OpenTelemetry Collector Service

The Service section is used to configure what components are enabled in the Collector based on the configuration found in the receivers, processors, exporters, and extensions sections.

Info

If a component is configured, but not defined within the Service section then it is not enabled.

The service section consists of three sub-sections:

extensions
pipelines
telemetry

In the default configuration, the extension section has been configured to enable health_check, pprof and zpages, which we configured in the Extensions module earlier.

service:
  extensions: [health_check, pprof, zpages]

So lets configure our Metric Pipeline!

OpenTelemetry Collector Service

Hostmetrics Receiver

If you recall from the Receivers portion of the workshop, we defined the Host Metrics Receiver to generate metrics about the host system, which are scraped from various sources. To enable the receiver, we must include the hostmetrics receiver in the metrics pipeline.

In the metrics pipeline, add hostmetrics to the metrics receivers section.

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus]
      processors: [batch]
      exporters: [debug]

OpenTelemetry Collector Service

Prometheus Internal Receiver

Earlier in the workshop, we also renamed the prometheus receiver to reflect that is was collecting metrics internal to the collector, renaming it to prometheus/internal.

We now need to enable the prometheus/internal receiver under the metrics pipeline. Update the receivers section to include prometheus/internal under the metrics pipeline:

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus/internal]
      processors: [batch]
      exporters: [debug]

OpenTelemetry Collector Service

Resource Detection Processor

We also added resourcedetection/system and resourcedetection/ec2 processors so that the collector can capture the instance hostname and AWS/EC2 metadata. We now need to enable these two processors under the metrics pipeline.

Update the processors section to include resourcedetection/system and resourcedetection/ec2 under the metrics pipeline:

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus/internal]
      processors: [batch, resourcedetection/system, resourcedetection/ec2]
      exporters: [debug]

OpenTelemetry Collector Service

Attributes Processor

Also in the Processors section of this workshop, we added the attributes/conf processor so that the collector will insert a new attribute called participant.name to all the metrics. We now need to enable this under the metrics pipeline.

Update the processors section to include attributes/conf under the metrics pipeline:

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus/internal]
      processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf]
      exporters: [debug]

OpenTelemetry Collector Service

OTLP HTTP Exporter

In the Exporters section of the workshop, we configured the otlphttp exporter to send metrics to Splunk Observability Cloud. We now need to enable this under the metrics pipeline.

Update the exporters section to include otlphttp/splunk under the metrics pipeline:

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus/internal]
      processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf]
      exporters: [debug, otlphttp/splunk]

Ninja: Observing the collector internals

The collector captures internal signals about its behavior this also includes additional signals from running components. The reason for this is that components that make decisions about the flow of data need a way to surface that information as metrics or traces.

Why monitor the collector?

This is somewhat of a chicken and egg problem of, “Who is watching the watcher?”, but it is important that we can surface this information. Another interesting part of the collector’s history is that it existed before the Go metrics’ SDK was considered stable so the collector exposes a Prometheus endpoint to provide this functionality for the time being.

Considerations

Monitoring the internal usage of each running collector in your organization can contribute a significant amount of new Metric Time Series (MTS). The Splunk distribution has curated these metrics for you and would be able to help forecast the expected increases.

The Ninja Zone

To expose the internal observability of the collector, some additional settings can be adjusted:

service:
  telemetry:
    logs:
      level: <info|warn|error>
      development: <true|false>
      encoding: <console|json>
      disable_caller: <true|false>
      disable_stacktrace: <true|false>
      output_paths: [<stdout|stderr>, paths...]
      error_output_paths: [<stdout|stderr>, paths...]
      initial_fields:
        key: value
    metrics:
      level: <none|basic|normal|detailed>
      # Address binds the promethues endpoint to scrape
      address: <hostname:port>

service:
  telemetry:
    logs: 
      level: info
      encoding: json
      disable_stacktrace: true
      initial_fields:
        instance.name: ${env:INSTANCE}
    metrics:
      address: localhost:8888

References

https://opentelemetry.io/docs/collector/configuration/#service

Final configuration

Check-inReview your final configuration

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# To limit exposure to denial of service attacks, change the host in endpoints below from 0.0.0.0 to a specific network interface.
# See https://github.com/open-telemetry/opentelemetry-collector/blob/main/docs/security-best-practices.md#safeguards-against-denial-of-service-attacks

extensions:
  health_check:
    endpoint: 0.0.0.0:13133
  pprof:
    endpoint: 0.0.0.0:1777
  zpages:
    endpoint: 0.0.0.0:55679

receivers:
  hostmetrics:
    collection_interval: 10s
    scrapers:
      # CPU utilization metrics
      cpu:
      # Disk I/O metrics
      disk:
      # File System utilization metrics
      filesystem:
      # Memory utilization metrics
      memory:
      # Network interface I/O metrics & TCP connection metrics
      network:
      # CPU load metrics
      load:
      # Paging/Swap space utilization and I/O metrics
      paging:
      # Process count metrics
      processes:
      # Per process CPU, Memory and Disk I/O metrics. Disabled by default.
      # process:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

  opencensus:
    endpoint: 0.0.0.0:55678

  # Collect own metrics
  prometheus/internal:
    config:
      scrape_configs:
      - job_name: 'otel-collector'
        scrape_interval: 10s
        static_configs:
        - targets: ['0.0.0.0:8888']

  jaeger:
    protocols:
      grpc:
        endpoint: 0.0.0.0:14250
      thrift_binary:
        endpoint: 0.0.0.0:6832
      thrift_compact:
        endpoint: 0.0.0.0:6831
      thrift_http:
        endpoint: 0.0.0.0:14268

  zipkin:
    endpoint: 0.0.0.0:9411

processors:
  batch:
  resourcedetection/system:
    detectors: [system]
    system:
      hostname_sources: [os]
  resourcedetection/ec2:
    detectors: [ec2]
  attributes/conf:
    actions:
      - key: participant.name
        action: insert
        value: "INSERT_YOUR_NAME_HERE"

exporters:
  debug:
    verbosity: normal
  otlphttp/splunk:
    metrics_endpoint: https://ingest.${env:REALM}.signalfx.com/v2/datapoint/otlp
    headers:
      X-SF-Token: ${env:ACCESS_TOKEN}

service:

  pipelines:

    traces:
      receivers: [otlp, opencensus, jaeger, zipkin]
      processors: [batch]
      exporters: [debug]

    metrics:
      receivers: [hostmetrics, otlp, opencensus, prometheus/internal]
      processors: [batch, resourcedetection/system, resourcedetection/ec2, attributes/conf]
      exporters: [debug, otlphttp/splunk]

    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [debug]

  extensions: [health_check, pprof, zpages]

Tip

It is recommended that you validate your configuration file before restarting the collector. You can do this by pasting the contents of your config.yaml file into the OTelBin Configuration Validator tool.

ScreenshotOTelBin

Now that we have a working configuration, let’s start the collector and then check to see what zPages is reporting.

otelcol-contrib --config=file:/etc/otelcol-contrib/config.yaml

Open up zPages in your browser: http://localhost:55679/debug/pipelinez (change localhost to reflect your own environment).

OpenTelemetry Collector Service

Subsections of 6. Service

OpenTelemetry Collector Service

Hostmetrics Receiver

OpenTelemetry Collector Service

Prometheus Internal Receiver

OpenTelemetry Collector Service

Resource Detection Processor

OpenTelemetry Collector Service

Attributes Processor

OpenTelemetry Collector Service

OTLP HTTP Exporter

Why monitor the collector?

Considerations

The Ninja Zone

References

Final configuration