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Standard Plugins

Plugins are the way to extend the Monasca Agent. Plugins add additional functionality that allow the agent to perform checks on other applications, servers or services. Some plugins may have corresponding Detection Plugins to automatically detect, configure, and activate certain Agent plugins. This section describes the standard plugins that are delivered by default.

** Standard location for plugin YAML config files **

/etc/monasca/agent/conf.d/

The following plugins are delivered via setup as part of the standard plugin checks. See Customizations.md for how to write new plugins.

Setup Plugin Name Dot File Detail
a10
apache /root/.apache.cnf Apache web server
cacti
cAdvisor_host
cert_check
check_mk_local
couch
couchbase
cpu
crash
directory
disk
docker
elastic
file_size
gunicorn
haproxy
hdfs
host_alive
http_check
http_metrics
iis Microsoft Internet Information Services
jenkins
json_plugin
kafka_consumer
kibana kibana_install_dir/kibana.yml Integration to Kibana
kubernetes
kubernetes_api
kyototycoon
libvirt
lighttpd
load
mcache
memory
mk_livestatus
mongo
mysql /root/.my.cnf
nagios_wrapper
network
nginx Tracks basic nginx metrics via the status module
ntp Uses ntplib to grab a metric for the ntp offset
postfix Provides metrics on the number of messages in a given postfix queue
postgres
process
prometheus
rabbitmq /root/.rabbitmq.cnf
redisdb
riak
solidfire Track cluster health and use stats
sqlserver
supervisord
swift_diags
tcp_check
varnish
vcenter
vcenter_slim Tracks vm status only
vertica /root/.vertica.cnf
wmi_check
zk Apache Zookeeper

Dot File Configuration

Dot files, as referenced above, provide an added level of configuration to some component plugins. Here are a few examples:

apache

Example for apache process and server-status metrics (secure)
[client]
user=root
password=pass
url=https://localhost/server-status?auto
or
Example for apache process and server-status metrics (non-secure)
[client]
url=http://localhost/server-status?auto
or
Example for apache process metrics only
[client]
use_server_status_metrics=false

mysql

[client]
user=root
password=pass
host=server
socket=/var/run/mysqld/mysqld.sock
ssl_ca=/etc/ssl/certs/ca-certificates.crt

rabbitmq

[client]
user=guest
password=pass
nodes=rabbit@devstack
queues=conductor
exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat,ironic,openstack

Plugin Configuration

Each plugin has a corresponding YAML configuration file with the same stem name as the plugin script file.

The configuration file has the following structure:

init_config:
    key1: value1
    key2: value2

instances:
    - username: john_smith
      password: 123456
      dimensions:
          node_type: test
    - username: jane_smith
      password: 789012
      dimensions:
          node_type: production

init_config

In the init_config section you can specify an arbitrary number of global name:value pairs that will be available on every run of the check in self.init_config. Here you can specify a collection frequency specific to the plugin by setting collect_period. The global frequency at which all plugins are run is specified by the variable "check_frequency" defined in https://github.com/openstack/monasca-agent/blob/master/docs/Agent.md. Under normal and default conditions when a plugin runs all the metrics are collected and sent. For example, if check_frequency=30, by default the plugin will be run every 30 seconds and the metrics will be sent. The variable "collect_period" allows each plugins collect period to be further adjusted to a value greater than the frequency at which the plugin is run specified by "check_frequency", such that when the collection run starts, the plugin might not be called. For example, if check_frequency=30 and collect_period=600, the plugin will be called and metrics sent every 600 seconds. This allows fewer metrics to be sent. The "collect_period" should be evenly divisible by the "check_frequency". For example, if you want the plugin to collect and send metrics every 600 seconds (10 minutes), and the global check_frequency=30, then the collect_period should be set to 600. If the "collect_period" is not evenly divisible by the "check_frequency" then the "collect_period" will get rounded up to the nearest multiple of the "check_frequency". For example, if the collect_period=45 and the global check_frequency=30, then the "collect_period" will get rounded up to 60 and the plugin will get called and send metrics every 60 seconds.

instances

The instances section is a list of instances that this check will be run against. Your actual check() method is run once per instance. The name:value pairs for each instance specify details about the instance that are necessary for the check.

dimensions

The instances section can also contain optional dimensions. These dimensions will be added to any metrics generated by the check for that instance.

Plugin Documentation

Your plugin should include an example YAML configuration file to be placed in /etc/monasca/agent/conf.d/ which has the name of the plugin YAML file plus the extension '.example', so the example configuration file for the process plugin would be at /usr/local/share/monasca/agent/conf.d/process.yaml.example. This file should include a set of example init_config and instances clauses that demonstrate how the plugin can be configured.

Detection Plugins

The monasca_setup library contains a number of detection plugins, which are located within the library at

monasca_setup/detection/plugins/

Some detection plugins activate a specific Agent plugin of the same name, and some leverage other general-purpose Agent plugins to monitor a particular service. There are three classes in total:

Plugin

The base class of detection plugins requires a separate Agent plugin of the same name.

ArgsPlugin

Any plugins which are configured by passing arguments, rather than relying on detection, may use the ArgsPlugin class.

ServicePlugin

This class covers Process, HTTP endpoints, Directory, and File monitoring. It is primarily used for monitoring OpenStack components. Note: There are existing default detection plugins for http_check.py, directory.py, and file_size.py that only require configuration.

A process can be monitored by process_names or by process_username. Pass in the process_names list argument when watching process by name. Pass in the process_username argument and component_name arguments when watching process by username. Watching by username is useful for groups of processes that are owned by a specific user. For process monitoring by process_username the component_name is required since it is used to initialize the instance name in process.yaml. component_name is optional for monitoring by process_name and all other checks.

An http endpoint connection can be checked by passing in the service_api_url and optional search_pattern parameters. The http check can be skipped by specifying the argument 'disable_http_check'

Directory size can be checked by passing in a directory_names list.

File size can be checked by passing in a file_dirs_names list where each directory name item includes a list of files. example: 'file_dirs_names': [('/var/log/monasca/api', ['monasca-api'])]

Note: service_name and component_name are optional (except component_name is required with process_username) arguments used for metric dimensions by all checks.

List of Detection Plugins

These are the detection plugins included with the Monasca Agent. See Customizations.md for how to write new detection plugins.

Detection Plugin Name Type
a10 Plugin
apache Plugin
barbican ServicePlugin
bind Plugin
cassandra ServicePlugin
ceilometer ServicePlugin
ceph Plugin
cert_check ArgsPlugin
check_mk_local Plugin
cinder ServicePlugin
cloudkitty ServicePlugin
crash Plugin
cue ServicePlugin
designate ServicePlugin
directory ServicePlugin
file_size ServicePlugin
freezer Plugin (multiple)
glance ServicePlugin
haproxy Plugin
heat ServicePlugin
host_alive ArgsPlugin
http_check ArgsPlugin
ironic ServicePlugin
kafka_consumer Plugin
keystone ServicePlugin
libvirt Plugin
magnum ServicePlugin
mk_livestatus Plugin
mon Plugin (multiple)
mysql Plugin
neutron ServicePlugin
nova ServicePlugin
ntp Plugin
octavia ServicePlugin
ovsvapp ServicePlugin
postfix Plugin
powerdns Plugin
process Plugin
rabbitmq Plugin
supervisord Plugin
swift ServicePlugin
system Plugin
trove ServicePlugin
vcenter Plugin
vertica Plugin
zookeeper Plugin
kibana Plugin

Agent Plugin Detail

This section documents all the checks that are supplied by the Agent.

System Metrics

This section documents the system metrics that are sent by the Agent.

Docker environment:

For Docker environment you can enable the system plugins by adding cpu, disk, memory and load yaml files to the monasca-agent-collector container (mount plugin files to /plugins.d/cpu|disk|memory|load.yaml). Additionally you have to specify the path of the host process filesystem. In this case mount host root directory / to /rootfs in the container. Docker compose example:

volumes:
  - "/:/rootfs:ro"

Sample configurations:

cpu.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: cpu_stats

disk.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: disk_stats
  ignore_filesystem_types: iso9660,tmpfs,nsfs

memory.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: memory_stats

load.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: load_stats

CPU

Metric Name Dimensions Semantics
cpu.idle_perc Percentage of time the CPU is idle when no I/O requests are in progress
cpu.wait_perc Percentage of time the CPU is idle AND there is at least one I/O request in progress
cpu.stolen_perc Percentage of stolen CPU time, i.e. the time spent in other OS contexts when running in a virtualized environment
cpu.system_perc Percentage of time the CPU is used at the system level
cpu.user_perc Percentage of time the CPU is used at the user level
cpu.total_logical_cores Total number of logical cores available for an entire node (Includes hyper threading). NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
cpu.percent Percentage of time the CPU is used in total
cpu.idle_time Time the CPU is idle when no I/O requests are in progress
cpu.wait_time Time the CPU is idle AND there is at least one I/O request in progress
cpu.user_time Time the CPU is used at the user level
cpu.system_time Time the CPU is used at the system level
cpu.frequency_mhz Maximum MHz value for the cpu frequency. NOTE: This value is dynamic, and driven by CPU governor depending on current resource need .

Load

Metric Name Dimensions Semantics
load.avg_1_min The normalized (by number of logical cores) average system load over a 1 minute period
load.avg_5_min The normalized (by number of logical cores) average system load over a 5 minute period
load.avg_15_min The normalized (by number of logical cores) average system load over a 15 minute period

Memory

Metric Name Dimensions Semantics
mem.free_mb Mbytes of free memory
mem.swap_free_perc Percentage of free swap memory that is free
mem.swap_free_mb Mbytes of free swap memory that is free
mem.swap_total_mb Mbytes of total physical swap memory
mem.swap_used_mb Mbytes of total swap memory used
mem.total_mb Total Mbytes of memory
mem.usable_mb Total Mbytes of usable memory
mem.usable_perc Percentage of total memory that is usable
mem.used_buffers Number of buffers in Mbytes being used by the kernel for block io
mem.used_cached Mbytes of memory used for the page cache
mem.used_shared Mbytes of memory shared between separate processes and typically used for inter-process communication
mem.used_real_mb Mbytes of memory currently in use less mem.used_buffers and mem.used_cached

Disk

Metric Name Dimensions Semantics
disk.inode_used_perc device, mount_point The percentage of inodes that are used on a device
disk.space_used_perc device, mount_point The percentage of disk space that is being used on a device
disk.total_space_mb The total amount of disk space in Mbytes aggregated across all the disks on a particular node. NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
disk.total_used_space_mb The total amount of used disk space in Mbytes aggregated across all the disks on a particular node. NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
io.read_kbytes_sec device Kbytes/sec read by an io device
io.read_req_sec device Number of read requests/sec to an io device
io.read_time_sec device Amount of read time in seconds to an io device
io.write_kbytes_sec device Kbytes/sec written by an io device
io.write_req_sec device Number of write requests/sec to an io device
io.write_time_sec device Amount of write time in seconds to an io device

Network

The network check can be configured to submit its metrics in either bytes/sec or bits/sec. The default behavior is to submit bytes. To submit net.in_bits_sec and net.out_bits_sec rather than net.in_bytes_sec and net.out_bytes_sec, set the config option use_bits to true for the instance you want to configure.

Example configuration:

init_config: null
instances:
- built_by: System
  excluded_interface_re: lo.*|vnet.*|tun.*|ovs.*|br.*|tap.*|qbr.*|qvb.*|qvo.*
  name: network_stats
  send_rollup_stats: true
  use_bits: false
Metric Name Dimensions Semantics
net.in_bytes_sec device Number of network bytes received per second
net.out_bytes_sec device Number of network bytes sent per second
net.in_packets_sec device Number of network packets received per second
net.out_packets_sec device Number of network packets sent per second
net.in_errors_sec device Number of network errors on incoming network traffic per second
net.out_errors_sec device Number of network errors on outgoing network traffic per second
net.in_packets_dropped_sec device Number of inbound network packets dropped per second
net.out_packets_dropped_sec device Number of outbound network packets dropped per second
net.int_status device Network interface status

Monasca Agent

The Monasca Agent itself generates a small number of metrics.

Metric Name Dimensions Semantics
monasca.thread_count service=monitoring component=monasca-agent Number of threads that the collector is consuming for this collection run
monasca.emit_time_sec service=monitoring component=monasca-agent Amount of time that the forwarder took to send metrics to the Monasca API.
monasca.collection_time_sec service=monitoring component=monasca-agent Amount of time that the collector took for this collection run

Limiting System Metrics

It is possible to reduce the number of system metrics with certain configuration parameters.

Config Option Values Description
net_bytes_only true/false Sends bytes/sec metrics only, disabling packets/sec, packets_dropped/sec, and errors/sec.
cpu_idle_only true/false Sends idle_perc only, disabling wait/stolen/system/user metrics
send_io_stats true/false If true, sends I/O metrics for each disk device. If false, sends only disk space metrics.

These parameters may added to instances in the plugin .yaml configuration file, or added via monasca-setup like this:

$ monasca-setup -d system -a 'cpu_idle_only=true net_bytes_only=true send_io_stats=false' --overwrite

By default, all metrics are enabled.

A10

This section describes the A10 System Check.

init_config:

instances:
    - name: a10_system_check
        a10_device: a10_device_ip
        a10_username: admin
        a10_password: password
Metric Name Dimensions Semantics
a10.memory_total_mb a10_device, service=networking Total memory presented in MB
a10.memory_used_mb a10_device, service=networking Memory used presented in MB
a10.memory_free_mb a10_device, service=networking Free memory presented in MB
a10.memory_used a10_device, service=networking Realtime Memory Usage

Apache

This section describes the Apache Web Server check that can be performed by the Agent. The Apache check gathers metrics on the Apache Web Server. The Apache check requires a configuration file called apache.yaml to be available in the agent conf.d configuration directory. The config file must contain the server url, username and password (If you are using authentication) that you are interested in monitoring.

Sample config:

init_config:

instances:
  - apache_status_url: http://localhost/server-status?auto
    apache_user: root
    apache_password: password

If you want the monasca-setup program to detect and auto-configure the plugin for you, you must create the file /root/.apache.cnf with the information needed in the configuration yaml file before running the setup program. It should look something like this:

[client]
url=http://localhost/server-status?auto
user=root
password=password

The Apache checks return the following metrics:

Metric Name Dimensions Semantics
apache.performance.idle_worker_count hostname, service=apache component=apache The number of idle workers
apache.performance.busy_worker_count hostname, service=apache component=apache The number of workers serving requests
apache.performance.cpu_load_perc hostname, service=apache component=apache The current percentage of CPU used by each worker and in total by all workers combined
apache.net.total_kbytes hostname, service=apache component=apache Total Kbytes
apache.net.hits hostname, service=apache component=apache Total accesses
apache.net.kbytes_sec hostname, service=apache component=apache Total Kbytes per second
apache.net.requests_sec hostname, service=apache component=apache Total accesses per second

Cacti

See the example configuration for how to configure the Cacti plugin.

cAdvisor_host

This plugin collects metrics about a host from a given cAdvisor instance. This is useful in a container environment where the agent is running in a container but still wants to monitor the underlying hosts.

It connects to the cAdvisor instance and queries the stats API about the host.

There are two ways to configure the plugin.

  • Set cAdvisor url
  • Set kubernetes detect url to True. If true, the assumption is that the Agent is running in a Kubernetes container. The agent will obtain the cAdvisor url by first querying the Kubernetes API to ask which node it is running on and then from there hit the local cAdvisor on that node that is included in the kubelet.

As a result the plugin only supports getting data from one cAdvisor endpoint. So the config yaml file must only have one instance defined under instances. (Example shown below)

Sample config (passing in cAdvisor url):

init_config:
    # Timeout on GET requests to the cAdvisor endpoints
    connection_timeout: 3
instances:
    # Set to the url of the cAdvisor instance you want to connect to
    - cadvisor_url: "127.0.0.1:4194"

Sample config (setting Kubernetes detect cAdvisor url):

init_config:
    # Timeout on GET requests to the cAdvisor endpoints
    connection_timeout: 3
instances:
    # Set to the url of the cAdvisor instance you want to connect to
    - kubernetes_detect_cadvisor: True

Note if both a url and detect cAdvisor are both set it will by default use the url

The cAdvisor host check returns the following metrics:

Metric Name Dimensions Semantics
cpu.num_cores hostname, unit Number of cores of host
cpu.system_time hostname, unit Cumulative system CPU time consumed in core seconds
cpu.system_time_sec hostname, unit Rate of system CPU time consumed in core seconds per second
cpu.total_time hostname, unit Cumulative CPU time consumed in core seconds
cpu.total_time_sec hostname, unit Rate of CPU time consumed in core seconds per second
cpu.user_time hostname, unit Cumulative user cpu time consumed in core seconds
cpu.user_time_sec hostname, unit Rate of user CPU time consumed in core seconds per second
fs.total_bytes hostname, device, unit Number of bytes available
fs.usage_bytes hostname, device, unit Number of bytes consumed
fs.usage_perc hostname, device, unit Usage of fs as percentage
io.read_bytes hostname, unit Total number of bytes read by all devices
io.read_bytes_sec hostname, unit Total number of bytes read by all devices per second
io.write_bytes hostname, unit Total number of bytes written by all devices
io.write_bytes_sec hostname, unit Total number of bytes written by all devices per second
mem.cache_bytes hostname, unit Number of bytes of page cache memory
mem.swap_bytes hostname, unit Swap usage in memory in bytes
mem.used_bytes hostname, unit Current memory in use in bytes
mem.used_perc hostname, unit Current memory usage as percentage
mem.working_set_bytes hostname, unit Current working set of memory in bytes (total minus cache)
net.in_bytes hostname, interface, unit Total network bytes received by all interfaces
net.in_bytes_sec hostname, interface, unit Total number of network bytes received by all interfaces per second
net.in_dropped_packets hostname, interface, unit Total inbound network packets dropped by all interfaces
net.in_dropped_packets_sec hostname, interface, unit Total number of inbound network packets dropped by all interfaces per second
net.in_errors hostname, interface, unit Total network errors on incoming network traffic by all interfaces
net.in_errors_sec hostname, interface, unit Total number of network errors on incoming network traffic by all interfaces per second
net.in_packets hostname, interface, unit Total network packets received by all interfaces
net.in_packets_sec hostname, interface, unit Total number of network packets received by all interfaces per second
net.out_bytes hostname, interface, unit Total network bytes sent by all interfaces
net.out_bytes_sec hostname, interface, unit Total number of network bytes sent by all interfaces per second
net.out_dropped_packets hostname, interface, unit Total outbound network packets dropped by all interfaces
net.out_dropped_packets_sec hostname, interface, unit Total number of outbound network packets dropped by all interfaces per second
net.out_errors hostname, interface, unit Total network errors on outgoing network traffic by all interfaces
net.out_errors_sec hostname, interface, unit Total number of network errors on outgoing network traffic by all interfaces per second
net.out_packets hostname, interface, unit Total network packets sent by all interfaces
net.out_packets_sec hostname, interface, unit Total number of network packets sent by all interfaces per second

Cassandra Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the Cassandra service. Please note that no directories are monitored per default. directory_names argument can be passed to monasca-setup to change this behaviour.

The following Cassandra processes are monitored, if they exist when the monasca-setup script is run:

Cassandra Processes Monitored
  • cassandra
Example Cassandra Metrics

| Component | Metric Name | Metric Type | Check Type | Dimensions | Plugin | Description | | --------- | ----------- | ----------- | ---------- | ---- | ------ | ----------- | ----- | | cassandra | process_pid_count | Gauge | Passive | service=cassandra, component=cassandra, process_user=cassandra | process | cassandra process pid count | | cassandra | directory.files_count | Gauge | Active | service=cassandra, component=cassandra, path=/var/cassandra/data | cassandra data directory file count | | cassandra | directory.size_bytes | Gauge | Active | service=cassandra, component=cassandra, path=/var/cassandra/data | cassandra data directory size | | cassandra | directory.files_count | Gauge | Active | service=cassandra, component=cassandra, path=/var/cassandra/commitlog | cassandra commit log directory file count | | cassandra | directory.size_bytes | Gauge | Active | service=cassandra, component=cassandra, path=/var/cassandra/commitlog | cassandra commit log directory size |

Check_MK_Local

The Check_MK Agent can be extended through a series of local checks. This plugin parses the <<<local>>> output of check_mk_agent and converts them into Monasca metrics. It is installed by monasca-setup automatically when the check_mk_agent script is found to be installed on the system.

The default configuration is to submit metrics from all local checks returned by check_mk_agent. One metric will be submitted for the status code, and one additional metric for each performance measurement included in the result. The basic format of check_mk_agent local check output is:

<status> <item name> <performance data> <check output>

So if the output line is:

0 glance_registry response_time=0.004 glance_registry: status UP http://0.0.0.0:9191

the check_mk_local plugin for the Monasca Agent will return these metrics:

 Timestamp:  1430848955
 Name:       check_mk.glance_registry.status
 Value:      0
 Dimensions: hostname=devstack
             service=monitoring
 Value Meta: detail=glance_registry: status UP http://0.0.0.0:9191

and

 Timestamp:  1430852467
 Name:       check_mk.glance_registry.response_time
 Value:      0.006
 Dimensions: hostname=devstack
             service=monitoring
 Value Meta: None

The name of the metric starts with check_mk., includes the check_mk item name, and is followed by either status for the Nagios status code (0, 1, 2, or 3), or the name of the performance metric. The free-form output from the check is included in the meta field of the check status.

You may override these defaults in the configuration, which by default is /etc/monasca/agent/conf.d/check_mk_local.yaml.

init_config:
    mk_agent_path: /usr/bin/check_mk_agent

    custom:
      - mk_item: sirius-api
        discard: false
        dimensions: {'component': 'sirius'}
        metric_name_base: check_mk.sirius_api
      - mk_item: eon-api
        discard: true

instances:
    - {}

The custom section of init_config is optional and may be blank or removed entirely. In this section, you may add custom rules to Monasca metrics based on the check_mk item name.

  • mk_item - This is the name (2nd field) returned by check_mk_agent
  • discard - Exclude the metric from Monasca, True or False (if discard is not specified, the default is False)
  • dimensions - Extra dimensions to include, in {'name': 'value'} format.
  • metric_name_base - This represents the leftmost part of the metric name to use. Status and any performance metrics are appended following a dot, so ".status" and ".response_time" would be examples.

Because check_mk_agent can only return all local metrics at once, the check_mk_local plugin requires no instances to be defined in the configuration. It runs check_mk_agent once and processes all the results. This way, new check_mk local scripts can be added without having to modify the plugin configuration.

Ceph

This section describes the Ceph check that can be performed by the Agent. The Ceph check gathers metrics from multiple ceph clusters. The Ceph check requires a configuration file called ceph.yaml to be available in the agent conf.d configuration directory. The config file must contain the cluster name that you are interested in monitoring (defaults to ceph). Also, it is possible to configure the agent to collect only specific metrics about the cluster (usage, stats, monitors, osds or pools).

Requirements:

  • ceph-common
  • The user running monasca-agent must be able to execute ceph commands. This can be done by adding the monasca-agent user to the ceph group, and giving group read permission on the ceph.client.admin.keyring file.
  usermod -a -G ceph monasca-agent
  chmod 0640 /etc/ceph/ceph.client.admin.keyring

Alternatively, you can configure monasca-agent to use sudo using the use_sudo option. The example configuration below assumes you added the monasca-agent user to the ceph group which does not require using sudo.

Sample config:

init_config:

instances:
  - cluster_name: ceph
    use_sudo: False
    collect_usage_metrics: True
    collect_stats_metrics: True
    collect_mon_metrics: True
    collect_osd_metrics: True
    collect_pool_metrics: True

The Ceph checks return the following metrics:

Metric Name Dimensions Semantics
ceph.cluster.total_bytes hostname, ceph_cluster, service=ceph Total capacity of the cluster in bytes
ceph.cluster.total_used_bytes hostname, ceph_cluster, service=ceph Capacity of the cluster currently in use in bytes
ceph.cluster.total_avail_bytes hostname, ceph_cluster, service=ceph Available space within the cluster in bytes
ceph.cluster.objects.total_count hostname, ceph_cluster, service=ceph No. of rados objects within the cluster
ceph.cluster.utilization_perc hostname, ceph_cluster, service=ceph Percentage of available storage on the cluster
ceph.cluster.health_status hostname, ceph_cluster, service=ceph Health status of cluster, can vary between 3 states (err:2, warn:1, ok:0)
ceph.cluster.osds.down_count hostname, ceph_cluster, service=ceph Number of OSDs that are in DOWN state
ceph.cluster.osds.out_count hostname, ceph_cluster, service=ceph Number of OSDs that are in OUT state
ceph.cluster.osds.up_count hostname, ceph_cluster, service=ceph Number of OSDs that are in UP state
ceph.cluster.osds.in_count hostname, ceph_cluster, service=ceph Number of OSDs that are in IN state
ceph.cluster.osds.total_count hostname, ceph_cluster, service=ceph Total number of OSDs in the cluster
ceph.cluster.objects.degraded_count hostname, ceph_cluster, service=ceph Number of degraded objects across all PGs, includes replicas
ceph.cluster.objects.misplaced_count hostname, ceph_cluster, service=ceph Number of misplaced objects across all PGs, includes replicas
ceph.cluster.pgs.avg_per_osd hostname, ceph_cluster, service=ceph Average number of PGs per OSD in the cluster
ceph.cluster.pgs.total_count hostname, ceph_cluster, service=ceph Total no. of PGs in the cluster
ceph.cluster.pgs.scrubbing_count hostname, ceph_cluster, service=ceph Number of scrubbing PGs in the cluster
ceph.cluster.pgs.deep_scrubbing_count hostname, ceph_cluster, service=ceph Number of deep scrubbing PGs in the cluster
ceph.cluster.pgs.degraded_count hostname, ceph_cluster, service=ceph Number of PGs in a degraded state
ceph.cluster.pgs.stuck_degraded_count hostname, ceph_cluster, service=ceph No. of PGs stuck in a degraded state
ceph.cluster.pgs.unclean_count hostname, ceph_cluster, service=ceph Number of PGs in an unclean state
ceph.cluster.pgs.stuck_unclean_count hostname, ceph_cluster, service=ceph Number of PGs stuck in an unclean state
ceph.cluster.pgs.undersized_count hostname, ceph_cluster, service=ceph Number of undersized PGs in the cluster
ceph.cluster.pgs.stuck_undersized_count hostname, ceph_cluster, service=ceph Number of stuck undersized PGs in the cluster
ceph.cluster.pgs.stale_count hostname, ceph_cluster, service=ceph Number of stale PGs in the cluster
ceph.cluster.pgs.stuck_stale_count hostname, ceph_cluster, service=ceph Number of stuck stale PGs in the cluster
ceph.cluster.pgs.remapped_count hostname, ceph_cluster, service=ceph Number of PGs that are remapped and incurring cluster-wide movement
ceph.cluster.recovery.bytes_per_sec hostname, ceph_cluster, service=ceph Rate of bytes being recovered in cluster per second
ceph.cluster.recovery.keys_per_sec hostname, ceph_cluster, service=ceph Rate of keys being recovered in cluster per second
ceph.cluster.recovery.objects_per_sec hostname, ceph_cluster, service=ceph Rate of objects being recovered in cluster per second
ceph.cluster.client.read_bytes_per_sec hostname, ceph_cluster, service=ceph Rate of bytes being read by all clients per second
ceph.cluster.client.write_bytes_per_sec hostname, ceph_cluster, service=ceph Rate of bytes being written by all clients per second
ceph.cluster.client.read_ops hostname, ceph_cluster, service=ceph Total client read I/O ops on the cluster measured per second
ceph.cluster.client.write_ops hostname, ceph_cluster, service=ceph Total client write I/O ops on the cluster measured per second
ceph.cluster.cache.flush_bytes_per_sec hostname, ceph_cluster, service=ceph Rate of bytes being flushed from the cache pool per second
ceph.cluster.cache.evict_bytes_per_sec hostname, ceph_cluster, service=ceph Rate of bytes being evicted from the cache pool per second
ceph.cluster.cache.promote_ops hostname, ceph_cluster, service=ceph Total cache promote operations measured per second
ceph.cluster.slow_requests_count hostname, ceph_cluster, service=ceph Number of slow requests
ceph.cluster.quorum_size hostname, ceph_cluster, service=ceph Number of monitors in quorum
ceph.monitor.total_bytes hostname, ceph_cluster, monitor, service=ceph Total storage capacity of the monitor node
ceph.monitor.used_bytes hostname, ceph_cluster, monitor, service=ceph Storage of the monitor node that is currently allocated for use
ceph.monitor.avail_bytes hostname, ceph_cluster, monitor, service=ceph Total unused storage capacity that the monitor node has left
ceph.monitor.avail_perc hostname, ceph_cluster, monitor, service=ceph Percentage of total unused storage capacity that the monitor node has left
ceph.monitor.store.total_bytes hostname, ceph_cluster, monitor, service=ceph Total capacity of the FileStore backing the monitor daemon
ceph.monitor.store.sst_bytes hostname, ceph_cluster, monitor, service=ceph Capacity of the FileStore used only for raw SSTs
ceph.monitor.store.log_bytes hostname, ceph_cluster, monitor, service=ceph Capacity of the FileStore used only for logging
ceph.monitor.store.misc_bytes hostname, ceph_cluster, monitor, service=ceph Capacity of the FileStore used only for storing miscellaneous information
ceph.monitor.skew hostname, ceph_cluster, monitor, service=ceph Monitor clock skew
ceph.monitor.latency hostname, ceph_cluster, monitor, service=ceph Monitor's latency
ceph.osd.crush_weight hostname, ceph_cluster, osd, service=ceph OSD crush weight
ceph.osd.depth hostname, ceph_cluster, osd, service=ceph OSD depth
ceph.osd.reweight hostname, ceph_cluster, osd, service=ceph OSD reweight
ceph.osd.total_bytes hostname, ceph_cluster, osd, service=ceph OSD total bytes
ceph.osd.used_bytes hostname, ceph_cluster, osd, service=ceph OSD used storage in bytes
ceph.osd.avail_bytes hostname, ceph_cluster, osd, service=ceph OSD available storage in bytes
ceph.osd.utilization_perc hostname, ceph_cluster, osd, service=ceph OSD utilization
ceph.osd.variance hostname, ceph_cluster, osd, service=ceph OSD variance
ceph.osd.pgs_count hostname, ceph_cluster, osd, service=ceph OSD placement group count
ceph.osd.perf.commit_latency_seconds hostname, ceph_cluster, osd, service=ceph OSD commit latency in seconds
ceph.osd.perf.apply_latency_seconds hostname, ceph_cluster, osd, service=ceph OSD apply latency in seconds
ceph.osd.up hostname, ceph_cluster, osd, service=ceph OSD up status (up: 1, down: 0)
ceph.osd.in hostname, ceph_cluster, osd, service=ceph OSD in status (in: 1, out: 0)
ceph.osds.total_bytes hostname, ceph_cluster, service=ceph OSDs total storage in bytes
ceph.osds.total_used_bytes hostname, ceph_cluster, service=ceph OSDs total used storage in bytes
ceph.osds.total_avail_bytes hostname, ceph_cluster, service=ceph OSDs total available storage in bytes
ceph.osds.avg_utilization_perc hostname, ceph_cluster, osd, service=ceph OSDs average utilization in percent
ceph.pool.used_bytes hostname, ceph_cluster, pool, service=ceph Capacity of the pool that is currently under use
ceph.pool.used_raw_bytes hostname, ceph_cluster, pool, service=ceph Raw capacity of the pool that is currently under use, this factors in the size
ceph.pool.max_avail_bytes hostname, ceph_cluster, pool, service=ceph Free space for this ceph pool
ceph.pool.objects_count hostname, ceph_cluster, pool, service=ceph Total no. of objects allocated within the pool
ceph.pool.dirty_objects_count hostname, ceph_cluster, pool, service=ceph Total no. of dirty objects in a cache-tier pool
ceph.pool.read_io hostname, ceph_cluster, pool, service=ceph Total read i/o calls for the pool
ceph.pool.read_bytes hostname, ceph_cluster, pool, service=ceph Total read throughput for the pool
ceph.pool.write_io hostname, ceph_cluster, pool, service=ceph Total write i/o calls for the pool
ceph.pool.write hostname, ceph_cluster, pool, service=ceph Total write throughput for the pool
ceph.pool.quota_max_bytes hostname, ceph_cluster, pool, service=ceph Quota maximum bytes for the pool
ceph.pool.quota_max_objects hostname, ceph_cluster, pool, service=ceph Quota maximum objects for the pool
ceph.pool.total_bytes hostname, ceph_cluster, pool, service=ceph Total capacity of the pool in bytes
ceph.pool.utilization_perc hostname, ceph_cluster, pool, service=ceph Percentage of used storage for the pool
ceph.pool.client.read_bytes_sec hostname, ceph_cluster, pool, service=ceph Read bytes per second on the pool
ceph.pool.client.write_bytes_sec hostname, ceph_cluster, pool, service=ceph Write bytes per second on the pool
ceph.pool.client.read_ops hostname, ceph_cluster, pool, service=ceph Read operations per second on the pool
ceph.pool.client.write_ops hostname, ceph_cluster, pool, service=ceph Write operations per second on the pool
ceph.pool.recovery.objects_per_sec hostname, ceph_cluster, pool, service=ceph Objects recovered per second on the pool
ceph.pool.recovery.bytes_per_sec hostname, ceph_cluster, pool, service=ceph Bytes recovered per second on the pool
ceph.pool.recovery.keys_per_sec hostname, ceph_cluster, pool, service=ceph Keys recovered per second on the pool
ceph.pool.recovery.objects hostname, ceph_cluster, pool, service=ceph Objects recovered on the pool
ceph.pool.recovery.bytes hostname, ceph_cluster, pool, service=ceph Bytes recovered on the pool
ceph.pool.recovery.keys hostname, ceph_cluster, pool, service=ceph Keys recovered on the pool
ceph.pools.count hostname, ceph_cluster, service=ceph Number of pools on the cluster

Certificate Expiration (HTTPS)

An extension to the Agent provides the ability to determine the expiration date of the certificate for the URL. The metric is days until the certificate expires

default dimensions: url: url

A YAML file (cert_check.yaml) contains the list of urls to check. It also contains

The configuration of the certificate expiration check is done in YAML, and consists of two keys:

  • init_config
  • instances

The init_config section lists the global configuration settings, such as the Certificate Authority Certificate file, the ciphers to use, the period at which to output the metric and the url connection timeout (in seconds, floating-point number)

$ ls -l `which ping` -rwsr-xr-x 1 root root 35712 Nov 8 2011 /bin/ping
init_config:
  ca_certs: /etc/ssl/certs/ca-certificates.crt
  ciphers: HIGH:-aNULL:-eNULL:-PSK:RC4-SHA:RC4-MD5
  collect_period: 3600
  timeout: 1.0

The instances section contains the urls to check.

instances:
- built_by: CertificateCheck
  url: https://somehost.somedomain.net:8333
- built_by: CertificateCheck
  url: https://somehost.somedomain.net:9696

The certicate expiration checks return the following metrics

Metric Name Dimensions Semantics
https.cert_expire_days url=supplied url being checked The number of days until the certificate expires

There is a detection plugin that should be used to configure this extension. It is invoked as:

$ monasca-setup -d CertificateCheck -a urls=https://somehost.somedomain.net:8333,https://somehost.somedomain.net:9696

The urls option is a comma separated list of urls to check.

These options can be set if desired:

  • ca_certs: file containing the certificates for Certificate Authorities. The default is /etc/ssl/certs/ca-certificates.crt
  • ciphers: list of ciphers to use. default is HIGH:-aNULL:-eNULL:-PSK:RC4-SHA:RC4-MD5
  • collect_period: Integer time in seconds between outputting the metric. Since the metric is in days, it makes sense to output it at a slower rate. The default is 3600, once per hour
  • timeout: Float time in seconds before timing out the connect to the url. Increase if needed for very slow servers, but making this too long will increase the time this plugin takes to run if the server for the url is down. The default is 1.0 seconds

Congestion

This section describes the congestion check performed by monasca-agent. Congestion check collects metrics from special iptable chain created by the agent called congestion. Metric names that are cross-posted to the infrastructure project will have the ecn. prefix.

Configuration

The congestion check requires a configuration file called congestion.yaml to be available in the agent conf.d configuration directory. An example of the configuration is given below.

auth_url is the keystone endpoint for authentication.

cache_dir will be used to cache ecn metrics in a file called congestion_status.json.

enable_ecn optional method that activates ecn marking in each machine. When the transmission equipment in the network encounters a congestion in its queues, it will not mark packets until the ecn is enabled by the sender. enable_ecn method ensures that ecn marking is enabled for both the sender and the receiver. This method is optional because the end user could enable ecn by changing the value of tcp_ecn from 0 to 2 or running 'echo 2 > /proc/sys/net/ipv4/tcp_ecn' in each machine.

enable_vm optional method that gathers ecn metrics ecn.packets, ecn.bytes, and ecn.cong.rate of each VM hosted in a remote compute. By default the agent collects ecn metrics of computes, activating this method add fine-grained control of the congestion.

s_factor Smoothing factor used to compute ecn congestion rate.

collect_period Period of time in sec to collect metrics and used also in ecn congestion rate calculation.

password is the password for the nova user.

project_name is the project/tenant to POST ecn metrics.

region_name is used to add the region dimension to metrics.

username is the username capable of making administrative nova calls.

instances are not used and should be empty in congestion.yaml because the plugin runs against all computes.

Sample config (congestion.yaml):

---
init_config:
  auth_url: http://10.10.10.10/identity_admin
  cache_dir: /dev/shm
  enable_ecn: true
  enable_vm: true
  password: admin
  project_name: service
  region_name: RegionOne
  username: nova
  collect_period: 30
  s_factor = 0.1

instances:
 - {}

The congestion checks return the following metrics:

Metric Name Dimensions Semantics
ecn.packets hostname, device, component=neutron, service=networking Number of packets marked as Congestion Experienced
ecn.bytes hostname, device, component=neutron, service=networking Number of bytes marked as Congestion Experienced
ecn.cong.rate hostname, device, component=neutron, service=networking Congestion rate in kbps calculated using ecn.bytes value

There is a detection plugin that should be used to configure this plugin. It is invoked as:

$ monasca-setup -d congestion

You can check the current congestion status of the network by simply running:

$ sudo monasca-collector -v check congestion

Couch

See the example configuration for how to configure the Couch plugin.

Couchbase

See the example configuration for how to configure the Couchbase plugin.

Crash

Overview

The crash plugin provides metrics for crash dumps present on the system. Currently, it only returns the number of crash dumps found plus the date-/timestamp of the most recent crash in a value_meta dictionary.

Metrics

Only one metric is provided at the moment with a hostname dimension.

Name Description value_meta
crash.dump_count Number of crash dumps found {'latest': u'<date-/timestamp>'}

Configuration

The monasca-setup program will configure the Crash plugin if a crash kernel is loaded. The default directory where the plugin will look for crash dumps is /var/crash.

Sample config:

init_config:
  crash_dir: /var/crash

instances:
  - name: crash_stats

Directory Checks

This section describes the directory check that can be performed by the Agent. Directory checks are used for gathering the total size of all the files under a specific directory. A YAML file (directory.yaml) contains the list of directory names to check. A Python script (directory.py) runs checks each host in turn to gather stats. Note: for sparse file, directory check is using its resident size instead of the actual size.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. The former is not used by directory check, while the later contains one or more sets of directory names to check on. Directory check will sum the size of all the files under the given directory recursively.

Sample config:

init_config: null
instances:
- built_by: Directory
  directory: /var/log/monasca/agent
- built_by: Directory
  directory: /etc/monasca/agent

The directory checks return the following metrics:

Metric Name Dimensions
directory.size_bytes path, hostname, service
directory.files_count path, hostname, service

Docker

This plugin gathers metrics on docker containers.

A YAML file (docker.yaml) contains the url of the docker api to connect to and the root of docker that is used for looking for docker proc metrics.

For this check the user that is running the monasca agent (usually the mon-agent user) must be a part of the docker group

Also if you want to want to attach kubernetes dimensions to each metric you can set add_kubernetes_dimensions to true in the yaml file. This will set the pod_name and namespace.

Sample config:

Without kubernetes dimensions

init_config:
  docker_root: /
  socket_timeout: 5
instances:
  - url: "unix://var/run/docker.sock"

With kubernetes dimensions

init_config:
  docker_root: /
  socket_timeout: 5
instances:
  - url: "unix://var/run/docker.sock"
    add_kubernetes_dimensions: True

Note this plugin only supports one instance in the config file.

The docker check return the following metrics:

Metric Name Metric Type Dimensions Optional_dimensions (set if add_kubernetes_dimensions is true and container is running under kubernetes) Semantics
container.containers.running_count Gauge hostname Number of containers running on the host
container.cpu.system_time Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The total time the CPU has executed system calls on behalf of the processes in the container
container.cpu.system_time_sec Rate hostname, name, image kubernetes_pod_name, kubernetes_namespace The rate the CPU is executing system calls on behalf of the processes in the container
container.cpu.user_time Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The total time the CPU is under direct control of the processes in this container
container.cpu.user_time_sec Rate hostname, name, image kubernetes_pod_name, kubernetes_namespace The rate the CPU is under direct control of the processes in this container
container.cpu.utilization_perc Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The percentage of CPU used by the container
container.io.read_bytes Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The total amount bytes read from the processes in the container
container.io.read_bytes_sec Rate hostname, name, image kubernetes_pod_name, kubernetes_namespace The rate of bytes read from the processes in the container
container.io.write_bytes Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The total amount bytes written from the processes in the container
container.io.write_bytes_sec Rate hostname, name, image kubernetes_pod_name, kubernetes_namespace The rate of bytes written from the processes in the container
container.mem.cache Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The amount of cached memory that belongs to the container's processes
container.mem.rss Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The amount of non-cached memory used by the container's processes
container.mem.swap Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The amount of swap memory used by the processes in the container
container.mem.used_perc Gauge hostname, name, image kubernetes_pod_name, kubernetes_namespace The percentage of memory used out of the given limit of the container
container.net.in_bytes Gauge hostname, name, image, interface kubernetes_pod_name, kubernetes_namespace The total amount of bytes received by the container per interface
container.net.in_bytes_sec Rate hostname, name, image, interface kubernetes_pod_name, kubernetes_namespace The rate of bytes received by the container per interface
container.net.out_bytes Gauge hostname, name, image, interface kubernetes_pod_name, kubernetes_namespace The total amount of bytes sent by the container per interface
container.net.out_bytes_sec Rate hostname, name, image, interface kubernetes_pod_name, kubernetes_namespace The rate of bytes sent by the container per interface

Elasticsearch Checks

This section describes the Elasticsearch check that can be performed by the Agent. The Elasticsearch check requires a configuration file called elastic.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:
instances:
-   url: http://127.0.0.1:9200

The Elasticsearch checks return the following metrics:

Metric Name Dimensions Semantics
elasticsearch.docs.count url, hostname, service=monitoring The total number of docs including nested documents.
elasticsearch.docs.deleted url, hostname, service=monitoring The number of deleted docs.
elasticsearch.store.size url, hostname, service=monitoring The filesystem storage size.
elasticsearch.indexing.index.total url, hostname, service=monitoring
elasticsearch.indexing.index.time url, hostname, service=monitoring
elasticsearch.indexing.index.current url, hostname, service=monitoring
elasticsearch.indexing.delete.total url, hostname, service=monitoring
elasticsearch.indexing.delete.time url, hostname, service=monitoring
elasticsearch.indexing.delete.current url, hostname, service=monitoring
elasticsearch.get.total url, hostname, service=monitoring
elasticsearch.get.time url, hostname, service=monitoring
elasticsearch.get.current url, hostname, service=monitoring
elasticsearch.get.exists.total url, hostname, service=monitoring
elasticsearch.get.exists.time url, hostname, service=monitoring
elasticsearch.get.missing.total url, hostname, service=monitoring
elasticsearch.get.missing.time url, hostname, service=monitoring
elasticsearch.search.query.total url, hostname, service=monitoring
elasticsearch.search.query.time url, hostname, service=monitoring
elasticsearch.search.query.current url, hostname, service=monitoring
elasticsearch.search.fetch.total url, hostname, service=monitoring
elasticsearch.search.fetch.time url, hostname, service=monitoring
elasticsearch.search.fetch.current url, hostname, service=monitoring
elasticsearch.merges.current url, hostname, service=monitoring
elasticsearch.merges.current.docs url, hostname, service=monitoring
elasticsearch.merges.current.size url, hostname, service=monitoring
elasticsearch.merges.total url, hostname, service=monitoring
elasticsearch.merges.total.time url, hostname, service=monitoring
elasticsearch.merges.total.docs url, hostname, service=monitoring
elasticsearch.merges.total.size url, hostname, service=monitoring
elasticsearch.refresh.total url, hostname, service=monitoring
elasticsearch.refresh.total.time url, hostname, service=monitoring
elasticsearch.flush.total url, hostname, service=monitoring
elasticsearch.flush.total.time url, hostname, service=monitoring The elasticsearch flush time.
elasticsearch.process.open_fd url, hostname, service=monitoring The number of open files descriptors on the machine.
elasticsearch.transport.rx_count url, hostname, service=monitoring
elasticsearch.transport.tx_count url, hostname, service=monitoring
elasticsearch.transport.rx_size url, hostname, service=monitoring
elasticsearch.transport.tx_size url, hostname, service=monitoring
elasticsearch.transport.server_open url, hostname, service=monitoring
elasticsearch.thread_pool.bulk.active url, hostname, service=monitoring The number of active threads for bulk operations.
elasticsearch.thread_pool.bulk.threads url, hostname, service=monitoring The total number of threads for bulk operations.
elasticsearch.thread_pool.bulk.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for bulk operations.
elasticsearch.thread_pool.bulk.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for bulk operations.
elasticsearch.thread_pool.flush.active url, hostname, service=monitoring The number of active threads for flush operations.
elasticsearch.thread_pool.flush.threads url, hostname, service=monitoring The total number of threads for flush operations.
elasticsearch.thread_pool.flush.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for flush operations.
elasticsearch.thread_pool.flush.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for flush operations.
elasticsearch.thread_pool.generic.active url, hostname, service=monitoring The number of active threads for generic operations (i.e. node discovery).
elasticsearch.thread_pool.generic.threads url, hostname, service=monitoring The total number of threads for generic operations (i.e. node discovery).
elasticsearch.thread_pool.generic.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for generic operations.
elasticsearch.thread_pool.generic.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for generic operations.
elasticsearch.thread_pool.get.active url, hostname, service=monitoring The number of active threads for get operations.
elasticsearch.thread_pool.get.threads url, hostname, service=monitoring The total number of threads for get operations.
elasticsearch.thread_pool.get.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for get operations.
elasticsearch.thread_pool.get.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for get operations.
elasticsearch.thread_pool.index.active url, hostname, service=monitoring The number of active threads for indexing operations.
elasticsearch.thread_pool.index.threads url, hostname, service=monitoring The total number of threads for indexing operations.
elasticsearch.thread_pool.index.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for indexing operations.
elasticsearch.thread_pool.index.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for indexing operations.
elasticsearch.thread_pool.management.active url, hostname, service=monitoring The number of active threads for management operations.
elasticsearch.thread_pool.management.threads url, hostname, service=monitoring The total number of threads for management operations.
elasticsearch.thread_pool.management.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for management operations.
elasticsearch.thread_pool.management.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for management operations.
elasticsearch.thread_pool.merge.active url, hostname, service=monitoring The number of active threads for merging operation.
elasticsearch.thread_pool.merge.threads url, hostname, service=monitoring The total number of threads for merging operation.
elasticsearch.thread_pool.merge.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for merge operations.
elasticsearch.thread_pool.merge.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for merge operations.
elasticsearch.thread_pool.percolate.active url, hostname, service=monitoring The number of active threads for percolate operations.
elasticsearch.thread_pool.percolate.threads url, hostname, service=monitoring The total number of threads for percolate operations.
elasticsearch.thread_pool.percolate.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for percolate operations.
elasticsearch.thread_pool.percolate.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for percolate operations.
elasticsearch.thread_pool.refresh.active url, hostname, service=monitoring The number of active threads for refresh operations.
elasticsearch.thread_pool.refresh.threads url, hostname, service=monitoring The total number of threads for refresh operations.
elasticsearch.thread_pool.refresh.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for refresh operations.
elasticsearch.thread_pool.refresh.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for refresh operations.
elasticsearch.thread_pool.search.active url, hostname, service=monitoring The number of active threads for search operations.
elasticsearch.thread_pool.search.threads url, hostname, service=monitoring The total number of threads for search operations.
elasticsearch.thread_pool.search.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for search operations.
elasticsearch.thread_pool.search.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for search operations.
elasticsearch.thread_pool.snapshot.active url, hostname, service=monitoring The number of active threads for snapshot operations.
elasticsearch.thread_pool.snapshot.threads url, hostname, service=monitoring The total number of threads for snapshot operations.
elasticsearch.thread_pool.snapshot.queue url, hostname, service=monitoring The number of tasks in queue of thread pool used for snapshot operations.
elasticsearch.thread_pool.snapshot.rejected url, hostname, service=monitoring The number of rejected tasks of thread pool used for snapshot operations.
elasticsearch.http.current_open url, hostname, service=monitoring Current number of opened HTTP connections.
elasticsearch.http.total_opened url, hostname, service=monitoring Max number of HTTP connections.
jvm.gc.concurrent_mark_sweep.count url, hostname, service=monitoring
jvm.gc.concurrent_mark_sweep.collection_time url, hostname, service=monitoring
jvm.gc.par_new.count url, hostname, service=monitoring ParNew count.
jvm.gc.par_new.collection_time url, hostname, service=monitoring ParNew pauses time.
jvm.mem.heap_committed url, hostname, service=monitoring The allocated amount of heap memory.
jvm.mem.heap_used url, hostname, service=monitoring The amount of heap memory which is actually in use.
jvm.mem.non_heap_committed url, hostname, service=monitoring The allocated amount of non-heap memory.
jvm.mem.non_heap_used url, hostname, service=monitoring The amount of non-heap memory which is actually in use.
jvm.threads.count url, hostname, service=monitoring Current number of live daemon and non-daemon threads.
jvm.threads.peak_count url, hostname, service=monitoring Peak live thread count since the JVM started or the peak was reset.
elasticsearch.number_of_nodes url, hostname, service=monitoring Number of nodes.
elasticsearch.number_of_data_nodes url, hostname, service=monitoring Number of data nodes.
elasticsearch.active_primary_shards url, hostname, service=monitoring Indicates the number of primary shards in your cluster. This is an aggregate total across all indices.
elasticsearch.active_shards url, hostname, service=monitoring Aggregate total of all shards across all indices, which includes replica shards.
elasticsearch.relocating_shards url, hostname, service=monitoring Shows the number of shards that are currently moving from one node to another node.
elasticsearch.initializing_shards url, hostname, service=monitoring The count of shards that are being freshly created.
elasticsearch.unassigned_shards url, hostname, service=monitoring The number of unassigned shards from the master node.
elasticsearch.cluster_status url, hostname, service=monitoring Cluster health status.

Additional links

File Size

This section describes the file size check that can be performed by the Agent. File size checks are used for gathering the size of individual files or the size of each file under a specific directory. The agent supports additional functionality through the use of Python scripts. A YAML file (file_size.yaml) contains the list of file directory names and file names to check. A Python script (file_size.py) runs checks each host in turn to gather stats.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. The former is not used by file_size, while the later contains one or more sets of file directory name and file names to check, plus optional parameter recursive. When recursive is true and file_name is set to '*', file_size check will take all the files under the given directory recursively.

Sample config:

init_config: null
instances:
- built_by: FileSize
  directory_name: /var/log/monasca/agent/
  file_names:
  - '*'
  recursive: false
- built_by: FileSize
  directory_name: /var/log/monasca/api
  file_names:
  - monasca-api.log
  - request.log
  recursive: false
- built_by: FileSize
  directory_name: /var/log/monasca/notification
  file_names:
  - notification.log
  recursive: false

The file_size checks return the following metrics:

Metric Name Dimensions
file.size_bytes file_name, directory_name, hostname, service

GearmanD

See the example configuration for how to configure the GearmandD plugin.

Gunicorn

See the example configuration for how to configure the Gunicorn plugin.

HAProxy

See the example configuration for how to configure the HAProxy plugin.

HDFS

See the example configuration for how to configure the HDFS plugin.

Host Alive

An extension to the Agent can provide basic "aliveness" checks of other systems, verifying that the remote host (or device) is online. This check currently provides two methods of determining connectivity:

  • ping (ICMP)
  • SSH (banner test, port 22 by default)

Of the two, the SSH check provides a more comprehensive test of a remote system's availability, since it checks the banner returned by the remote host. A server in the throes of a kernel panic may still respond to ping requests, but would not return an SSH banner. It is suggested, therefore, that the SSH check be used instead of the ping check when possible.

A YAML file (host_alive.yaml) contains the list of remote hosts to check, including the host name and testing method (either 'ping' or 'ssh'). A Python script (host_alive.py) runs checks against each host in turn, returning a 0 on success and a 1 on failure in the result sent through the Forwarder and on the Monitoring API.

Because the Agent itself does not run as root, it relies on the system ping command being suid root in order to function.

The configuration of the host alive check is done in YAML, and consists of two keys:

  • init_config
  • instances

The init_config section lists the global configuration settings, such as SSH port, SSH connection timeout (in seconds, floating-point number), and ping timeout (in seconds, integer).

$ ls -l `which ping` -rwsr-xr-x 1 root root 35712 Nov 8 2011 /bin/ping
init_config:
    ssh_port: 22

    # ssh_timeout is a floating-point number of seconds
    ssh_timeout: 0.5

    # ping_timeout is an integer number of seconds
    ping_timeout: 1

The instances section contains the hostname/IP to check, and the type of check to perform, which is either ssh or ping.

    # alive_test can be either "ssh" for an SSH banner test (port 22)
    # or "ping" for an ICMP ping test instances:
  - name: ssh to somehost
    host_name: somehost.somedomain.net
    alive_test: ssh

  - name: ping gateway
    host_name: gateway.somedomain.net
    alive_test: ping

  - name: ssh to 192.168.0.221
    host_name: 192.168.0.221
    alive_test: ssh

To handle the case where the target system has multiple IP Addresses and the network name to be used for liveness checking is not the same as the usual name used to identify the server in Monasca, an additional target_hostname parameter can be configured. It is the network hostname or IP Address to check instead of host_name. The hostname dimension will always be set to the value of host_name even if target_hostname is specified. A dimension target_hostname will be added with the value of target_hostname if it is different from host_name.

To simplify configuring multiple checks, when the host_alive detection plugin is configured, hostname can be a comma separated list. Instances will be created for each value. target_hostname can also be a comma separated list, however, empty values for an individual entry can be given if there is no target_hostname for a given hostname entry.

Here is an example of configuring target_hostname :

  - name: ping somenode
    host_name: somenode
    target_hostname: somenode.mgmt.net
    alive_test: ssh

The host alive checks return the following metrics

Metric Name Dimensions Semantics
host_alive_status observer_host=fqdn of checking host, hostname=supplied hostname being checked, target_hostname=the network hostname or IP Address to check instead of host_name; only added if different than hostname, test_type=ping or ssh Status of remote host(device) is online or not. (0=online, 1=offline)

Also in the case of an error the value_meta contains an error message.

The default dimensions are: observer_host: fqdn hostname: fqdn | supplied target_hostname: Set to target_hostname only if that is different than host_name test_type: ping | ssh | Unrecognized alive_test

default value_meta error: error_message

HTTP (endpoint status)

This section describes the http endpoint check that can be performed by the Agent. Http endpoint checks are checks that perform simple up/down checks on services, such as HTTP/REST APIs. An agent, given a list of URLs, can dispatch an http request and report to the API success/failure as a metric.

default dimensions: url: endpoint

default value_meta error: error_message

The Agent supports additional functionality through the use of Python scripts. A YAML file (http_check.yaml) contains the list of URLs to check (among other optional parameters). A Python script (http_check.py) runs checks each host in turn, returning a 0 on success and a 1 on failure in the result sent through the Forwarder and on the Monitoring API.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. In the former, you can provide Keystone configuration for checks to retrieve token for authentication that will be used for all checks. While the later contains one or more URLs to check, plus optional parameters like a timeout, username/password, pattern to match against the HTTP response body, whether or not to include the HTTP response in the metric (as a 'detail' dimension), whether or not to also record the response time, and more. If the endpoint being checked requires authentication, there are two options. First, a username and password supplied in the instance options will be used by the check for authentication. Alternately, the check can retrieve a keystone token for authentication. Specific keystone information can be provided for all checks in init_config section, or if it's not provided there, the information from the agent config will be used. DEPRECATED: providing Keystone configuration in each instance.

Sample config:

init_config:
    keystone_config:
        keystone_url: http://endpoint.com/v3/
        project_name: project
        username: user
        password: password

instances:
    url: http://192.168.0.254/healthcheck
    timeout: 1
    include_content: true
    collect_response_time: true
    match_pattern: '.*OK.*OK.*OK.*OK.*OK'

The http_status checks return the following metrics:

Metric Name Dimensions Semantics
http_status url, detail The status of the http endpoint call (0 = success, 1 = failure)
http_response_time url The response time in seconds of the http endpoint call

HTTP Metrics

This section describes the http metrics check that can be performed by the agent. Http metrics checks are checks that retrieve metrics from any url returning a json formatted response. An agent, given a list of URLs, can dispatch an http request and parse the desired metrics from the json response.

default dimensions: url: endpoint

default value_meta error: error_message

Similar to other checks, the configuration is done in YAML (http_metrics.yaml), and consists of two keys: init_config and instances. The former is not used by http_metrics, while the later contains one or more URLs to check, plus optional parameters like a timeout, username/password, whether or not to also record the response time, and a whitelist of metrics to collect. The whitelist should consist of a name, path, and type for each metric to be collected. The name is what the metric will be called when it is reported. The path is a string of keys separated by '/' where the metric value resides in the json response. The type is how you want the metric to be recorded (gauge, counter, histogram, rate, set). A gauge will store and report the value it find with no modifications. A counter will increment itself by the value it finds. A histogram will store values and return the calculated max, median, average, count, and percentiles. A rate will return the difference between the last two recorded samples divided by the interval between those samples in seconds. A set will record samples and return the number of unique values in the set. If the endpoint being checked requires authentication, there are two options. First, a username and password supplied in the instance options will be used by the check for authentication. Alternately, the check can retrieve a keystone token for authentication. Specific keystone information can be provided for each check, otherwise the information from the agent config will be used.

init_config:

instances:
       url: http://192.168.0.254/metrics
       timeout: 1
       collect_response_time: true
       whitelist:
              name: jvm.memory.total.max,
              path: gauges/jvm.memory.total.max/value
              type: gauge

InfluxDB

Auto-detection for InfluxDB plugin comes with two checks enabled:

  • process monitoring with following configuration
{
    'detailed': True,
    'search_string': ['influxd'],
    'exact_match': False,
    'name': 'influxd',
    'dimensions': {
        'component': 'influxdb',
        'service': 'influxdb'
    }
}
  • http_check monitoring
{
    'name': 'influxdb',
    'url': 'http://127.0.0.1:8086/ping'
}
InfluxDB does expose internal metrics on its own, however
they are subject to extend influxdb auto-detection capabilities
in future

InfluxDB-Relay

InfluxDB-Relay does not expose any internal metrics on its own, however auto-detection plugin configures two checks on behalf of it:

  • process monitoring with following configuration
{
    'detailed': True,
    'search_string': ['influxdb-relay'],
    'exact_match': False,
    'name': 'influxdb-relay',
    'dimensions': {
        'component': 'influxdb-relay',
        'service': 'influxdb'
    }
}
  • http_check monitoring
{
    'name': 'influxdb-relay',
    'url': 'http://127.0.0.1:9096/ping'
}

IIS

See the example configuration for how to configure the IIS plugin.

Jenkins

See the example configuration for how to configure the Jenkins plugin.

JsonPlugin

This plugin allows you to report metrics by simply writing the metrics to a file. The plugin reads the file and sends the metrics to Monasca.

Simple Reporting

The simplest approach is to create a file in the /var/cache/monasca_json_plugin directory. The file should contain a list of metrics in JSON format as shown in the following example. The file must have a ".json" extension in the name.

Simple Example -- /var/cache/monasca_json_plugin/my-metrics-file.json:

[
   {"name": "metric1", "value": 10.1, "timestamp": 1475596165},
   {"name": "metric2", "value": 12.3, "timestamp": 1475596165}
]

In the above example, the "name", "value" and "timestamp" of each measurement is reported. The following keys are available:

Key Description
name Required. The name of the metric. The key "metric" may be used instead of "name".
value Required. The value of the measurement. This is a floating point number.
timestamp Optional (if replace_timestamps is true; see below); otherwise required. The time of the measurement. Uses UNIX time epoch value. Note: this is seconds, not mulliseconds, since the epoch.
dimensions Optional. Dimensions of the metric as a set of key/value pairs.
value_meta Optional. Value meta of the metric as a set of key/value pairs.

Writing and Locking the Metrics File

You should take an exclusive lock on the file while you write new metrics (this plugin takes a shared lock). You must close or flush the file after writing new data to make sure the data is written to the file.

Example of writing metrics file:

metric_data = [{"name": "metric1", "value": 10.1, "timestamp": time.time()}]
max_retries = 10
delay = 0.02
attempts = 0
with open('/var/cache/monasca_json_plugin/my-metrics-file.json', 'w') as fd:
    while True:
        attempts += 1
        try:
            fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
            break
        except IOError as err:
            if (err.errno not in [errno.EWOULDBLOCK, errno.EACCES] or
                    attempts > max_retries):
                raise
        time.sleep(delay * attempts)
    fd.write(json.dumps(metric_data))

Additional Directives

You can add additional directives to the JSON file as shown in the following example:

Additional Directives Example:

{
   "replace_timestamps": false,
   "stale_age": 300,
   "measurements": [
      {"name": "metric1", "value": 10.1, "timestamp": 1475596165, "dimensions": {"path": "/tmp"}},
      {"name": "metric2", "value": 12.3, "timestamp": 1475596165, "value_meta": {"msg": "hello world"}}
   ]
}

The additional directives are described in the following table. The directives are optional.

Directive Description
replace_timestamps If true, the timestamps are ignored. Instead, the timestamp of the measurement is set to the current time. Default is false.
stale_age The number of seconds after which metrics are considered stale. This stops measurements from a file that is not updating from being reported to Monasca. It defaults to 4 minutes.

The main purpose of the stale_age directive is to detect if the JSON file stops updating (e.g., due to a bug or system failure). See the description of the monasca.json_plugin.status metric below.

The main purpose of the replace_timestamps directive is where the mechanism to write the JSON file runs infrequently or erratically. Every time Monasca Agent runs, the metrics are reported with the current time -- whether or not the file is updated. In this mode, you do not need to supply a timestamp (in fact, any timestamp you include is ignored). Also the stale_age directive is also ignored.

Custom JSON file locations

To use the built-in /var/cache/monasca_json_plugin directory, your application must be able to create and write files to that directory. If this is not possible, you can write the JSON file(s) to a different file path. An example of this configuration is in the example configuration.

The Monasca Agent user must be able to read the files.

The monasca.json_plugin.status Metric

The plugin reports a metric called "monasca.json_plugin.status". A single metric is reported by the JSON plugin. If there are problems, you can examine the value_meta. It will contain a list of problem paths/messages. You to create an alarm to trigger if there is a problem processing any JSON file.

The monasca.json_plugin.status metric has the following information:

Field Description
name "monasca.json_plugin.status" -- the name of the metric
value A value of 0.0 is normal -- there are no issues processing all JSON files. A value of 1.0 indicates there is a problem.
value_meta Value meta is only present when the value is 1.0. The value meta contains a "msg" key indicating the problem.

The value_meta/msg reports problems such as:

  • Failure to open the JSON file
  • Invalid JSON syntax
  • That metrics are older than the stale_age

Kafka Checks

This section describes the Kafka check that can be performed by the Agent. The Kafka check requires a configuration file called kafka_consumer.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
- built_by: Kafka
  consumer_groups:
    1_metrics:
      metrics: []
    thresh-event:
      events: []
    thresh-metric:
      metrics: []
  kafka_connect_str: 192.168.10.6:9092
  name: 192.168.10.6:9092
  per_partition: false

The Kafka checks return the following metrics:

Metric Name Dimensions Semantics
kafka.broker_offset topic, service, component, partition, hostname broker offset
kafka.consumer_offset topic, service, component, partition, consumer_group, hostname consumer offset
kafka.consumer_lag topic, service, component, partition, consumer_group, hostname consumer offset lag from broker offset

Kubernetes

This plugin collects metrics about containers (optionally) and pods on a kubernetes node.

The plugin collects metrics on a kubernetes node by going to the kubelet on the node to get all pod data. Included in that is containers configured under each pod and metadata about each.

It then goes to cAdvisor to get all docker container metrics and metadata associated with it. The plugin then does a comparison of the containers collected from cAdvisor and the containers defined from the kubelet.

If a container is defined to be apart of a pod it will take the metadata from the kubelet as dimensions (so it can get all of the kuberenetes associated tags), if it is not apart of a pod it will set the dimensions from the cAdvisor metadata.

When setting the kubernetes configuration there is a parameter "kubernetes_labels" where it will look for kubernetes tags that are user defined to use as dimensions for pod/container metrics. By default it will look for the label 'app'.

For each pod that we detect we will also aggregate container metrics that belong to that pod to output pod level metrics.

The kubernetes node that the plugin will connect to can be configured in two different ways. The first being setting the host variable in the instance. The other being setting the derive_host to True under the instance. We derive the host by first using the kubernetes environment variables to get the api url (assuming we are running in a kubernetes container). Next we use the container's pod name and namespace (passed in as environment variables to the agents container - see kubernetes example yaml file) with the api url to hit the api to get the pods metadata including the host it is running on. That is the host we use.

If derive_host is set to true the plugin will also hit the API when the owner of a Kubernetes pod is a replicaset (taken from the kubelet) to see if it is under a deployment.

Also by default we will not report the container metrics due to throughput it generates. If you want the container metrics you can set the configuration parameter "report_container_metrics" to True.

Sample configs:

Without custom labels and host being manually set:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    # Set to the host that the plugin will use when connecting to cAdvisor/kubelet
    - host: "127.0.0.1"
      cadvisor_port: 4194
      kublet_port: 10255

With custom labels and host being manually set:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    # Set to the host that the plugin will use when connecting to cAdvisor/kubelet
    - host: "127.0.0.1"
      cadvisor_port: 4194
      kublet_port: 10255
      kubernetes_labels: ['k8s-app', 'version']

With custom labels and derive host being set:

instances:
    # Set to the host that the plugin will use when connecting to the Kubernetes API
    - host: "127.0.0.1"
      kubernetes_api_port: 8080
      kubernetes_labels: ['k8s-app', 'version']

With custom labels and derive api url set to True:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    - derive_host: True
      cadvisor_port: 4194
      kublet_port: 10255
      kubernetes_labels: ['k8s-app', 'version']

Note this plugin only supports one instance in the config file.

The kubernetes check returns the following metrics (note that for containers running under kubernetes and pod metrics can also have dimensions set from the configuration option 'kubernetes_labels' which by default will include 'app')

Note the container metrics will only be reported when the report_container_metrics is True with the exception of container.mem.usage_percent which will be reported based on the flag report_container_mem_percent.

Common Container metrics between containers running underneath kubernetes and standalone:

Metric Name Dimensions if owned by a kubernetes pod Dimensions if running standalone from kubernetes Semantics
container.cpu.system_time image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Cumulative system CPU time consumed in core seconds
container.cpu.system_time_sec image, container_name, pod_name, namespace, unit image, container_name, hostname Rate of system CPU time consumed in core seconds
container.cpu.total_time image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Cumulative CPU time consumed in core seconds
container.cpu.total_time_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Rate of CPU time consumed in core seconds
container.cpu.user_time image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Cumulative user cpu time consumed in core seconds
container.cpu.user_time_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Rate of user CPU time consumed in core seconds
container.fs.total_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of bytes available
container.fs.usage_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of bytes consumed
container.fs.writes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Cumulative number of completed writes
container.fs.writes_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of completed writes per a second
container.fs.reads image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Cumulative number of completed reads
container.fs.reads_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of completed reads per a second
container.fs.io_current image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of i/o operations in progress
container.mem.cache_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of bytes of page cache memory
container.mem.rss_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Size of rss in bytes
container.mem.swap_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Swap usage in memory in bytes
container.mem.used_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Current memory in use in bytes
container.mem.working_set_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Current working set memory in bytes (total minus cache)
container.mem.fail_count image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of memory usage limit hits
container.net.in_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network bytes received
container.net.in_bytes_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network bytes received per second
container.net.in_dropped_packets image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total inbound network packets dropped
container.net.in_dropped_packets_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of inbound network packets dropped per second
container.net.in_errors image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network errors on incoming network traffic
container.net.in_errors_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network errors on incoming network traffic per second
container.net.in_packets image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network packets received
container.net.in_packets_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network packets received per second
container.net.out_bytes image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network bytes sent
container.net.out_bytes_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network bytes sent per second
container.net.out_dropped_packets image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total outbound network packets dropped
container.net.out_dropped_packets_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of outbound network packets dropped per second
container.net.out_errors image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network errors on outgoing network traffic
container.net.out_errors_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network errors on outgoing network traffic per second
container.net.out_packets image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Total network packets sent
container.net.out_packets_sec image, container_name, pod_name, namespace, unit image, container_name, hostname, unit Number of network packets sent per second

Container metrics specific to containers running under kubernetes:

Metric Name Dimensions Semantics
container.ready_status image, name, pod_name, namespace Ready status of the container defined by the ready probe
container.restart_count image, name, pod_name, namespace Restart count of the container
container.cpu.limit image, name, pod_name, namespace Limit in CPU cores for the container
container.memory.limit_bytes image, name, pod_name, namespace Limit of memory in bytes for the container
container.request.cpu image, name, pod_name, namespace Amount of CPU cores requested by the container
container.request.memory_bytes image, name, pod_name, namespace Amount of memory in bytes requested by the container
container.mem.usage_percent image, name, pod_name, namespace Percentage of memory used out of defined container limit.

Kubelet Metrics:

Metric Name Dimensions Semantics
kubelet.health_status hostname Health status of the kubelet api

Pod Metrics:

Metric Name Dimensions Semantics
pod.cpu.system_time pod_name, namespace Cumulative system CPU time consumed in core seconds
pod.cpu.system_time_sec pod_name, namespace Rate of system CPU time consumed in core seconds
pod.cpu.total_time pod_name, namespace Cumulative CPU time consumed in core seconds
pod.cpu.total_time_sec pod_name, namespace Rate of CPU time consumed in core seconds
pod.cpu.user_time pod_name, namespace Cumulative user cpu time consumed in core seconds
pod.cpu.user_time_sec pod_name, namespace Rate of user CPU time consumed in core seconds
pod.mem.cache_bytes pod_name, namespace Number of bytes of page cache memory
pod.mem.fail_count pod_name, namespace Number of memory usage limit hits
pod.mem.rss_bytes pod_name, namespace Size of rss in bytes
pod.mem.swap_bytes pod_name, namespace Swap usage in memory in bytes
pod.mem.used_bytes pod_name, namespace Current memory in use in bytes
pod.mem.working_set_bytes pod_name, namespace Current working set memory in bytes (total minus cache)
pod.net.in_bytes pod_name, namespace Total network bytes received
pod.net.in_bytes_sec pod_name, namespace Number of network bytes received per second
pod.net.in_dropped_packets pod_name, namespace Total inbound network packets dropped
pod.net.in_dropped_packets_sec pod_name, namespace Number of inbound network packets dropped per second
pod.net.in_errors pod_name, namespace Total network errors on incoming network traffic
pod.net.in_errors_sec pod_name, namespace Number of network errors on incoming network traffic per second
pod.net.in_packets pod_name, namespace Total network packets received
pod.net.in_packets_sec pod_name, namespace Number of network packets received per second
pod.net.out_bytes pod_name, namespace Total network bytes sent
pod.net.out_bytes_sec pod_name, namespace Number of network bytes sent per second
pod.net.out_dropped_packets pod_name, namespace Total outbound network packets dropped
pod.net.out_dropped_packets_sec pod_name, namespace Number of outbound network packets dropped per second
pod.net.out_errors pod_name, namespace Total network errors on outgoing network traffic
pod.net.out_errors_sec pod_name, namespace Number of network errors on outgoing network traffic per second
pod.net.out_packets pod_name, namespace Total network packets sent
pod.net.out_packets_sec pod_name, namespace Number of network packets sent per second
pod.restart_count pod_name, namespace Aggregated restart count of the pod's containers
pod.phase pod_name, namespace Current phase of the pod. See table below for mapping

There is also additional Kubernetes dimensions for the Container and Pod metrics depending on the owner for the pod:

Owner Dimension Name Notes
ReplicationController replication_controller
ReplicaSet replica_set
DaemonSet daemon_set
StatefulSet stateful_set
Deployment deployment Only will be set if derive_host is set to true as it needs to connect to the API to see if the ReplicaSet is under a deployment
Job job

Pod Phase Mapping:

Metric Value Phase
0 Succeeded
1 Running
2 Pending
3 Failed
4 Unknown

Kubernetes_API

This plugin collects metrics from the kubernetes api on kubernetes components, nodes, deployments and replication controllers.

When setting the kubernetes configuration there is a parameter "kubernetes_labels" where it will look for kubernetes tags that are user defined to use as dimensions for replication controller and deployment metrics.

There are two ways you can configure the plugin to connect to the kubernetes api. Either by setting the host and port or by setting the derive_api_url to True. If deriving the plugin sets the kubernetes api url by looking at the environment variables. (This should be used if the agent is running in a kubernetes container)

Sample configs:

instances:
    - derive api url: True
      kubernetes_labels: ['k8s-app', 'version']

Note this plugin only supports one instance in the config file.

Metrics (Note for replication controller and deployment metrics they can also have custom dimensions set from the configuration option 'kubernetes_labels')

Metric Name Dimensions Semantics
kubernetes.api.health_status Health status of the api
kubernetes.component_status component_name Status of cluster's components
kubernetes.node.out_of_disk hostname The node is out of disk
kubernetes.node.memory_pressure hostname Available memory on the node has satisfied an eviction threshold
kubernetes.node.disk_pressure hostname Available disk space and inodes on either the node’s root filesystem or image filesystem has satisfied an eviction threshold
kubernetes.node.ready_status hostname The ready status of the kubernetes node
kubernetes.node.allocatable.memory_bytes hostname, unit Total allocatable memory in bytes available for scheduling on the node
kubernetes.node.allocatable.cpu hostname, unit Total allocatable cpu cores available for scheduling on the node
kubernetes.node.allocatable.pods hostname Total allocatable pods available for scheduling on the node
kubernetes.node.capacity.memory_bytes hostname, unit Total memory on the node
kubernetes.node.capacity.cpu hostname, unit Total amount of cpu cores on the node
kubernetes.node.capacity.pods hostname Total amount of pods that could be run on the node
kubernetes.deployment.available_replicas deployment, namespace The number of available replicas for the deployment
kubernetes.deployment.replicas deployment, namespace The number of replicas for the deployment
kubernetes.deployment.unavailable_replicas deployment, namespace The number of unavailable replicas for the deployment
kubernetes.deployment.updated_replicas deployment, namespace The number of updated replicas for the deployment
kubernetes.replication.controller.ready_replicas replication_controller, namespace The number of ready replicas for the replication controller
kubernetes.replication.controller.replicas replication_controller, namespace The number of replicas for the replication controller

KyotoTycoon

See the example configuration for how to configure the KyotoTycoon plugin.

Libvirt VM Monitoring

Complete documentation of the Libvirt VM monitoring plugin can be found in the Libvirt.md document.

Open vSwitch Neutron Router Monitoring

Complete documentation of the Open vSwitch Neutron Router monitoring plugin can be found in the Ovs.md document.

Lighttpd

See the example configuration for how to configure the Lighttpd plugin.

LXC

An agent that provides LXC cgroup data. This agent does not require sudo.

Requirements:

  • lxc

Sample config:

init_config:

instances:
    - container: all
      cpu: True
      mem: True
      swap: True
      blkio: True
      net: True

The LXC checks return the following metrics:

Metric Name Dimensions Semantics
blkio.read hostname, container_name, service=lxc number of bytes read from the disk to the cgroup(container)
blkio.write hostname, container_name, service=lxc number of bytes written from the cgroup(container) to the disk
blkio.async hostname, container_name, service=lxc number of asynchronous bytes
blkio.sync hostname, container_name, service=lxc number of synchronous bytes
blkio.total hostname, container_name, service=lxc total number of bytes
cpuacct.usage hostname, container_name, service=lxc reports the total CPU time (in nanoseconds) consumed
cpuacct.usage_percpu.cpu{X} hostname, container_name, service=lxc reports the total CPU time (in nanoseconds) consumed by cpu X
cpuacct.user hostname, container_name, service=lxc CPU time consumed by tasks in user mode. Unit defined by the USER_HZ variable
cpuacct.system hostname, container_name, service=lxc CPU time consumed by tasks in kernel mode. Unit defined by the USER_HZ variable
memory.cache hostname, container_name, service=lxc page cache, including tmpfs (shmem), in bytes
memory.rss hostname, container_name, service=lxc anonymous and swap cache, not including tmpfs (shmem), in bytes
memory.mapped_file hostname, container_name, service=lxc size of memory-mapped mapped files, including tmpfs (shmem), in bytes
memory.pgpgin hostname, container_name, service=lxc number of pages paged into memory
memory.pgpgout hostname, container_name, service=lxc number of pages paged out of memory
memory.swap hostname, container_name, service=lxc swap usage in bytes
memory.active_anon hostname, container_name, service=lxc anonymous and swap cache on LRU list, in bytes
memory.inactive_anon hostname, container_name, service=lxc anonymous and swap cache on inactive LRU list, in bytes
memory.active_file hostname, container_name, service=lxc file-backed memory on active LRU list, in bytes
memory.inactive_file hostname, container_name, service=lxc file-backed memory on inactive LRU list, in bytes
memory.unevictable hostname, container_name, service=lxc memory that cannot be reclaimed, in bytes
memory.hierarchical_memory_limit hostname, container_name, service=lxc memory limit for the hierarchy that contains the memory cgroup, in bytes
memory.hierarchical_memsw_limit hostname, container_name, service=lxc memory plus swap limit for the hierarchy that contains the memory cgroup, in bytes
memory.usage_in_bytes hostname, container_name, service=lxc memory usage, in bytes
memory.memsw.usage_in_bytes hostname, container_name, service=lxc swap memory usage, in bytes
net.rx.bytes hostname, container_name, service=lxc, iface number of received bytes
net.rx.packets hostname, container_name, service=lxc, iface number of received packets
net.rx.errs hostname, container_name, service=lxc, iface number of received error packets
net.rx.drop hostname, container_name, service=lxc, iface number of received dropped packets
net.rx.fifo hostname, container_name, service=lxc, iface number of received fifo packets
net.rx.frame hostname, container_name, service=lxc, iface number of received frame packets
net.rx.compressed hostname, container_name, service=lxc, iface number of received compressed bytes
net.rx.multicast hostname, container_name, service=lxc, iface number of received multicast packets
net.tx.bytes hostname, container_name, service=lxc, iface number of transferred bytes
net.tx.packets hostname, container_name, service=lxc, iface number of transferred packets
net.tx.errs hostname, container_name, service=lxc, iface number of transferred error packets
net.tx.drop hostname, container_name, service=lxc, iface number of transferred dropped packets
net.tx.fifo hostname, container_name, service=lxc, iface number of transferred fifo packets
net.tx.frame hostname, container_name, service=lxc, iface number of transferred frame packets
net.tx.compressed hostname, container_name, service=lxc, iface number of transferred compressed bytes
net.tx.multicast hostname, container_name, service=lxc, iface number of transferred multicast packets
running_containers hostname, service=lxc number of running containers

Mcache

See the example configuration for how to configure the Mcache plugin.

MK Livestatus

MK Livestatus is a Nagios Event Broker, allowing access to Nagios host and service data through a socket query. The Monasca Agent mk_livestatus plugin is a way to access Nagios data and commit it to Monasca. Possible use cases of this plugin include:

  • A way to evaluate Monasca with identical metrics to Nagios, providing an apples-to-apples comparison
  • A gentle migration from Nagios to Monasca, where both monitoring processes can exist simultaneously during Nagios decommissioning
  • A turnkey solution for rapidly converting an existing Nagios installation to Monasca, where the Nagios infrastructure can remain indefinitely

The mk_livestatus plugin will be installed during monasca-setup if a Nagios/Icinga configuration is found, the MK Livestatus broker_module is installed, and the livestatus socket can be accessed. The monasca-agent user will need read access to the socket file in order to function, and a message to this effect will be included in monasca-setup output if the socket exists but monasca-agent cannot read it.

The configuration file (/etc/monasca/agent/conf.d/mk_livestatus.yaml by default) allows for a level of customization of both host and service checks.

  • Service checks
    • name - (Required) Monasca metric name to assign
    • check_type - (Required) "service" (as opposed to "host" below)
    • display_name - (Required) Name of the check as seen in Nagios
    • host_name - (Optional) Limit Monasca metrics of this check to the specified host name (as seen in Nagios).
    • dimensions - (Optional) Extra Monasca dimensions to include, in {'key': 'value'} format
  • Host checks
    • name - (Required) Monasca metric name to assign
    • check_type - (Required) "host" (as opposed to "service" above)
    • host_name - (Optional) Limit Monasca metrics of this check to the specified host name (as seen in Nagios).
    • dimensions - (Optional) Extra Monasca dimensions to include, in {'key': 'value'} format

If host_name is not specified, metrics for all hosts will be reported.

This configuration example shows several ways to specify instances:

init_config:
    # Specify the path to the mk_livestatus socket
    socket_path: /var/lib/icinga/rw/live

instances:

    # One service on one host
    - name:           nagios.check_http_status
      check_type:     service
      display_name:   HTTP
      host_name:      web01.example.net

    # One service on all hosts
    - name:           nagios.process_count_status
      check_type:     service
      display_name:   Total Processes

    # One service on all hosts with extra dimensions
    - name:           nagios.check_http_status
      check_type:     service
      display_name:   HTTP
      dimensions:     { 'group': 'webservers' }

    # All services on all hosts
    # These will be assigned metric names automatically, based on display_name
    - check_type:     service

    # One host
    - name:           nagios.host_status
      check_type:     host
      host_name:      web01.example.net

    # All hosts
    - name:           nagios.host_status
      check_type:     host

Mongo

See the example configuration for how to configure the Mongo plugin.

MySQL Checks

This section describes the mySQL check that can be performed by the Agent. The mySQL check also supports MariaDB. The mySQL check requires a configuration file called mysql.yaml to be available in the agent conf.d configuration directory.

Sample config: defaults_file: /root/.my.cnf

[client]
host=padawan-ccp-c1-m1-mgmt
user=root
password=pass
Note

Be assured that the password is set properly. As default monasca-agent expects password without quotation marks. Otherwise monasca-setup returns an error about inability to connect to MySQL with given password.

Instance variables can be passed via command line arguments to the monasca-setup -d mysql command. The instance config files are built by the detection plugin.

init_config:
Example clear connect:
instances:
- built_by: MySQL
  name: padawan-ccp-c1-m1-mgmt
  pass: secretpass
  port: 3306
  server: padawan-ccp-c1-m1-mgmt
  user: root

Example ssl connect:
instances:
- built_by: MySQL
  name: padawan-ccp-c1-m1-mgmt
  pass: secretpass
  port: 3306
  server: padawan-ccp-c1-m1-mgmt
  ssl_ca: /etc/ssl/certs/ca-certificates.crt
  user: root

Almost metrics show the server status variables in MySQL or MariaDB. The others are calculated by the server status variables of MySQL or MariaDB. For details of the server status variables, please refer the documents of MySQL or MariaDB. The mySQL checks return the following metrics:

Metric Name Dimensions Semantics
mysql.performance.questions hostname, mode, service=mysql Corresponding to "Question" of the server status variable.
mysql.performance.qcache_hits hostname, mode, service=mysql Corresponding to "Qcache_hits" of the server status variable.
mysql.performance.open_files hostname, mode, service=mysql Corresponding to "Open_files" of the server status variable.
mysql.performance.created_tmp_tables hostname, mode, service=mysql Corresponding to "Created_tmp_tables" of the server status variable.
mysql.performance.user_time hostname, mode, service=mysql The CPU user time for DB's performance, in seconds.
mysql.performance.com_replace_select hostname, mode, service=mysql Corresponding to "Com_replace_select" of the server status variable.
mysql.performance.kernel_time hostname, mode, service=mysql The kernel time for DB's performance, in seconds.
mysql.performance.com_insert hostname, mode, service=mysql Corresponding to "Com_insert" of the server status variable.
mysql.performance.threads_connected hostname, mode, service=mysql Corresponding to "Threads_connected" of the server status variable.
mysql.performance.com_update_multi hostname, mode, service=mysql Corresponding to "Com_update_multi" of the server status variable.
mysql.performance.table_locks_waited hostname, mode, service=mysql Corresponding to "Table_locks_waited" of the server status variable.
mysql.performance.com_insert_select hostname, mode, service=mysql Corresponding to "Com_insert_select" of the server status variable.
mysql.performance.slow_queries hostname, mode, service=mysql Corresponding to "Slow_queries" of the server status variable.
mysql.performance.com_delete hostname, mode, service=mysql Corresponding to "Com_delete" of the server status variable.
mysql.performance.com_select hostname, mode, service=mysql Corresponding to "Com_select" of the server status variable.
mysql.performance.queries hostname, mode, service=mysql Corresponding to "Queries" of the server status variable.
mysql.performance.created_tmp_files hostname, mode, service=mysql Corresponding to "Created_tmp_files" of the server status variable.
mysql.performance.com_update hostname, mode, service=mysql Corresponding to "Com_update" of the server status variable.
mysql.performance.com_delete_multi hostname, mode, service=mysql Corresponding to "Com_delete_multi" of the server status variable.
mysql.performance.created_tmp_disk_tables hostname, mode, service=mysql Corresponding to "Created_tmp_disk_tables" of the server status variable.
mysql.innodb.mutex_spin_rounds hostname, mode, service=mysql Corresponding to spinlock rounds of the server status variable.
mysql.innodb.current_row_locks hostname, mode, service=mysql Corresponding to current row locks of the server status variable.
mysql.innodb.mutex_os_waits hostname, mode, service=mysql Corresponding to the OS waits of the server status variable.
mysql.innodb.buffer_pool_used hostname, mode, service=mysql The number of used pages, in bytes. This value is calculated by subtracting "Innodb_buffer_pool_pages_total" away from "Innodb_buffer_pool_pages_free" of the server status variable.
mysql.innodb.data_writes hostname, mode, service=mysql Corresponding to "Innodb_data_writes" of the server status variable.
mysql.innodb.data_reads hostname, mode, service=mysql Corresponding to "Innodb_data_reads" of the server status variable.
mysql.innodb.row_lock_waits hostname, mode, service=mysql Corresponding to "Innodb_row_lock_waits" of the server status variable.
mysql.innodb.os_log_fsyncs hostname, mode, service=mysql Corresponding to "Innodb_os_log_fsyncs" of the server status variable.
mysql.innodb.buffer_pool_total hostname, mode, service=mysql The total size of buffer pool, in bytes. This value is calculated by multiplying "Innodb_buffer_pool_pages_total" and "Innodb_page_size" of the server status variable.
mysql.innodb.row_lock_time hostname, mode, service=mysql Corresponding to "Innodb_row_lock_time" of the server status variable.
mysql.innodb.mutex_spin_waits hostname, mode, service=mysql Corresponding to the spin waits of the server status variable.
mysql.innodb.buffer_pool_free hostname, mode, service=mysql The number of free pages, in bytes. This value is calculated by multiplying "Innodb_buffer_pool_pages_free" and "Innodb_page_size" of the server status variable.
mysql.net.max_connections hostname, mode, service=mysql Corresponding to "Max_used_connections" of the server status variable.
mysql.net.connections hostname, mode, service=mysql Corresponding to "Connections" of the server status variable.

Nagios Wrapper

The Agent can run Nagios plugins. A YAML file (nagios_wrapper.yaml) contains the list of Nagios checks to run, including the check name, command name with parameters, and desired interval between iterations. A Python script (nagios_wrapper.py) runs each command in turn, captures the resulting exit code (0 through 3, corresponding to OK, warning, critical and unknown), and sends that information to the Forwarder, which then sends the Monitoring API. Currently, the Agent can only send the exit code from a Nagios plugin. Any accompanying text is not sent.

default dimensions: observer_host: fqdn target_host: fqdn | supplied

default value_meta 0, 1, 2, 3, 4 OK, Warning, Critical, Unknown error: error_message

Similar to all plugins, the configuration is done in YAML, and consists of two keys: init_config and instances.

init_config contains global configuration options:

init_config:
  # Directories where Nagios checks (scripts, programs) may live
  check_path: /usr/lib/nagios/plugins:/usr/local/bin/nagios

  # Where to store last-run timestamps for each check
  temp_file_path: /dev/shm/

instances contains the list of checks to run

instances:
  - name: load
    check_command: check_load -r -w 2,1.5,1 -c 10,5,4

  - name: disk
    check_command: check_disk -w 15\% -c 5\% -A -i /srv/node
    check_interval: 300
  • 'name' value is the name of the metric

  • check_command is the full command to run. Specifying the full path is optional if the checks are located somewhere in check_path. These above examples are a copy-and-paste from existing service checks in /etc/cron.d/servicecheck-* files, so migration is fairly easy.

  • check_interval (optional) If unspecified, the checks will be run at the regular collector interval, which is 60 seconds by default. You may not want to run some checks that frequently, especially if they are resource-intensive, so check_interval lets you force a delay, in seconds, between iterations of that particular check. The state for these are stored in temp_file_path with file names like nagios_wrapper_19fe42bc7cfdc37a2d88684013e66c7b.pck where the hash is an md5sum of the 'name' value (to accommodate odd characters that the filesystem may not like).

Nginx

See the example configuration for how to configure the Nginx plugin.

NTP

This section describes the Network Time Protocol checks that can be performed by the Agent. The NTP checks monitors time offset between NTP server and your own server. The NTP checks requires a configuration file called ntp.yaml to be available in the agent conf.d configuration directory. The config file must contain the hostname and port number, version information, timeout(These are optional params) that you are interested in monitoring.

Sample config:

init_config:

instances:
  - host: pool.ntp.org
    port: ntp
    version: 3
    timeout: 5

The NTP checks return the following metrics:

Metric Name Dimensions Semantics
ntp.offset hostname, ntp_server Time offset in seconds
ntp.connection_status hostname, ntp_server Value of ntp server connection status (0=Healthy)

Postfix Checks

This section describes the Postfix checks that can be performed by the Agent. The Postfix checks gathers metrics on the Postfix. The Postfix checks requires a configuration file called postfix.yaml to be available in the agent conf.d configuration directory. The config file must contain the name, directory and queue that you are interested in monitoring.

NOTE: The user running monasca-agent must have passwordless sudo access for the find command to run the postfix check. Here's an example:

 example /etc/sudoers entry:
          monasca-agent ALL=(ALL) NOPASSWD:/usr/bin/find

Sample config:

init_config:

instances:
    - name: /var/spool/postfix
      directory: /var/spool/postfix
      queues:
          - incoming
          - active
          - deferred

The Postfix return the following metrics:

Metric Name Dimensions Semantics
postfix.queue_size queue A total number of queues

PostgreSQL

This section describes the PostgreSQL checks that can be performed by the Agent. The PostgreSQL checks requires a configuration file called postgres.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
   -   host: localhost
       port: 5432
       username: my_username
       password: my_password
       dbname: db_name

If you want to track per-relation (table), you need to add relations keys and specify the list.

       relations:
            - my_table
            - my_other_table

Each metrics show statistics collected in PostgreSQL. The PostgreSQL checks return the following metrics:

Metric Name Dimensions Semantics
postgresql.connections hostname, db, service=postgres Value of the "numbackends" of "pg_stat_database".
postgresql.commits hostname, db, service=postgres Value of the "xact_commit" of "pg_stat_database".
postgresql.rollbacks hostname, db, service=postgres Value of the "xact_rollback" of "pg_stat_database".
postgresql.disk_read hostname, db, service=postgres Value of the "blks_read" of "pg_stat_database".
postgresql.buffer_hit hostname, db, service=postgres Value of the "blks_hit" of "pg_stat_database".
postgresql.rows_returned hostname, db, service=postgres Value of the "tup_returned" of "pg_stat_database".
postgresql.rows_fetched hostname, db, service=postgres Value of the "tup_fetched" of "pg_stat_database".
postgresql.deadlocks hostname, db, service=postgres Value of the "deadlocks" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.temp_bytes hostname, db, service=postgres Value of the "temp_bytes" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.temp_files hostname, db, service=postgres Value of the "temp_files" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.seq_scans hostname, db, service=postgres, table Value of the "seq_scan" of "pg_stat_user_tables"
postgresql.seq_rows_read hostname, db, service=postgres, table Value of the "seq_tup_read" of "pg_stat_user_tables"
postgresql.index_scans hostname, db, service=postgres, table, index Value of the "idx_scan" of "pg_stat_user_tables" or "pg_stat_user_indexes"
postgresql.index_rows_fetched hostname, db, service=postgres, table, index Value of the "idx_tup_fetch" of "pg_stat_user_tables" or "pg_stat_user_indexes"
postgresql.rows_inserted hostname, db, service=postgres, table Value of the "n_tup_ins" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_updated hostname, db, service=postgres, table Value of the "n_tup_upd" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_deleted hostname, db, service=postgres, table Value of the "n_tup_del" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_hot_updated hostname, db, service=postgres, table Value of the "n_tup_hot_upd" of "pg_stat_user_tables"
postgresql.live_rows hostname, db, service=postgres, table Value of the "n_live_tup" of "pg_stat_user_tables"
postgresql.dead_rows hostname, db, service=postgres, table Value of the "n_dead_tup" of "pg_stat_user_tables"
postgresql.index_rows_read hostname, db, service=postgres, table, index Value of the "idx_tup_read" of "pg_stat_user_indexes"

Process Checks

Process checks can be performed to both verify that a set of named processes are running on the local system and collect/send system level metrics on those processes. The YAML file process.yaml contains the list of processes that are checked.

The processes that are monitored can be filtered using a pattern to specify the matching process names or distinctly identified by process name or by the username that owns the process.

A Python script process.py runs each execution cycle to check that required processes are alive. If the process is running a value of 0 is sent, otherwise a value of 1 is sent to the Monasca API.

Each process entry consists of one primary key: name. Either search_string or username must be set but you can not set both. Optionally, if an exact match on search_string is required the exact_match boolean can be added to the entry and set to True.

To grab more process metrics beside the process.pid_count, which only shows that the process is up and running, the configuration option detailed must be set to true.

Sample monasca-setup: Monitor by process_names:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_names":["monasca-notification","monasca-api"],"dimensions":{"service":"monitoring"}}]}'

Monitor by process_username:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_username":"dbadmin","dimensions":{"service":"monitoring","component":"vertica"}}]}'

Multiple entries in one call:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_names":["monasca-notification","monasca-api"],"dimensions":{"service":"monitoring"}},
                             {"process_names":["elasticsearch"],"dimensions":{"service":"logging"}},
                             {"process_username":"dbadmin","dimensions":{"service":"monitoring","component":"vertica"}}]}'

Using a yaml config file:

monasca-setup -d ProcessCheck -a "conf_file_path=/home/stack/myprocess.yaml"

Example yaml input file format for process check by process names:


process_config:
- process_names:
  - monasca-notification
  - monasca-api
  dimensions:
    service: monitoring

Example yaml input file format for multiple process_names entries:


process_config:
- process_names:
  - monasca-notification
  - monasca-api
  dimensions:
    service: monitoring
- process_names:
  - elasticsearch
  dimensions:
    service: logging
- process_names:
  - monasca-thresh
  exact_match: 'true'
  dimensions:
    service: monitoring
    component: thresh

Sample successfully built process.yaml:

init_config: null
instances:
- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: monasca-api
    service: monitoring
  exact_match: false
  name: monasca-api
  search_string:
  - monasca-api

- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: monasca-notification
    service: monitoring
  exact_match: false
  name: monasca-notification
  search_string:
  - monasca-notification

- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: vertica
    service: monitoring
  name: vertica
  username: dbadmin

Docker environment:

For Docker environment you can enable the process plugin by adding proccess.yaml to the monasca-agent-collector container (mount plugin file to /plugins.d/process.yaml). Additionally you have to specify the path of the host process filesystem. In this case mount host root directory / to /rootfs in the container. Sample configuration:

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: monasca-collector
  detailed: true
  dimensions:
    service: monasca-collector
  exact_match: false
  search_string:
  - monasca-collector

The process checks return the following metrics ( if detailed is set to true, otherwise process.pid_count is only returned ):

Metric Name Dimensions Semantics
process.mem.rss_mbytes process_name, service, component Amount of physical memory allocated to a process, including memory from shared libraries in Mbytes
process.io.read_count process_name, service, component Number of reads by a process
process.io.write_count process_name, service, component Number of writes by a process
process.io.read_kbytes process_name, service, component Kbytes read by a process
process.io.write_kbytes process_name, service, component Kbytes written by a process
process.thread_count process_name, service, component Number of threads a process is using
process.cpu_perc process_name, service, component Percentage of cpu being consumed by a process
process.open_file_descriptors process_name, service, component Number of files being used by a process
process.pid_count process_name, service, component Number of processes that exist with this process name

On Linux, if the Agent is not run as root or the owner of the process the io metrics and the open_file_descriptors metric will fail to be reported if the mon-agent user does not have permission to get it for the process.

Prometheus Client

This plugin is for scraping metrics from endpoints that are created by prometheus client libraries - https://prometheus.io/docs/instrumenting/clientlibs/

It can be configured in two ways. One being manually setting all the endpoints that you want to scrape. The other being running in a Kubernetes environment where we autodetect on either services or pods based on annotations set.

Manually Configuring Endpoints

In this instance the plugin goes to a configured list of prometheus client endpoints and scrapes the posted metrics from each.

When configuring each endpoint you can define a set of dimensions that is attached to each metric being scraped.

By default we grab the defined labels on each metric as dimensions.

Example yaml file:

init_config:
  # Timeout on connections to each endpoint
  timeout: 3
instances:
  - metric_endpoint: "http://127.0.0.1:8000"
    # Dimensions to add to every metric coming out of the plugin
    default_dimensions:
        app: my_app

  - metric_endpoint: "http://127.0.0.1:9000"

Running in a Kubernetes Environment with autodetection

There are two ways for the autodetection to be set up. One for auto detecting based on pods and the other auto detecting for services. In both cases it is looking for the annotations set for the Kubernetes service or pod.

The annotations the plugin is looking for are -

  • prometheus.io/scrape: Only scrape pods that have a value of 'true'
  • prometheus.io/path: If the metrics path is not '/metrics' override this.
  • prometheus.io/port: Scrape the pod on the indicated port instead of the default of '9102'.
  • monasca.io/usek8slabels: Attach Kubernetes labels of the pod that is being scraped. Default to 'true'
  • monasca.io/whitelist: Yaml list of metric names to whitelist against on detected endpoint
  • monasca.io/metric_types: Yaml dictionary where key is metric name and value is desired type from 'rate' or 'counter'. Metric name will be appended with '_rate' or '_counter' respectively. If not specified, the scraped value will be passed without modification.
  • monasca.io/report_pod_label_owner: If the metrics that are scraped contain pod as a label key we will attempt to get the pod owner and attach that to the metric as another dimension. Very useful for other scraping from other solutions that monitor k8s (Ex. kube-state-metrics). Default to 'false'

These annotations are pulled from the Kubelet for pod autodetection and the Kubernetes API for the service auto detection

There is also configuration parameter of "kubernetes_labels" where it will look for Kubernetes tags to use as dimensions for metrics coming out. By default that will be set to "app"

Example yaml file (by pod):

init_config:
  timeout: 3
  auto_detect_endpoints: True
  detect_method: "pod"
instances:
- kubernetes_labels: ['app']

Example yaml file (by service):

init_config:
  timeout: 3
  auto_detect_endpoints: True
  detect_method: "service"
instances:
- kubernetes_labels: ['app']

Example k8s manifest annotation section:

annotations:
  prometheus.io/scrape: "true"
  prometheus.io/port: "8080"
  monasca.io/usek8slabels: "false"
  monasca.io/whitelist: |
    - storage
    - cpu
    - memory
  monasca.io/metric_types: "{storage: rate}"

NOTE This Plugin can only have one configured instance

RabbitMQ Checks

This section describes the RabbitMQ check that can be performed by the Agent. The RabbitMQ check gathers metrics on Nodes, Exchanges and Queues from the rabbit server. The RabbitMQ check requires a configuration file called rabbitmq.yaml to be available in the agent conf.d configuration directory. The config file must contain the names of the Exchanges and Queues that you are interested in monitoring.

NOTE: The agent RabbitMQ plugin requires the RabbitMQ Management Plugin to be installed. The management plugin is included in the RabbitMQ distribution. To enable it, use the rabbitmq-plugins command like this:

rabbitmq-plugins enable rabbitmq_management

Sample config:

init_config:

instances:
  - exchanges: [nova, cinder, ceilometer, glance, keystone, neutron, heat]
    nodes: [rabbit@devstack]
    queues: [conductor]
    rabbitmq_api_url: http://localhost:15672/api
    rabbitmq_user: guest
    rabbitmq_pass: guest

If you want the monasca-setup program to detect and auto-configure the plugin for you, you must pass watch_api=true to the plugin, for example:

monasca-setup \
  --detection_plugins rabbitmq \
  --detection_args "watch_api=true"

Additionally, you must create the file /root/.rabbitmq.cnf with the information needed in the configuration yaml file before running the setup program. It should look something like this:

[client]
user=guest
password=pass
nodes=rabbit@devstack
queues=conductor
exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat

Alternatively, the arguments can be passed on the command line, but note that all arguments must be passed in this case - the configuration file will not be read:

monasca-setup \
  --detection_plugins rabbitmq \
  --detection_args \
    "watch_api=true
     user=guest
     password=pass
     nodes=rabbit@devstack
     queues=conductor
     exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat"

For more details of each metric, please refer the RabbitMQ documentation. The RabbitMQ checks return the following metrics:

Metric Name Dimensions Check Type Description
rabbitmq.node.fd_used hostname, node, service=rabbitmq Node Value of the "fd_used" field in the response of /api/nodes
rabbitmq.node.sockets_used hostname, node, service=rabbitmq Node Value of the "sockets_used" field in the response of /api/nodes
rabbitmq.node.run_queue hostname, node, service=rabbitmq Node Value of the "run_queue" field in the response of /api/nodes
rabbitmq.node.mem_used hostname, node, service=rabbitmq Node Value of the "mem_used" field in the response of /api/nodes
rabbitmq.exchange.messages.received_count hostname, exchange, vhost, type, service=rabbitmq Exchange Value of the "publish_in" field of "message_stats" object
rabbitmq.exchange.messages.received_rate hostname, exchange, vhost, type, service=rabbitmq Exchange Value of the "rate" field of "message_stats/publish_in_details" object
rabbitmq.exchange.messages.published_count hostname, exchange, vhost, type, service=rabbitmq Exchange Value of the "publish_out" field of "message_stats" object
rabbitmq.exchange.messages.published_rate hostname, exchange, vhost, type, service=rabbitmq Exchange Value of the "rate" field of "message_stats/publish_out_details" object
rabbitmq.queue.consumers hostname, queue, vhost, service=rabbitmq Queue Number of consumers
rabbitmq.queue.memory hostname, queue, vhost, service=rabbitmq Queue Bytes of memory consumed by the Erlang process associated with the queue, including stack, heap and internal structures
rabbitmq.queue.active_consumers hostname, queue, vhost, service=rabbitmq Queue
rabbitmq.queue.messages hostname, queue, vhost, service=rabbitmq Queue Sum of ready and unacknowledged messages (queue depth)
rabbitmq.queue.messages.rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_details" object
rabbitmq.queue.messages.ready hostname, queue, vhost, service=rabbitmq Queue Number of messages ready to be delivered to clients
rabbitmq.queue.messages.ready_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_ready_details" object
rabbitmq.queue.messages.publish_count hostname, queue, vhost, service=rabbitmq Queue Value of the "publish" field of "message_stats" object
rabbitmq.queue.messages.publish_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_stats/publish_details" object
rabbitmq.queue.messages.deliver_count hostname, queue, vhost, service=rabbitmq Queue Value of the "deliver" field of "message_stats" object
rabbitmq.queue.messages.deliver_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_stats/deliver_details" object
rabbitmq.queue.messages.redeliver_count hostname, queue, vhost, service=rabbitmq Queue Value of the "redeliver" field of "message_stats" object
rabbitmq.queue.messages.redeliver_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_stats/redeliver_details" object
rabbitmq.queue.messages.unacknowledged hostname, queue, vhost, service=rabbitmq Queue Number of messages delivered to clients but not yet acknowledged
rabbitmq.queue.messages.unacknowledged_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_stats/messages_unacknowledged_details" object
rabbitmq.queue.messages.deliver_get_count hostname, queue, vhost, service=rabbitmq Queue Value of the "deliver_get" field of "message_stats" object
rabbitmq.queue.messages.deliver_get_rate hostname, queue, vhost, service=rabbitmq Queue Value of the "rate" field of "message_stats/deliver_get_details" object
rabbitmq.queue.messages.ack_count hostname, queue, vhost, service=rabbitmq Queue
rabbitmq.queue.messages.ack_rate hostname, queue, vhost, service=rabbitmq Queue

RedisDB

See the example configuration for how to configure the plugin.

Riak

See the example configuration for how to configure the Riak plugin.

SolidFire

The SolidFire checks require a matching solidfire.yaml to be present. Currently the checks report a mixture of cluster utilization and health metrics. Multiple clusters can be monitored via separate instance stanzas in the config file.

Sample config:

instances: - name: cluster_rack_d username: cluster_admin password: secret_password mvip: 192.168.1.1

The SolidFire checks return the following metrics:

Metric Name Dimensions Semantics
solidfire.active_cluster_faults service=solidfire, cluster Amount of active cluster faults, such as failed drives
solidfire.cluster_utilization service=solidfire, cluster Overall cluster IOP utilization
solidfire.num_iscsi_sessions service=solidfire, cluster Amount of active iSCSI sessions connected to the cluster
solidfire.iops.avg_5_sec service=solidfire, cluster Average IOPs over the last 5 seconds
solidfire.iops.avg_utc service=solidfire, cluster Average IOPs since midnight UTC
solidfire.iops.peak_utc service=solidfire, cluster Peak IOPS since midnight UTC
solidfire.iops.max_available service=solidfire, cluster Theoretical maximum amount of IOPs
solidfire.active_block_bytes service=solidfire, cluster Amount of space consumed by the block services, including cruft
solidfire.active_meta_bytes service=solidfire, cluster Amount of space consumed by the metadata services
solidfire.active_snapshot_bytes service=solidfire, cluster Amount of space consumed by the metadata services for snapshots
solidfire.provisioned_bytes service=solidfire, cluster Total number of provisioned bytes
solidfire.unique_blocks_used_bytes service=solidfire, cluster Amount of space the unique blocks take on the block drives
solidfire.max_block_bytes service=solidfire, cluster Maximum amount of bytes allocated to the block services
solidfire.max_meta_bytes service=solidfire, cluster Maximum amount of bytes allocated to the metadata services
solidfire.max_provisioned_bytes service=solidfire, cluster Max provisionable space if 100% metadata space used
solidfire.max_overprovisioned_bytes service=solidfire, cluster Max provisionable space * 5, artificial safety limit
solidfire.unique_blocks service=solidfire, cluster Number of blocks(not always 4KiB) stored on block drives
solidfire.non_zero_blocks service=solidfire, cluster Number of 4KiB blocks with data after the last garbage collection
solidfire.zero_blocks service=solidfire, cluster Number of 4KiB blocks without data after the last garbage collection
solidfire.thin_provision_factor service=solidfire, cluster Thin provisioning factor, (nonZeroBlocks + zeroBlocks) / nonZeroBlocks
solidfire.deduplication_factor service=solidfire, cluster Data deduplication factor, nonZeroBlocks / uniqueBlocks
solidfire.compression_factor service=solidfire, cluster Data compression factor, (uniqueBlocks * 4096) / uniqueBlocksUsedSpace
solidfire.data_reduction_factor service=solidfire, cluster Aggregate data reduction efficiency, thin_prov * dedup * compression

SQLServer

See the example configuration for how to configure the SQLServer plugin.

Supervisord

See the example configuration for how to configure the Supervisord plugin.

Swift Diags

See the example configuration for how to configure the Swift Diags plugin.

TCP Check

See the example configuration for how to configure the TCP Check plugin.

Varnish

See the example configuration for how to configure the Varnish plugin.

VCenter

This plugin provides metrics for VMware ESX clusters. It connects to vCenter server with its credentials and collects the configured cluster's performance data.

Sample Config

init_config: {}
instances:
    - vcenter_ip: <vcenter-ip or fqdn>
        username: <vcenter-user>
        password: <vcenter-password>
        clusters: <[cluster-name-list]> # e.g: [cluster-1, cluster-2]

ESX Cluster Metrics

Below are the list of metrics collected by this plugin from the configured cluster:

Metric Name Description
vcenter.cpu.total_mhz Total amount of CPU resources of all hosts in the cluster, as measured in megahertz. ESX counter name: cpu.totalmhz.average
vcenter.cpu.used_mhz Sum of the average CPU usage values, in megahertz, of all virtual machines in the cluster. ESX counter name: cpu.usagemhz.average
vcenter.cpu.used_perc CPU usage in percent, during the interval
vcenter.cpu.total_logical_cores Aggregated number of CPU threads. ESX counter name: numCpuThreads
vcenter.mem.total_mb Total amount of machine memory of all hosts in the cluster that is available for guest memory and guest overhead memory. ESX counter name: mem.consumed.average
vcenter.mem.used_mb A cluster's consumed memory consists of guest consumed memory and overhead memory. It does not include host-specific overhead memory. ESX counter name: mem.consumed.average
vcenter.mem.used_perc A cluster's consumed memory in percentage
vcenter.disk.total_space_mb Aggregation of maximum capacities of datastores connected to the hosts of a cluster, in megabytes. ESX counter name: summary.capacity
vcenter.disk.total_used_space_mb Aggregation of all available capacities of datastores connected to the hosts of a cluster, in megabytes. ESX counter name: summary.freeSpace
vcenter.disk.total_used_space_perc Aggregation of all available capacities of datastores connected to the hosts of a cluster, in percent

ESX Cluster Dimensions

    "vcenter_ip": <vcenter-ip or fqdn>,
    "cluster": <cluster-name>,
    "host_type": "compute_node",
    "role": "esx",
    "id": <cluster-name>-<vcenter-ip or fqdn>

VCenter Slim

This plugin provides exclusively vm status metrics for VMware ESX clusters. Includes configuration for which annotations to add to dimensions via allowed_keys (collects annotations with that key, if available) and key_map (replaces annotation key when creating dimension). In the example below, the resulting metrics will have a dimension of 'tenant_id' with the value from the 'project_id' annotation.

Sample Config

init_config:
  vcenter_ip: "127.0.0.1"
  vcenter_user: "joe"
  vcenter_password: "12345"
  vcenter_port: 443
  retry_count: 3
  poll_interval: 0.5
  vcenter_max_objects: 100000
  allowed_keys:
  - project_id
  key_map:
    project_id: tenant_id

instances:
  # this plugin doesn't support instances, this section will be ignored (but is still required for structure)
Metric Name Description
vm.status The connection status of the vm. Value is 0 if the vm can be managed normally, 1 for all other states

Vertica Checks

This section describes the vertica check that can be performed by the Agent. The vertica check requires a configuration file called vertica.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
    user: mon_api
    password: password
    service: monasca (optional, defaults to vertica)
    timeout: 3 (optional, defaults to 3 seconds)
Metric Name Dimensions Semantics
vertica.license_usage_percent hostname, service=vertica Percentage of the license size taken up.
vertica.connection_status hostname, node_name, service=vertica Value of DB connection status (0=Healthy).
vertica.node_status hostname, node_name, service=vertica Status of node connection (0=UP).
vertica.projection.ros_count hostname, node_name, projection_name, service=vertica The number of ROS containers in the projection.
vertica.projection.tuple_mover_mergeouts hostname, node_name, projection_name, service=vertica Number of current tuple mover mergeouts on this projection.
vertica.projection.tuple_mover_moveouts hostname, node_name, projection_name, service=vertica Number of current tuple mover moveout on this projection.
vertica.projection.wos_used_bytes hostname, node_name, projection_name, service=vertica The number of WOS bytes in the projection.).
vertica.resource.disk_space_rejections hostname, node_name, service=vertica The number of rejected disk write requests.
vertica.resource.pool.memory_inuse_kb hostname, node_name, resource_pool, service=vertica Amount of memory, in kilobytes, acquired by requests running against this pool.
vertica.resource.pool.memory_size_actual_kb hostname, node_name, resource_pool, service=vertica Current amount of memory, in kilobytes, allocated to the pool by the resource manager.
vertica.resource.pool.rejection_count hostname, node_name, resource_pool, service=vertica Number of resource rejections for this pool
vertica.resource.pool.running_query_count hostname, node_name, resource_pool, service=vertica Number of queries actually running using this pool.
vertica.resource.request_queue_depth hostname, node_name, service=vertica The cumulative number of requests for threads, file handles, and memory.
vertica.resource.resource_rejections hostname, node_name, service=vertica The number of rejected plan requests.
vertica.resource.wos_used_bytes hostname, node_name, service=vertica The size of the WOS in bytes.

WMI Check

ZooKeeper

This section describes the Zookeeper check that can be performed by the Agent. The Zookeeper check requires a configuration file called zk.yaml to be available in the agent conf.d configuration directory. The Zookeeper check parses the result of zookeeper's stat admin command.

Sample config:

init_config:

instances:
  - host: localhost
    port: 2181
    timeout: 3

The Zookeeper checks return the following metrics:

Metric Name Dimensions Semantics
zookeeper.max_latency_sec hostname, mode, service=zookeeper Maximum latency in second
zookeeper.min_latency_sec hostname, mode, service=zookeeper Minimum latency in second
zookeeper.avg_latency_sec hostname, mode, service=zookeeper Average latency in second
zookeeper.out_bytes hostname, mode, service=zookeeper Sent bytes
zookeeper.outstanding_bytes hostname, mode, service=zookeeper Outstanding bytes
zookeeper.in_bytes hostname, mode, service=zookeeper Received bytes
zookeeper.connections_count hostname, mode, service=zookeeper Number of connections
zookeeper.node_count hostname, mode, service=zookeeper Number of nodes
zookeeper.zxid_count hostname, mode, service=zookeeper Count number
zookeeper.zxid_epoch hostname, mode, service=zookeeper Epoch number

Kibana

This section describes the Kibana check that can be performed by the Agent. The Kibana check requires a configuration file containing Kibana configuration (it is the same file Kibana is using).

Check is accessing status endpoint (curl -XGET http://localhost:5601/api/status) of Kibana, which means it can work only with Kibana >= 4.2.x, that was first to introduce this capability.

Sample config:

init_config:
  url: http://localhost:5601/api/status
instances:
- built_by: Kibana
  metrics:
    - heap_size
    - heap_used
    - load
    - req_sec
    - resp_time_avg
    - resp_time_max

The Kibana checks return the following metrics:

Metric Name Dimensions Semantics
kibana.load_avg_1m hostnam, version, service=monitoring The average kibana load over a 1 minute period, for more details see here
kibana.load_avg_5m hostnam, version, service=monitoring The average kibana load over a 5 minutes period, for more details see here
kibana.load_avg_15m hostnam, version, service=monitoring The average kibana load over a 15 minutes period, for more details see here
kibana.heap_size_mb hostnam, version, service=monitoring Total heap size in MB
kibana.heap_used_mb hostnam, version, service=monitoring Used heap size in MB
kibana.req_sec hostnam, version, service=monitoring Requests per second to Kibana server
kibana.resp_time_avg_ms hostnam, version, service=monitoring The average response time of Kibana server in ms
kibana.resp_time_max_ms hostnam, version, service=monitoring The maximum response time of Kibana server in ms

OpenStack Monitoring

The monasca-setup script when run on a system that is running OpenStack services, configures the Agent to send the following list of metrics:

  • The setup program creates process checks for each process that is part of an OpenStack service. A few sample metrics from the process check are provided. For the complete list of process metrics, see the [Process Checks](#Process Checks) section.
  • Additionally, an http_status check will be setup on the api for the service, if there is one.

PLEASE NOTE: The monasca-setup program will only install checks for OpenStack services it detects when it is run. If an additional service is added to a particular node or deleted, monasca-setup must be re-run to add monitoring for the additional service or remove the service that is no longer there.

Nova Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Nova service.

The following nova processes are monitored, if they exist when the monasca-setup script is run:

Nova Processes Monitored
  • nova-compute
  • nova-conductor
  • nova-cert
  • nova-network
  • nova-scheduler
  • nova-novncproxy
  • nova-xvpncproxy
  • nova-consoleauth
  • nova-objectstore
  • nova-api
Example Nova Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
nova-compute processes.process_pid_count Gauge Passive service=nova, component=nova-compute process nova-compute process exists This is only one of the process checks performed
nova-api processes.process_pid_count Gauge Passive service=nova, component=nova-api process nova-api process pid count This is only one of the process checks performed
nova-api http_status Gauge Active service=nova, component=nova-api url=url_to_nova_api http_status nova-api http endpoint is alive This check should be executed on multiple systems.

Swift Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Swift service.

The following swift processes are monitored, if they exist when the monasca-setup script is run:

Swift Processes Monitored
  • swift-container-updater
  • swift-account-auditor
  • swift-object-replicator
  • swift-container-replicator
  • swift-object-auditor
  • swift-container-auditor
  • swift-account-reaper
  • swift-container-sync
  • swift-account-replicator
  • swift-object-updater
  • swift-object-server
  • swift-account-server
  • swift-container-server
  • swift-proxy-server
Example Swift Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
swift-container-updater processes.process_pid_count Gauge Passive service=swift, component=swift-container-updater process swift-container-updater process exists This is only one of the process checks performed
swift-proxy-server processes.process_pid_count Gauge Passive service=swift, component=swift-proxy-server process swift-proxy-server process pid count This is only one of the process checks performed
swift-proxy-server http_status Gauge Active service=swift, component=swift-proxy-server url=url_to_swift_proxy_server http_status swift-proxy-server http endpoint is alive This check should be executed on multiple systems.

Glance Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Glance service.

The following glance processes are monitored, if they exist when the monasca-setup script is run:

Glance Processes Monitored
  • glance-registry
  • glance-api
Example Glance Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
glance-registry processes.process_pid_count Gauge Passive service=glance, component=glance-registry process glance-registry process exists This is only one of the process checks performed
glance-api processes.process_pid_count Gauge Passive service=glance, component=glance-api process glance-api process pid count This is only one of the process checks performed
glance-api http_status Gauge Active service=glance, component=glance-api url=url_to_glance_api http_status glance-api http endpoint is alive This check should be executed on multiple systems.

Cinder Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Cinder service.

The following cinder processes are monitored, if they exist when the monasca-setup script is run:

Cinder Processes Monitored
  • cinder-volume
  • cinder-scheduler
  • cinder-api
Example Cinder Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
cinder-volume processes.process_pid_count Gauge Passive service=cinder, component=cinder-volume process cinder-volume process exists This is only one of the process checks performed
cinder-api processes.process_pid_count Gauge Passive service=cinder, component=cinder-api process cinder-api process pid count This is only one of the process checks performed
cinder-api http_status Gauge Active service=cinder, component=cinder-api url=url_to_cinder_api http_status cinder-api http endpoint is alive This check should be executed on multiple systems.

Neutron Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Neutron service.

The following neutron processes are monitored, if they exist when the monasca-setup script is run:

Neutron Processes Monitored
  • neutron-server
  • neutron-openvswitch-agent
  • neutron-rootwrap
  • neutron-dhcp-agent
  • neutron-vpn-agent
  • neutron-metadata-agent
  • neutron-metering-agent
  • neutron-ns-metadata-proxy
Example Neutron Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
neutron-server processes.process_pid_count Gauge Passive service=neutron, component=neutron-server process neutron-server process exists This is only one of the process checks performed
neutron-ns-metadata-proxy processes.process_pid_count Gauge Passive service=neutron, component=neutron-ns-metadata-proxy process neutron-ns-metadata-proxy process pid count This is only one of the process checks performed
neutron-ns-metadata-proxy http_status Gauge Active service=neutron, component=neutron-ns-metadata-proxy url=url_to_neutron_api http_status neutron-ns-metadata-proxy http endpoint is alive This check should be executed on multiple systems.

Keystone Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Keystone service.

The following keystone processes are monitored, if they exist when the monasca-setup script is run:

Keystone Processes Monitored
  • keystone-all
Example Keystone Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
keystone-all processes.process_pid_count Gauge Passive service=keystone, component=keystone-all process keystone-all process pid count This is only one of the process checks performed
keystone-all http_status Gauge Active service=keystone, component=keystone-all url=url_to_keystone_api http_status keystone-all http endpoint is alive This check should be executed on multiple systems.

Ceilometer Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Ceilometer service.

The following ceilometer processes are monitored, if they exist when the monasca-setup script is run:

Ceilometer Processes Monitored
  • ceilometer-agent-compute
  • ceilometer-agent-central
  • ceilometer-agent-notification
  • ceilometer-collector
  • ceilometer-alarm-notifier
  • ceilometer-alarm-evaluator
  • ceilometer-api
Example Ceilometer Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
ceilometer-agent-compute processes.process_pid_count Gauge Passive service=ceilometer, component=ceilometer-agent-compute process ceilometer-agent-compute process exists This is only one of the process checks performed
ceilometer-api processes.process_pid_count Gauge Passive service=ceilometer, component=ceilometer-api process ceilometer-api process pid count This is only one of the process checks performed
ceilometer-api http_status Gauge Active service=ceilometer, component=ceilometer-api url=url_to_ceilometer_api http_status ceilometer-api http endpoint is alive This check should be executed on multiple systems.

Freezer Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Freezer service.

The following Freezer processes are monitored, if they exist when the monasca-setup script is run:

Freezer Processes Monitored
  • freezer-scheduler
  • freezer-api
Example Freezer Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
freezer-api processes.process_pid_count Gauge Passive service=backup, component=freezer-api process freezer-api process pid count This is only one of the process checks performed
freezer-api http_status Gauge Active service=backup, component=freezer-api url=url_to_freezer_api http_status freezer-api http endpoint is alive This check should be executed on multiple systems.
freezer-scheduler processes.process_pid_count Gauge Passive service=backup, component=freezer-scheduler process freezer-scheduler process pid count This is only one of the process checks performed

Magnum Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Magnum service.

The following Magnum processes are monitored, if they exist when the monasca-setup script is run:

Magnum Processes Monitored
  • magnum-api
  • magnum-controller
Example Magnum Metrics
Component Metric Name Metric Type Check Type Dimensions Plugin Description Notes
magnum-api processes.process_pid_count Gauge Passive service=container-infra, component=magnum-api process magnum-api process pid count This is only one of the process checks performed
magnum-api http_status Gauge Active service=container-infra, component=magnum-api url=url_to_magnum_api http_status magnum-api http endpoint is alive This check should be executed on multiple systems
magnum-controller processes.process_pid_count Gauge Passive service=container-infra, component=magnum-conductor process magnum-conductor process pid count This is only one of the process checks performed

License

(C) Copyright 2015-2017 Hewlett Packard Enterprise Development LP