop, the instance your are using has already been configured with an Access Token (which has been set as an environment variable). We will reference that environment variable in our configuration file. Otherwise, you will need to create a new token and set it as an environment variable e.g. +Splunk　主催のワークショップの参加者である場合、使用しているインスタンスにはすでにアクセストークンが設定されています（環境変数として設定されています）ので、その環境変数を設定ファイルで参照します。それ以外の場合は、新しいトークンを作成し、それを環境変数として設定する必要があります。例えば： ``` bash export ACCESS_TOKEN= @@ -55,7 +55,7 @@ export ACCESS_TOKEN= {{% /notice %}} -The token is defined in the configuration file by inserting `X-SF-TOKEN: ${env:ACCESS_TOKEN}` under a `headers:` section: +トークンは、設定ファイル内で `headers:` セクションの下に `X-SF-TOKEN: ${env:ACCESS_TOKEN}` を挿入することにで定義します： ```yaml {hl_lines="6-8"} exporters: @@ -67,13 +67,14 @@ exporters: X-SF-TOKEN: ${env:ACCESS_TOKEN} ``` -## Configuration Check-in +## 設定を確認しましょう +これで、エクスポーターもカバーできました。設定を確認していきましょう： Now that we've covered exporters, let's check our configuration changes: --- -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your configuration{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}設定をレビューしてください{{% /badge %}}" %}} {{< tabs >}} {{% tab title="config.yaml" %}} @@ -178,6 +179,6 @@ service: --- -Of course, you can easily configure the `metrics_endpoint` to point to any other solution that supports the **OTLP** protocol. +もちろん、**OTLP** プロトコルをサポートする他のソリューションを指すように `metrics_endpoint` を簡単に設定することができます。 -Next, we need to enable the receivers, processors and exporters we have just configured in the service section of the `config.yaml`. +次に、`config.yaml` のサービスセクションで、今設定したレシーバー、プロセッサー、エクスポーターを有効にしていきます。 From 92a09347bb7fefcec8d0e41abef5de61b57647a8 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 27 Nov 2023 19:48:03 +0900 Subject: [PATCH 07/12] services --- .../6-service/1-hostmetrics.md | 8 ++--- .../6-service/2-prometheus.md | 8 ++--- .../6-service/3-resourcedetection.md | 8 ++--- .../6-service/4-attributes.md | 8 ++--- .../6-service/5-otlphttp.md | 36 +++++++++---------- .../6-service/_index.md | 21 +++++------ 6 files changed, 44 insertions(+), 45 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md b/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md index 70d028dac6..4a78edd39f 100644 --- a/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md +++ b/content/ja/other/opentelemetry-collector/6-service/1-hostmetrics.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Service +title: OpenTelemetry Collector サービス linkTitle: 6.1 Host Metrics weight: 1 --- -## Hostmetrics Receiver +## Hostmetrics レシーバー -If you recall from the Receivers portion of the workshop, we defined the [Host Metrics Receiver](../3-receivers/#host-metrics-receiver) to generate metrics about the host system, which are scraped from various sources. To enable the receiver, we must include the `hostmetrics` receiver in the metrics pipeline. +ワークショップのレシーバー部分で振り返ると、ホストシステムに関するメトリクスを生成するために、様々なソースからスクレイピングする [Host Metrics](../3-receivers/#host-metrics-receiver) レシーバーを定義しました。このレシーバーを有効にするためには、メトリクスパイプラインに `hostmetrics` レシーバーを含める必要があります。 -In the `metrics` pipeline, add `hostmetrics` to the metrics `receivers` section. +`metrics` パイプラインで、メトリクスの `receivers` セクションに `hostmetrics` を追加します。 ```yaml {hl_lines="11"} service: diff --git a/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md b/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md index 761c95b795..1df6d9797e 100644 --- a/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md +++ b/content/ja/other/opentelemetry-collector/6-service/2-prometheus.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Service +title: OpenTelemetry Collector サービス linkTitle: 6.2 Prometheus weight: 2 --- -## Prometheus Internal Receiver +## Prometheus Internal レシーバー -Earlier in the workshop, we also renamed the `prometheus` receiver to reflect that is was collecting metrics internal to the collector, renaming it to `prometheus/internal`. +ワークショップの前半で、`prometheus` レシーバーの名前を変更し、コレクター内部のメトリクスを収集していることを反映して、`prometheus/internal` という名前にしました。 - We now need to enable the `prometheus/internal` receiver under the metrics pipeline. Update the `receivers` section to include `prometheus/internal` under the `metrics` pipeline: +現在、メトリクスパイプラインの下で `prometheus/internal` レシーバーを有効にする必要があります。`metrics` パイプラインの下の `receivers` セクションを更新して、`prometheus/internal` を含めます： ```yaml {hl_lines="11"} service: diff --git a/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md b/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md index 8d4b1fe367..570c89d9e8 100644 --- a/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md +++ b/content/ja/other/opentelemetry-collector/6-service/3-resourcedetection.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Service +title: OpenTelemetry Collector サービス linkTitle: 6.3 Resource Detection weight: 3 --- -## Resource Detection Processor +## Resource Detection プロセッサー -We also added `resourcedetection/system` and `resourcedetection/ec2` processors so that the collector can capture the instance hostname and AWS/EC2 metadata. We now need to enable these two processors under the metrics pipeline. +また、コレクターがインスタンスのホスト名やAWS/EC2のメタデータを取得できるように、`resourcedetection/system` および `resourcedetection/ec2` プロセッサーを追加しました。これらのプロセッサーをメトリクスパイプライン下で有効にする必要があります。 -Update the `processors` section to include `resourcedetection/system` and `resourcedetection/ec2` under the `metrics` pipeline: +`metrics` パイプラインの下の `processors` セクションを更新して、`resourcedetection/system` および `resourcedetection/ec2` を追加します： ```yaml {hl_lines="12"} service: diff --git a/content/ja/other/opentelemetry-collector/6-service/4-attributes.md b/content/ja/other/opentelemetry-collector/6-service/4-attributes.md index 661a403dd6..fa98b130a8 100644 --- a/content/ja/other/opentelemetry-collector/6-service/4-attributes.md +++ b/content/ja/other/opentelemetry-collector/6-service/4-attributes.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Service +title: OpenTelemetry Collector サービス linkTitle: 6.4 Attributes weight: 4 --- -## Attributes Processor +## Attributes プロセッサー -Also in the Processors section of this workshop, we added the `attributes/conf` processor so that the collector will inset a new attribute called `participant.name` to all the metrics. We now need to enable this under the metrics pipeline. +また、このワークショップのプロセッサーセクションでは、`attributes/conf` プロセッサーを追加し、コレクターがすべてのメトリクスに `participant.name` という新しい属性を挿入するようにしました。これをメトリクスパイプライン下で有効にする必要があります。 -Update the `processors` section to include `attributes/conf` under the `metrics` pipeline: +`metrics` パイプラインの下の `processors` セクションを更新して、`attributes/conf` を追加します： ```yaml {hl_lines="12"} service: diff --git a/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md b/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md index 6095fbb0a2..a83614b9d1 100644 --- a/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md +++ b/content/ja/other/opentelemetry-collector/6-service/5-otlphttp.md @@ -1,14 +1,14 @@ --- -title: OpenTelemetry Collector Service +title: OpenTelemetry Collector サービス linkTitle: 6.5 OTLP HTTP weight: 5 --- -## OTLP HTTP Exporter +## OTLP HTTP エクスポーター -In the Exporters section of the workshop, we configured the `otlphttp` exporter to send metrics to Splunk Observability Cloud. We now need to enable this under the metrics pipeline. +ワークショップのエクスポーターセクションでは、`otlphttp` エクスポーターを設定して、メトリクスを Splunk Observability Cloud に送信するようにしました。これをメトリクスパイプライン下で有効にする必要があります。 -Update the `exporters` section to include `otlphttp/splunk` under the `metrics` pipeline: +`metrics` パイプラインの下の `exporters` セクションを更新して、`otlphttp/splunk` を追加します： ```yaml {hl_lines="13"} service: @@ -28,23 +28,21 @@ service: --- -{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Observing the collector internals{{% /badge %}}" %}} +{{% expand title="{{% badge style=primary icon=user-ninja %}}**Ninja:** コレクターの内部を観測する{{% /badge %}}" %}} -The collector captures internal signals about its behavior this also include additional signals from running components. -The reason for this is that components that make decisions about the flow of data need a way to surface that information -as metrics or traces. +コレクターは、その動作に関する内部シグナルを捕捉しています。これには実行中のコンポーネントからの追加されるシグナルも含まれます。これは、データの流れに関する決定を行うコンポーネントが、その情報をメトリクスやトレースとして表面化する方法を必要とするためです。 -## Why monitor the collector? +## なぜコレクターを監視するの？ -This is somewhat of a chicken and egg problem of, "Who is watching the the watcher?", but it is important that we can surface this information. Another interesting part of the collector's history is that it existed before the Go metrics' SDK was considered stable so the collector exposes a prometheus endpoint to provide this functionality for the time being. +これは「監視者を監視するのは誰か？」という種類の問題ですが、このような情報を表面化できることは重要です。コレクターの歴史の興味深い部分は、GoメトリクスのSDKが安定と考えられる前に存在していたことで、コレクターは当面の間、この機能を提供するために Prometheus エンドポイントを公開しています。 -## Considerations +## 注意点 -Monitoring the internal usage of each running collector in your organisation can contribute a significant amount of new Metric Time Series (MTS). The Splunk distribution has curated these metrics for you and would be able to to help forcast the expected increases. +組織内で稼働している各コレクターの内部使用状況を監視することは、新しいメトリクス量（MTS）を大幅な増加させる可能性があります。Splunkディストリビューションはこれらのメトリクスをキュレーションしており、増加を予測するのに役立ちます。 -## The Ninja Zone +## Ninja ゾーン -To expose the internal observability of the collector, there are some additional settings that can be adjusted: +コレクターの内部オブザーバビリティを公開するためには、いくつかの設定を追加することがあります： {{< tabs >}} {{% tab title="telemetry schema" %}} @@ -87,7 +85,7 @@ service: {{% /tab %}} {{< /tabs >}} -## References +## 参照 1. [https://opentelemetry.io/docs/collector/configuration/#service](https://opentelemetry.io/docs/collector/configuration/#service) @@ -95,11 +93,11 @@ service: --- -## Final configuration +## 完成した設定 --- -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your final configuration{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}完成した設定をレビューしてください{{% /badge %}}" %}} {{< tabs >}} {{% tab title="config.yaml" %}} @@ -206,7 +204,7 @@ service: --- {{% notice style="tip" %}} -It is recommended that you validate your configuration file before restarting the collector. You can do this by using the built-in `validate` command: +コレクターを再起動する前に、設定ファイルを検証することをお勧めします。これは、組み込みの `validate` コマンドを使用して行うことができます： {{< tabs >}} {{% tab title="Command" %}} @@ -235,7 +233,7 @@ Error: failed to get config: cannot unmarshal the configuration: 1 error(s) deco {{< /tabs >}} {{% /notice %}} -Now that we have a working configuration, let's start the collector and then check to see what [zPages](../2-extensions/#zpages) is reporting. +動作する設定ができたので、コレクターを起動し、その後 [zPages](../2-extensions/#zpages) が報告している内容を確認しましょう。 {{% tab title="Command" %}} diff --git a/content/ja/other/opentelemetry-collector/6-service/_index.md b/content/ja/other/opentelemetry-collector/6-service/_index.md index 0ac2319593..2a3b394f41 100644 --- a/content/ja/other/opentelemetry-collector/6-service/_index.md +++ b/content/ja/other/opentelemetry-collector/6-service/_index.md @@ -1,26 +1,27 @@ --- -title: OpenTelemetry Collector Service -linkTitle: 6. Service +title: OpenTelemetry Collector サービス +linkTitle: 6. サービス weight: 6 --- -The **Service** section is used to configure what components are enabled in the Collector based on the configuration found in the receivers, processors, exporters, and extensions sections. +**Service** セクションでは、レシーバー、プロセッサー、エクスポーター、およびエクステンションにある設定に基づいて、コレクターで有効にするコンポーネントを設定していきます。 + {{% notice style="info" %}} -If a component is configured, but not defined within the **Service** section then it is **not** enabled. +コンポーネントが設定されていても、**Service** セクション内で定義されていない場合、そのコンポーネントは**有効化されません**。 {{% /notice %}} -The service section consists of three sub-sections: +サービスのセクションは、以下の3つのサブセクションで構成されています： -- extensions -- pipelines -- telemetry +- extensions（拡張機能） +- pipelines（パイプライン） +- telemetry（テレメトリー） -In the default configuration, the extension section has been configured to enable `health_check`, `pprof` and `zpages`, which we configured in the Extensions module earlier. +デフォルトの設定では、拡張機能セクションが `health_check`、`pprof`、`zpages` を有効にするように設定されており、これらは以前のエクステンションのモジュールで設定しました。 ``` yaml service: extensions: [health_check, pprof, zpages] ``` -So lets configure our Metric Pipeline! +それでは、メトリックパイプラインを設定していきましょう！ From 3153c6ce93e335853480a2b1ff5db0206556b6c7 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Mon, 27 Nov 2023 19:48:10 +0900 Subject: [PATCH 08/12] visualization --- .../7-visualisation/index.md | 24 +++++++++---------- 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/7-visualisation/index.md b/content/ja/other/opentelemetry-collector/7-visualisation/index.md index 58223c5680..01f8da2fe2 100644 --- a/content/ja/other/opentelemetry-collector/7-visualisation/index.md +++ b/content/ja/other/opentelemetry-collector/7-visualisation/index.md @@ -1,44 +1,44 @@ --- -title: Data Visualisations -linkTitle: 7. Visualisation +title: データの可視化 +linkTitle: 7. 可視化 weight: 7 --- ## Splunk Observability Cloud -Now that we have configured the OpenTelemetry Collector to send metrics to Splunk Observability Cloud, let's take a look at the data in Splunk Observability Cloud. If you have not received an invite to Splunk Observability Cloud, your instructor will provide you with login credentials. +OpenTelemetry Collector を設定して Splunk Observability Cloud にメトリクスを送信するようにしたので、Splunk Observability Cloud でデータを見てみましょう。Splunk Observability Cloud　への招待を受け取っていない場合は、講師がログイン資格情報を提供します。 -Before that, lets make things a little more interesting and run a stress test on the instance. This in turn will light up the dashboards. +その前に、もう少し興味深くするために、インスタンスでストレステストを実行しましょう。これにより、ダッシュボードが活性化されます。 ``` bash sudo apt install stress while true; do stress -c 2 -t 40; stress -d 5 -t 40; stress -m 20 -t 40; done ``` -Once you are logged into Splunk Observability Cloud, using the left-hand navigation, navigate to **Dashboards**: +Splunk Observability Cloudにログインしたら、左側のナビゲーションを使用して **Dashboards** に移動します： ![menu-dashboards](../images/menu-dashboards.png) -In the search box, search for **OTel Contrib**: +検索ボックスで **OTel Contrib** を検索します： ![search-dashboards](../images/search-dashboards.png) {{% notice style="info" %}} -If the dashboard does not exist, then your instructor will be able to quickly add it. If you are not attending a Splunk hosted version of this workshop then the Dashboard Group to import can be found at the bottom of this page. +ダッシュボードが存在しない場合は、講師が迅速に追加します。このワークショップの Splunk 主催版に参加していない場合、インポートするダッシュボードグループはこのページの下部にあります。 {{% /notice %}} -Click on the **OTel Contrib Dashboard** dashboard to open it: +**OTel Contrib Dashboard** ダッシュボードをクリックして開きます： ![otel-dashboard](../images/otel-dashboard.png) -In the **Filter** box, at the top of the dashboard, type in **participant** and select **participant.name**: +ダッシュボードの上部にある **Filter** 欄に「participant」の途中まで入力し、候補に出る **participant.name** を選択します： ![search-filter](../images/search-filter.png) -You can either start typing in your name you configured for `participant.name` in the `config.yaml` or you can select your name from the list: +`participant.name` で、`config.yaml` 内で設定したあなたの名前を入力するか、リストから選択することができます： ![select-conf-attendee-name](../images/select-participant-name.png) -You can now see the host metrics for the host upon which you configured the OpenTelemetry Collector. +これで、OpenTelemetry Collector を設定したホストの、ホストメトリクスを確認することができます。 -{{% attachments sort="asc" style="info" title="Download Dashboard JSON for importing" /%}} +{{% attachments sort="asc" style="info" title="ダッシュボードJSONのダウンロード方法" /%}} From 6da16483544882cbdfda8b82b635d85e3d713f00 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Fri, 1 Dec 2023 12:20:57 +0900 Subject: [PATCH 09/12] Develop --- .../4-processors/3-attributes.md | 2 +- .../8-develop/1-project-setup.md | 29 ++++--- .../8-develop/2-configuration.md | 71 ++++++++-------- .../8-develop/3-component.md | 80 +++++++++---------- .../8-develop/4-design.md | 21 +++-- .../8-develop/5-business-logic.md | 74 +++++++---------- .../8-develop/_index.md | 48 +++++------ 7 files changed, 149 insertions(+), 176 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md index 8dd8847ee7..69621aefd2 100644 --- a/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md +++ b/content/ja/other/opentelemetry-collector/4-processors/3-attributes.md @@ -76,7 +76,7 @@ processors: --- -## 設定の確認 +## 設定を確認しましょう これで、プロセッサーがカバーできました。ここで、設定のの変更内容をチェックしてみましょう。 diff --git a/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md b/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md index d8d0263b9c..323a75b3fc 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md +++ b/content/ja/other/opentelemetry-collector/8-develop/1-project-setup.md @@ -1,32 +1,31 @@ --- -title: OpenTelemetry Collector Development -linkTitle: 8.1 Project Setup +title: OpenTelemetry Collector を開発する +linkTitle: 8.1 セットアップ weight: 9 --- -## Project Setup {{% badge style=primary icon=user-ninja %}}**Ninja**{{% /badge %}} +## プロジェクトのセットアップ {{% badge style=primary icon=user-ninja %}}**Ninja**{{% /badge %}} {{% notice style="note" %}} -The time to finish this section of the workshop can vary depending on experience. +このワークショップのセクションを完了する時間は経験によって異なる場合があります。 -A complete solution can be found [here](https://github.com/splunk/collector-workshop-example) incase you're stuck or want to follow -along with the instructor. +完成したものは[こちら](https://github.com/splunk/collector-workshop-example)にあります。詰まった場合や講師と一緒に進めたい場合に利用してください。 {{% /notice %}} -To get started developing a the new _Jenkins CI_ receiver, we first need to set up a Golang project. -The steps to create your new Golang project is: +新しい _Jenkins CI_ レシーバーの開発を始めるため、まずは Go プロジェクトのセットアップから始めていきます。 +新しい Go プロジェクトを作成する手順は以下の通りです： -1. Create a new directoy named `${HOME}/go/src/jenkinscireceiver` and change into it - 1. The actual directory name or location is not strict, you can choose your own development directory to make it in. -1. Initialise the golang module by going `go mod init splunk.conf/workshop/example/jenkinscireceiver` - 1. This will create a file named `go.mod` which is used to track our direct and indirect dependencies - 1. Eventually there will be a `go.sum` which is the checksum values of the depedancies being imported. +1. `${HOME}/go/src/jenkinscireceiver` という名前の新しいディレクトリを作成し、そのディレクトリに移動します。 + 1. 実際のディレクトリ名や場所は厳密ではありません。自分の開発ディレクトリを自由に選ぶことができます。 +1. `go mod init splunk.conf/workshop/example/jenkinscireceiver` を実行して、Go のモジュールを初期化します。 + 1. 依存関係を追跡するために使用される `go.mod` というファイルが作成されます。 + 1. インポートされている依存関係のチェックサム値が `go.sum` として保存されます。 -{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}Review your go.mod{{% /badge %}}" %}} +{{% expand title="{{% badge icon=check color=green title=**Check-in** %}}go.modをレビューする{{% /badge %}}" %}} -``` text +`` text module splunk.conf/workshop/example/jenkinscireceiver go 1.20 diff --git a/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md b/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md index a6093af4fa..d8859c4260 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md +++ b/content/ja/other/opentelemetry-collector/8-develop/2-configuration.md @@ -1,40 +1,20 @@ --- -title: OpenTelemetry Collector Development +title: OpenTelemetry Collector を開発する linkTitle: 8.2 Configuration weight: 10 --- -## Building The Configuration +## Configuration の構築 -The configuration portion of the component is how the user is able to have their inputs over the component, -so the values that is used for the configuration need to be: +コンポーネントの Configuration 部分は、ユーザーがコンポーネントに対する入力を行う方法であり、設定に使用される値は以下のようである必要があります： -1. Intuitive for users to understand what that field controls -1. Be explicit in what is required and what is optional -1. Reuse common names and fields -1. Keep the options simple +1. そのフィールドが何を制御するのか、ユーザーが直感的に理解できる +1. 必須項目とオプション項目が明確である +1. 共通の名前とフィールドを再利用する +1. オプションをシンプルに保つ {{% tabs %}} -{{% tab title="bad config" %}} - -```yaml ---- -jenkins_server_addr: hostname -jenkins_server_api_port: 8089 -interval: 10m -filter_builds_by: - - name: my-awesome-build - status: amber -track: - values: - example.metric.1: yes - example.metric.2: yes - example.metric.3: no - example.metric.4: no -``` - -{{% /tab %}} -{{% tab title="good config" %}} +{{% tab title="良い config" %}} ``` yaml --- @@ -55,23 +35,38 @@ metrics: enabled: true ``` +{{% /tab %}} +{{% tab title="悪い config" %}} + +```yaml +--- +jenkins_server_addr: hostname +jenkins_server_api_port: 8089 +interval: 10m +filter_builds_by: + - name: my-awesome-build + status: amber +track: + values: + example.metric.1: yes + example.metric.2: yes + example.metric.3: no + example.metric.4: no +``` + {{% /tab %}} {{% /tabs %}} -The bad configuration highlights how doing the opposite of the recommendations of configuration practices impacts the usability -of the component. It doesn't make it clear what field values should be, it includes features that can be pushed to existing processors, -and the field naming is not consistent with other components that exist in the collector. +悪い例では、Configuration のベストプラクティスに反するとコンポーネントが使いにくくなってしまうことが理解できるはずです。 +フィールドの値が何であるべきかを明確ではなく、既存のプロセッサーに移譲できる機能を含み、コレクター内の他のコンポーネントと比較してフィールドの命名に一貫性がありません。 -The good configuration keeps the required values simple, reuses field names from other components, and ensures the component focuses on -just the interaction between Jenkins and the collector. +良い例では、必要な値をシンプルに保ち、他のコンポーネントからのフィールド名を再利用し、コンポーネントが Jenkins とコレクター間の相互作用にのみ焦点を当てています。 -The code tab shows how much is required to be added by us and what is already provided for us by shared libraries within the collector. -These will be explained in more detail once we get to the business logic. The configuration should start off small and will change -once the business logic has started to include additional features that is needed. +設定値の中には、このコンポーネントで独自に追加するものと、コレクター内部の共有ライブラリによって提供されているものがあります。これらはビジネスロジックに取り組む際にさらに詳しく説明します。Configuration は小さく始めるべきで、ビジネスロジックに追加の機能が必要になったら、設定も追加していきましょう。 -## Write the code +## コードを書く -In order to implement the code needed for the configuration, we are going to create a new file named `config.go` with the following content: +Configuration に必要なコードを実装するために、`config.go` という名前の新しいファイルを以下の内容で作成します： ``` go package jenkinscireceiver diff --git a/content/ja/other/opentelemetry-collector/8-develop/3-component.md b/content/ja/other/opentelemetry-collector/8-develop/3-component.md index 91951c0b7b..083a9fa817 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/3-component.md +++ b/content/ja/other/opentelemetry-collector/8-develop/3-component.md @@ -1,70 +1,64 @@ --- -title: OpenTelemetry Collector Development -linkTitle: 8.3 Component Review +title: OpenTelemetry Collector を開発する +linkTitle: 8.3 コンポーネントを検討する weight: 11 --- -## Component Review +## コンポーネントを検討する -To recap the type of component we will need to in order to capture metrics from Jenkins: +Jenkinsからメトリクスを取得するために必要なコンポーネントの種類をおさらいしましょう： {{% tabs %}} -{{% tab title="Extension" %}} -The business use case an extension helps solves for are: +{{% tab title="エクステンション" %}} +エクステンションが解決するビジネスユースケースは以下の通りです： -1. Having shared functionality that requires runtime configuration -1. Indirectly helps with observing the runtime of the collector +1. 実行時の設定が必要な共有機能を持つ +1. コレクターの実行時間の観察に間接的に役立つ -See [Extensions Overview](../2-extensions) for more details. +詳細については、[エクステンションの概要](../2-extensions)を参照してください。 {{% /tab %}} -{{% tab title="Receiver" %}} -The business use case a receiver solves for: +{{% tab title="レシーバー" %}} +レシーバーが解決するビジネスユースケースは以下の通りです： -- Fetching data from a remote source -- Receiving data from remote source(s) +- リモートソースからのデータの取得 +- リモートソースからのデータの受信 -This are commonly referred to _pull_ vs _push_ based data collection, and you read more about the details in the [Receiver Overview](../3-receivers). +これらは一般的に _pull_ 対 _push_ ベースのデータ収集と呼ばれ、詳細については[レシーバーの概要](../3-receivers)で読むことができます。 {{% /tab %}} -{{% tab title="Processor" %}} -The business use case a processor solves for is: +{{% tab title="プロセッサー" %}} +プロセッサーが解決するビジネスユースケースは以下の通りです： -- Adding or removing data, fields, or values -- Observing and making decisions on the data -- Buffering, queueing, and reordering +- データ、フィールド、または値の追加または削除 +- データの観察と意思決定 +- バッファリング、キューイング、および並べ替え -The thing to keep in mind that the data type flowing through a processor needs to use the forward -the same data type to its downstream components. -Read through [Processor Overview](../4-processors) for the details. +プロセッサーを通過するデータタイプは、下流のコンポーネントに同じデータタイプを転送する必要があることを覚えておいてください。 +詳細については、[プロセッサーの概要](../4-processors)をご覧ください。 {{% /tab %}} -{{% tab title="Exporter" %}} -The business use case an exporter solves for: +{{% tab title="エクスポーター" %}} +エクスポーターが解決するビジネスユースケースは以下の通りです： -- Send the data to a tool, service, or storage +- データをツール、サービス、またはストレージに送信する -The OpenTelemetry collector does not want to be "backend", an all in one observability suite, but rather -keep to the principles that founded OpenTelemetry to begin with; A vendor agnostic Observability for all. -To help revisit the details, please read through [Exporter Overview](../5-exporters). +OpenTelemetryコレクターは「バックエンド」、すべてを一元化した観測可能性スイートを目指すのではなく、OpenTelemetryの創設原則に忠実であり続けることを目指しています。つまり、ベンダーに依存しない全ての人のための観測可能性です。詳細については、[エクスポーターの概要](../5-exporters)をお読みください。 {{% /tab %}} -{{% tab title="{{% badge style=primary icon=user-ninja %}}**Ninja:** Connectors{{% /badge %}}" %}} +{{% tab title="{{% badge style=primary icon=user-ninja %}}**Ninja:** コネクター{{% /badge %}}" %}} -This is a component type that was missed in the workshop since it is a relatively new addition to the collector, -but the best way to think about a connector is that it is like a processor that allows to be used across different -telemetry types, and pipelines. Meaning that a connector can accept data as logs, and output metrics, or accept -metrics from one pipeline and provide metrics on the data it has observed. +コネクターは比較的新しいコンポーネントで、このワークショップではあまり触れていません。 +コネクターは、異なるテレメトリタイプやパイプラインをまたいで使用できるプロセッサーのようなものだといえます。たとえば、コネクターはログとしてデータを受け取り、メトリクスとして出力したり、あるパイプラインからメトリクスを受け取り、テレメトリーデータに関するメトリクスを提供したりすることができます。 -The business case that a connector solves for: +コネクターが解決するビジネスケースは以下の通りです： -- Converting from different telemetry types - - logs to metrics - - traces to metrics - - metrics to logs -- Observing incoming data and producing its own data - - Accepting metrics and generating analytical metrics of the data. +- 異なるテレメトリタイプ間の変換 + - ログからメトリクスへ + - トレースからメトリクスへ + - メトリクスからログへ +- 受信したデータを観察し、自身のデータを生成する + - メトリクスを受け取り、データの分析メトリクスを生成する。 -There was a brief overview within the **Ninja** section as part of the [Processor Overview](../4-processors), -and be sure what the project for updates for new connector components. +**Ninja**セクションの一部として[プロセッサーの概要](../4-processors)内で簡単に概要が説明されています。 {{% /tab %}} {{% /tabs %}} -From the component overviews, it is clear that developing a pull based receiver for Jenkins. +これらのコンポーネントについて考えると、Jenkins に対応する場合はプルベースのレシーバーを開発する必要があることがわかります。 diff --git a/content/ja/other/opentelemetry-collector/8-develop/4-design.md b/content/ja/other/opentelemetry-collector/8-develop/4-design.md index 50bba23807..591ef36e03 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/4-design.md +++ b/content/ja/other/opentelemetry-collector/8-develop/4-design.md @@ -1,12 +1,12 @@ --- -title: OpenTelemetry Collector Development -linkTitle: 8.4 Designing the Metrics +title: OpenTelemetry Collector を開発する +linkTitle: 8.4 メトリクスを設計する weight: 12 --- -### Designing The Metrics +### メトリクスを設計する -To help define and export the metrics captured by our receiver, we will be using, [mdatagen](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/cmd/mdatagen), a tool developed for the collector that turns yaml defined metrics into code. +レシーバーによってキャプチャされるメトリクスを定義し、エクスポートするために、コレクターのために開発された [mdatagen](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/cmd/mdatagen) を使って、yaml で定義したメトリクスをコードに変換していきます。 {{% tabs %}} {{% tab title="metadata.yaml"%}} @@ -82,16 +82,13 @@ package jenkinscireceiver {{% /tab%}} {{% /tabs %}} -Create these files within the project folder before continuing onto the next section. +次のセクションに進む前に、これらのファイルをプロジェクトフォルダ内に作成してください。 -## Building The Factory +## Factory の構築 -The Factory is a software design pattern that effectively allows for an object, in this case a `jenkinscireceiver`, to be created -dynamically with the provided configuration. To use a more real world example, it would be going to a phone store, asking for a phone -that matches your exact description, and then provides it to you. +Factory はソフトウェアデザインパターンの一種で、提供された Configuration を使って、動的にオブジェクト（この場合は `jenkinscireceiver`）を作成するものです。現実的な例では、携帯電話店に行って、あなたの正確な説明に合った携帯電話を求め、それを提供されるようなものです。 -Run the following command `go generate -x ./...` , it will create a new folder, `jenkinscireceiver/internal/metadata`, -that contains all code required to export the defined metrics. The required code is: +コマンド `go generate -x ./...` を実行すると、定義されたメトリクスをエクスポートするために必要なすべてのコードを含む新しいフォルダ `jenkinscireceiver/internal/metadata` が作成されます。生成されるコードは以下の通りです： {{% tabs %}} {{% tab title="factory.go" %}} @@ -247,4 +244,4 @@ replaces: {{% /tab %}} {{% /tabs %}} -Once you have written these file into the project with the expected contents then run, `go mod tidy`, which will fetch all the remote depedancies and update `go.mod` and generate the `go.sum` files. +これらのファイルがプロジェクトに作成されたら、`go mod tidy` を実行します。すると、すべての依存ライブラリが取得され、`go.mod` が更新されます。 diff --git a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md index ee2eee3edb..64b4d79c74 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md +++ b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md @@ -1,33 +1,28 @@ --- -title: OpenTelemetry Collector Development -linkTitle: 8.5 Building Business Logic +title: OpenTelemetry Collector を開発する +linkTitle: 8.5 ビジネスロジックを作る weight: 13 --- -## Building The Business Logic +## ビジネスロジックを作る -At this point, we have a custom component that currently does nothing so we need to add in the required -logic to capture this data from Jenkins. +この時点では、何も行っていないカスタムコンポーネントが作成されています。ここから、Jenkins からデータを取得するための必要なロジックを追加していきましょう。 -From this point, the steps that we need to take are: +ここからのステップは以下の通りです： -1. Create a client that connect to Jenkins -1. Capture all the configured jobs -1. Report the status of the last build for the configured job -1. Calculate the time difference between commit timestamp and job completion. +1. Jenkinsに接続するクライアントを作成する +1. 設定されたすべてのジョブをキャプチャする +1. 設定されたジョブの最後のビルドのステータスを報告する +1. コミットタイムスタンプとジョブ完了の時間差を計算する -The changes will be made to `scraper.go`. +変更を `scraper.go` に加えていきます。 {{% tabs %}} -{{% tab title="1. Add Jenkins client" %}} +{{% tab title="1. Jenkins クライアントを追加する" %}} -To be able to connect to the Jenkins server, we will be using the package, -["github.com/yosida95/golang-jenkins"](https://pkg.go.dev/github.com/yosida95/golang-jenkins), -which provides the functionality required to read data from the jenkins server. +Jenkinsサーバーに接続するために、パッケージ ["github.com/yosida95/golang-jenkins"](https://pkg.go.dev/github.com/yosida95/golang-jenkins) を使用します。これには、Jenkinsサーバーからデータを読み取るために必要な機能が提供されています。 -Then we are going to utilise some of the helper functions from the, -["go.opentelemetry.io/collector/receiver/scraperhelper"](https://pkg.go.dev/go.opentelemetry.io/collector/receiver/scraperhelper) , -library to create a start function so that we can connect to the Jenkins server once component has finished starting. +次に、["go.opentelemetry.io/collector/receiver/scraperhelper"](https://pkg.go.dev/go.opentelemetry.io/collector/receiver/scraperhelper) ライブラリのいくつかのヘルパー関数を利用して、コンポーネントの起動が完了したらJenkinsサーバーに接続できるようにするスタート関数を作成します。 ```go package jenkinscireceiver @@ -78,17 +73,14 @@ func (scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { } ``` +これで、Jenkinsレシーバーを初期化するために必要なすべてのコードが完成しました。 -This finishes all the setup code that is required in order to initialise a Jenkins receiver. {{% /tab%}} -{{% tab title="2. Capture all configured jobs" %}} +{{% tab title="2. ジョブをキャプチャする" %}} -From this point on, we will be focuses on the `scrape` method that has been waiting to be filled in. -This method will be run on each interval that is configured within the configuration (by default, every minute). +ここから先は、実装が必要な `scrape` メソッドに焦点を当てます。このメソッドは、設定された間隔（デフォルトでは1分）ごとに実行されます。 -The reason we want to capture the number of jobs configured so we can see the growth of our Jenkins server, -and measure of many projects have onboarded. To do this we will call the jenkins client to list all jobs, -and if it reports an error, return that with no metrics, otherwise, emit the data from the metric builder. +Jenkins サーバーの負荷状況や、どの程度のプロジェクトが実行されているかを測定するために、Jenkins で設定されているジョブの数をキャプチャしたいと考えています。これを行うために、Jenkins クライアントを呼び出してすべてのジョブをリスト化し、エラーが報告された場合はメトリクスなしでそれを返し、そうでなければメトリクスビルダーからのデータを発行します。 ```go func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { @@ -111,11 +103,10 @@ func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { ``` {{% /tab%}} -{{% tab title="3. Report the status of each job" %}} +{{% tab title="3. ジョブの状態を報告する" %}} -In the last step, we were able to capture all jobs ands report the number of jobs -there was. Within this step, we are going to examine each job and use the report values -to capture metrics. +前のステップにより、すべてのジョブをキャプチャしてジョブの数をレポートできるようになりました。 +このステップでは、それぞれのジョブを調査し、レポートされた値を使用してメトリクスをキャプチャしていきます。 ```go func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { @@ -164,11 +155,11 @@ func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { return s.mb.Emit(), nil } ``` + {{% /tab%}} -{{% tab title="4. Report the delta" %}} +{{% tab title="4. 差分を報告する" %}} -The final step is to calculate how long it took from -commit to job completion to help infer our DORA metrics. +最後のステップでは、コミットからジョブ完了までにかかった時間を計算して、[DORA メトリクス](https://cloud.google.com/blog/products/devops-sre/using-the-four-keys-to-measure-your-devops-performance) を推測するのに役立てていきます。 ```go func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { @@ -220,18 +211,15 @@ func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { {{% /tab%}} {{% /tabs %}} -Once all of these steps have been completed, you now have built a custom Jenkins CI receiver! - -## Whats next? - -There are more than likely features that would be desired from component that you can think of, like: +これらのステップがすべて完了すると、Jenkins CI レシーバーが完成します！ -- Can I include the branch name that the job used? -- Can I include the project name for the job? -- How I calculate the collective job durations for project? -- How do I validate the changes work? +## 次は何をするの？ -Please take this time to play around, break it, change things around, or even try to capture logs from the builds. +コンポーネントに必要な機能は、おそらく他にもたくさん思いつくでしょう。例えば： +- ジョブで使用されたブランチ名を含めることはできますか？ +- ジョブのプロジェクト名を含めることはできますか？ +- プロジェクトのジョブの総持続時間をどのように計算しますか？ +- 変更が機能するかどうかをどのように検証しますか？ -[^1]: [DORA Metrics](https://cloud.google.com/blog/products/devops-sre/using-the-four-keys-to-measure-your-devops-performance) +この時間を使って遊んでみたり、壊してみたり、変更してみたり、ビルドからのログをキャプチャしてみるなどしてください。 diff --git a/content/ja/other/opentelemetry-collector/8-develop/_index.md b/content/ja/other/opentelemetry-collector/8-develop/_index.md index ac314df769..7772000dbd 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/_index.md +++ b/content/ja/other/opentelemetry-collector/8-develop/_index.md @@ -1,39 +1,39 @@ --- -title: OpenTelemetry Collector Development +title: OpenTelemetry Collector を開発する linkTitle: 8. Develop weight: 8 --- -## Developing a custom component +## カスタムコンポーネントの開発 -Building a component for the Open Telemetry Collector requires three key parts: +Open Telemetry Collectorのためのコンポーネントを構築するには、以下の3つの主要な部分が必要です： -1. The Configuration - _What values are exposed to the user to configure_ -1. The Factory - _Make the component using the provided values_ -1. The Business Logic - _What the component needs to do_ +1. Configuration - _ユーザーが設定できる値は何か_ +1. Factory - _提供された値を使ってコンポーネントを作成する_ +1. Business Logic - _コンポーネントが実行する必要があること_ -For this, we will use the example of building a component that works with Jenkins so that we can track important DevOps metrics of our project(s). +これについて、プロジェクトの重要なDevOpsメトリクスを追跡するためにJenkinsと連携するコンポーネントを構築する例を考えていきます。 -The metrics we are looking to measure are: +測定しようとしているメトリクスは次のとおりです： -1. Lead time for changes - _"How long it takes for a commit to get into production"_ -1. Change failure rate - _"The percentage of deployments causing a failure in production"_ -1. Deployment frequency - _"How often a [team] successfully releases to production"_ -1. Mean time to recover - _"How long does it take for a [team] to recover from a failure in production"_ +1. 変更に対するリードタイム - _「コミットが本番環境に入るまでにかかる時間」_ +1. 変更失敗率 - _「本番環境での障害を引き起こすデプロイの割合」_ +1. デプロイ頻度 - _「[チーム]が本番環境に成功してリリースする頻度」_ +1. 平均復旧時間 - _「[チーム]が本番環境の障害から復旧するのにかかる時間」_ -These indicators were identified Google's DevOps Research and Assesment (DORA)[^1] team to help -show performance of a software development team. The reason for choosing _Jenkins CI_ is that we remain in the same Open Source Software ecosystem which we can serve as the example for the vendor managed CI tools to adopt in future. +これらの指標は Google の [DevOps Research and Assessment (DORA)](https://dora.dev/) チームによって特定されたもので、ソフトウェア開発チームのパフォーマンスを示すのに役立ちます。_Jenkins CI_ を選択した理由は、私たちが同じオープンソースソフトウェアエコシステムに留まり、将来的にベンダー管理のCIツールが採用する例となることができるためです。 -## Instrument Vs Component +## 計装 🆚 コンポーネント -There is something to consider when improving level of Observability within your organisation -since there are some trade offs that get made. +組織内でオブザーバビリティを向上させる際には、トレードオフが発生するため、考慮する点があります。 -| | Pros | Cons | +| | 長所 | 短所 | | ----- | ----- | ----- | -| **(Auto) Instrumented** | Does not require an external API to be monitored in order to observe the system. | Changing instrumentation requires changes to the project. | -| | Gives system owners/developers to make changes in their observability. | Requires additional runtime dependancies. | -| | Understands system context and can corrolate captured data with _Exemplars_. | Can impact performance of the system. | -| **Component** | - Changes to data names or semantics can be rolled out independently of the system's release cycle. | Breaking API changes require a coordinated release between system and collector. | -| | Updating/extending data collected is a seemless user facing change. | Captured data semantics can unexpectedly break that does not align with a new system release. | -| | Does not require the supporting teams to have a deep understanding of observability practice. | Strictly external / exposed information can be surfaced from the system. | +| **（自動）計装**[^1] | システムを観測するために外部APIが不要 | 計装を変更するにはプロジェクトの変更が必要 | +| | システム所有者/開発者は可観測性の変更が可能 | ランタイムへの追加の依存が必要 | +| | システムの文脈を理解し、_Exemplar_ とキャプチャされたデータを関連付けることが可能 | システムのパフォーマンスに影響を与える可能性がある | +| **コンポーネント** | データ名や意味の変更をシステムのリリースサイクルから独立した展開が可能 | APIの破壊的な変更の可能性があり、システムとコレクター間でリリースの調整が必要 | +| | その後の利用に合わせて収集されるデータの更新/拡張が容易 | キャプチャされたデータの意味がシステムリリースと一致せず、予期せず壊れる可能性がある | + + +[^1]: 計装（instrument, インストゥルメント）とは、アプリケーションなどのシステムコンポーネントに対して、トレースやメトリクス、ログなどのテレメトリーデータを出力させる実装。計装ライブラリを最低限セットアップするだけで一通りのトレースやメトリクスなどを出力できるような対応を「自動計装」と呼びます。 From 16c1e6838c5cdb07c5835ca922842f65de010b3e Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Wed, 6 Dec 2023 09:30:36 +0900 Subject: [PATCH 10/12] fix --- .../opentelemetry-collector/3-receivers/3-other-receivers.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md index d272547046..dba4a00fe7 100644 --- a/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md +++ b/content/ja/other/opentelemetry-collector/3-receivers/3-other-receivers.md @@ -30,7 +30,7 @@ receiver creator とそれに関連する observer エクステンションの この Ninja ゾーンに必要なものは2つだけです: -1. ビbuilder manifestに、 receiver creator レシーバーと observer エクステンションが追加する +1. builder manifestに、 receiver creator レシーバーと observer エクステンションを追加する 2. 検出されたエンドポイントを検出するように、設定を作成する 次のようにすると、設定をテンプレート化できます: From 9622dd14345337a6b203f2f2d32ca63af4ca6982 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Fri, 8 Dec 2023 18:21:56 +0900 Subject: [PATCH 11/12] fix code --- .../8-develop/5-business-logic.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md index 64b4d79c74..77935f1c32 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md +++ b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md @@ -40,7 +40,7 @@ import ( ) type scraper struct { - mb *metadata.Metricsbuilder + mb *metadata.MetricsBuilder client *jenkins.Jenkins } @@ -52,8 +52,8 @@ func newScraper(cfg *Config, set receiver.CreateSettings) (scraperhelper.Scraper return scraperhelper.NewScraper( metadata.Type, s.scrape, - scarperhelper.WithStart(func(ctx context.Context, h component.Host) error { - client, err := cfg.ToClient(h, set) + scraperhelper.WithStart(func(ctx context.Context, h component.Host) error { + client, err := cfg.ToClient(h, set.TelemetrySettings) if err != nil { return err } @@ -63,7 +63,7 @@ func newScraper(cfg *Config, set receiver.CreateSettings) (scraperhelper.Scraper s.client = jenkins.NewJenkins(nil, cfg.Endpoint) s.client.SetHTTPClient(client) return nil - }) + }), ) } @@ -83,7 +83,7 @@ func (scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { Jenkins サーバーの負荷状況や、どの程度のプロジェクトが実行されているかを測定するために、Jenkins で設定されているジョブの数をキャプチャしたいと考えています。これを行うために、Jenkins クライアントを呼び出してすべてのジョブをリスト化し、エラーが報告された場合はメトリクスなしでそれを返し、そうでなければメトリクスビルダーからのデータを発行します。 ```go -func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { +func (s scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { jobs, err := s.client.GetJobs() if err != nil { return pmetric.Metrics{}, err @@ -109,7 +109,7 @@ func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { このステップでは、それぞれのジョブを調査し、レポートされた値を使用してメトリクスをキャプチャしていきます。 ```go -func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { +func (s scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { jobs, err := s.client.GetJobs() if err != nil { return pmetric.Metrics{}, err @@ -162,7 +162,7 @@ func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { 最後のステップでは、コミットからジョブ完了までにかかった時間を計算して、[DORA メトリクス](https://cloud.google.com/blog/products/devops-sre/using-the-four-keys-to-measure-your-devops-performance) を推測するのに役立てていきます。 ```go -func (s scrape) scrape(ctx context.Context) (pmetric.Metrics, error) { +func (s scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { jobs, err := s.client.GetJobs() if err != nil { return pmetric.Metrics{}, err From 079b13cb613f9c8392e6566abb2222a0c5cf6ab5 Mon Sep 17 00:00:00 2001 From: Kazunori Otani Date: Fri, 8 Dec 2023 18:39:48 +0900 Subject: [PATCH 12/12] fix --- .../other/opentelemetry-collector/8-develop/5-business-logic.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md index 77935f1c32..955c837516 100644 --- a/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md +++ b/content/ja/other/opentelemetry-collector/8-develop/5-business-logic.md @@ -67,7 +67,7 @@ func newScraper(cfg *Config, set receiver.CreateSettings) (scraperhelper.Scraper ) } -func (scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { +func (s scraper) scrape(ctx context.Context) (pmetric.Metrics, error) { // To be filled in return pmetric.NewMetrics(), nil }

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