This page contains a reference for using the OpenTelemetry Collector to send trace data from your application to any of Tracetest's supported trace data stores.
:::tip
Examples of configuring Tracetest can be found in the examples folder of the Tracetest GitHub repo.
:::
Tracetest is designed to work with different trace data stores. To enable Tracetest to run end-to-end tests against trace data, you need to configure Tracetest to access trace data.
Currently, Tracetest supports the following data stores. Click on the respective data store to view configuration examples:
- Jaeger
- OpenSearch
- Elastic APM
- SignalFX
- Grafana Tempo
- Lightstep
- New Relic
- AWS X-Ray3
- Datadog
- Honeycomb
- Azure App Insights
- Dynatrace
Continue reading below to learn how to configure the OpenTelemetry Collector to send trace data from your application to any of the trace data stores above.
In your OpenTelemetry Collector config file, make sure to set the exporter to jaeger, with the endpoint pointing to your Jaeger instance on port 14250. If you are running Tracetest with Docker, the endpoint might look like this http://jaeger:14250.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and still use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 100ms
exporters:
jaeger:
endpoint: jaeger:14250
tls:
insecure: true
service:
pipelines:
# You probably already have a traces pipeline, you don't have to change it.
# Just add this one to your configuration. Just make sure to not have two
# pipelines with the same name.
traces/1:
receivers: [otlp] # your receiver
processors: [batch] # make sure to add the batch processor
exporters: [jaeger] # your exporter pointing to your Jaeger instanceYou'll configure the OpenTelemetry Collector to receive traces from your system and then send them to OpenSearch via Data Prepper. And, you don't have to change your existing pipelines to do so.
In your OpenTelemetry Collector config file, make sure to set the exporter to otlp, with the endpoint pointing to the Data Prepper on port 21890. If you are running Tracetest with Docker, the endpoint might look like this data-prepper:21890.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 100ms
exporters:
logging:
loglevel: debug
otlp/2:
endpoint: data-prepper:21890
tls:
insecure: true
insecure_skip_verify: true
service:
pipelines:
# You probably already have a traces pipeline, you don't have to change it.
# Just add this one to your configuration. Just make sure to not have two
# pipelines with the same name.
traces/1:
receivers: [otlp] # your receiver
processors: [batch] # make sure to add the batch processor
exporters: [otlp/2] # your exporter pointing to your Data Prepper instanceYou'll configure the OpenTelemetry Collector to receive traces from your system and then send them to Elasticsearch via Elastic APM. And, you don't have to change your existing pipelines to do so.
In your OpenTelemetry Collector config file, make sure to set the exporter to otlp, with the endpoint pointing to the Elastic APM server on port 8200. If you are running Tracetest with Docker, the endpoint might look like this apm-server:8200.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 100ms
exporters:
otlp/elastic:
endpoint: apm-server:8200
tls:
insecure: true
insecure_skip_verify: true
service:
pipelines:
# You probably already have a traces pipeline, you don't have to change it.
# Just add this one to your configuration. Just make sure to not have two
# pipelines with the same name.
traces/1:
receivers: [otlp] # your receiver
processors: [batch] # make sure to add the batch processor
exporters: [otlp/elastic] # your exporter pointing to your Elastic APM server instanceYou'll configure the OpenTelemetry Collector to receive traces from your system and then send them to SignalFx. And, you don't have to change your existing pipelines to do so.
In your OpenTelemetry Collector config file, make sure to set the exporter to sapm, with the endpoint pointing to the SignalFx trace ingestion endpoint. The endpoint might look like this https://ingest.us1.signalfx.com/v2/trace. Also make sure to add your SignalFx access_token.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 100ms
exporters:
sapm:
access_token: <YOUR_TOKEN> # UPDATE THIS
access_token_passthrough: true
endpoint: https://ingest.us1.signalfx.com/v2/trace # UPDATE THIS IF NEEDED
max_connections: 100
num_workers: 8
service:
pipelines:
# your probably already have a traces pipeline, you don't have to change it.
# just add this one to your configuration. Just make sure to not have two
# pipelines with the same name
traces/1:
receivers: [otlp] # your receiver
processors: [batch] # make sure to add the batch processor
exporters: [sapm] # your exporter pointing to your SignalFx instanceYou'll configure the OpenTelemetry Collector to receive traces from your system and then send them to Tempo. And, you don't have to change your existing pipelines to do so.
In your OpenTelemetry Collector config file, make sure to set the exporter to tempo, with the endpoint pointing to your Tempo's instance on port 4317. If you are running Tracetest with Docker, the endpoint might look like this http://tempo:4317.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and still use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 100ms
exporters:
otlp/2:
endpoint: tempo:4317
tls:
insecure: true
service:
pipelines:
# your probably already have a traces pipeline, you don't have to change it.
# just add this one to your configuration. Just make sure to not have two
# pipelines with the same name
traces/1:
receivers: [otlp] # your receiver
processors: [batch] # make sure to have the probabilistic_sampler before your batch processor
exporters: [otlp/2] # your exporter pointing to your Tempo instanceYou'll configure the OpenTelemetry Collector to receive traces from your system and then send them to Azure App Insights. And, you don't have to change your existing pipelines to do so.
In your OpenTelemetry Collector config file, make sure to set the exporter to azuremonitor, with the endpoint instrumentation key of your Azure App Insights instance.
# collector.config.yaml
# If you already have receivers declared, you can just ignore
# this one and still use yours instead.
receivers:
otlp:
protocols:
grpc:
http:
exporters:
azuremonitor:
instrumentation_key: <your-instrumentation-key>
service:
pipelines:
traces/appinsights:
receivers: [otlp] # your receiver
exporters: [azuremonitor] # your exporter pointing to your Azure App Insights instance