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Configuring and deploying the Red Hat build of OpenTelemetry

The Red Hat build of OpenTelemetry Operator uses a custom resource definition (CRD) file that defines the architecture and configuration settings to be used when creating and deploying the Red Hat build of OpenTelemetry resources. You can install the default configuration or modify the file.

OpenTelemetry Collector configuration options

The OpenTelemetry Collector consists of five types of components that access telemetry data:

Receivers

A receiver, which can be push or pull based, is how data gets into the Collector. Generally, a receiver accepts data in a specified format, translates it into the internal format, and passes it to processors and exporters defined in the applicable pipelines. By default, no receivers are configured. One or more receivers must be configured. Receivers may support one or more data sources.

Processors

Optional. Processors process the data between it is received and exported. By default, no processors are enabled. Processors must be enabled for every data source. Not all processors support all data sources. Depending on the data source, multiple processors might be enabled. Note that the order of processors matters.

Exporters

An exporter, which can be push or pull based, is how you send data to one or more back ends or destinations. By default, no exporters are configured. One or more exporters must be configured. Exporters can support one or more data sources. Exporters might be used with their default settings, but many exporters require configuration to specify at least the destination and security settings.

Connectors

A connector connects two pipelines. It consumes data as an exporter at the end of one pipeline and emits data as a receiver at the start of another pipeline. It can consume and emit data of the same or different data type. It can generate and emit data to summarize the consumed data, or it can merely replicate or route data.

Extensions

An extension adds capabilities to the Collector. For example, authentication can be added to the receivers and exporters automatically.

You can define multiple instances of components in a custom resource YAML file. When configured, these components must be enabled through pipelines defined in the spec.config.service section of the YAML file. As a best practice, only enable the components that you need.

Example of the OpenTelemetry Collector custom resource file
apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: cluster-collector
  namespace: tracing-system
spec:
  mode: deployment
  observability:
    metrics:
      enableMetrics: true
  config: |
    receivers:
      otlp:
        protocols:
          grpc:
          http:
    processors:
    exporters:
      otlp:
        endpoint: jaeger-production-collector-headless.tracing-system.svc:4317
        tls:
          ca_file: "/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt"
      prometheus:
        endpoint: 0.0.0.0:8889
        resource_to_telemetry_conversion:
          enabled: true # by default resource attributes are dropped
    service: (1)
      pipelines:
        traces:
          receivers: [otlp]
          processors: []
          exporters: [jaeger]
        metrics:
          receivers: [otlp]
          processors: []
          exporters: [prometheus]
1 If a component is configured but not defined in the service section, the component is not enabled.
Table 1. Parameters used by the Operator to define the OpenTelemetry Collector
Parameter Description Values Default 
receivers:

A receiver is how data gets into the Collector. By default, no receivers are configured. There must be at least one enabled receiver for a configuration to be considered valid. Receivers are enabled by being added to a pipeline.

otlp, jaeger, prometheus, zipkin, kafka, opencensus

None

 
processors:

Processors run through the data between it is received and exported. By default, no processors are enabled.

batch, memory_limiter, resourcedetection, attributes, span, k8sattributes, filter, routing

None

 
exporters:

An exporter sends data to one or more back ends or destinations. By default, no exporters are configured. There must be at least one enabled exporter for a configuration to be considered valid. Exporters are enabled by being added to a pipeline. Exporters might be used with their default settings, but many require configuration to specify at least the destination and security settings.

otlp, otlphttp, debug, prometheus, kafka

None

 
connectors:

Connectors join pairs of pipelines, that is by consuming data as end-of-pipeline exporters and emitting data as start-of-pipeline receivers, and can be used to summarize, replicate, or route consumed data.

spanmetrics

None

 
extensions:

Optional components for tasks that do not involve processing telemetry data.

bearertokenauth, oauth2client, jaegerremotesamplin, pprof, health_check, memory_ballast, zpages

None

 
service:
  pipelines:

Components are enabled by adding them to a pipeline under services.pipeline.

 
service:
  pipelines:
    traces:
      receivers:

You enable receivers for tracing by adding them under service.pipelines.traces.

None

 
service:
  pipelines:
    traces:
      processors:

You enable processors for tracing by adding them under service.pipelines.traces.

None

 
service:
  pipelines:
    traces:
      exporters:

You enable exporters for tracing by adding them under service.pipelines.traces.

None

 
service:
  pipelines:
    metrics:
      receivers:

You enable receivers for metrics by adding them under service.pipelines.metrics.

None

 
service:
  pipelines:
    metrics:
      processors:

You enable processors for metircs by adding them under service.pipelines.metrics.

None

 
service:
  pipelines:
    metrics:
      exporters:

You enable exporters for metrics by adding them under service.pipelines.metrics.

None

OpenTelemetry Collector components

Receivers

Receivers get data into the Collector.

OTLP Receiver

The OTLP receiver ingests traces and metrics using the OpenTelemetry protocol (OTLP).

OpenTelemetry Collector custom resource with an enabled OTLP receiver
  config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: 0.0.0.0:4317 (1)
            tls: (2)
              ca_file: ca.pem
              cert_file: cert.pem
              key_file: key.pem
              client_ca_file: client.pem (3)
              reload_interval: 1h (4)
          http:
            endpoint: 0.0.0.0:4318 (5)
            tls: (6)

    service:
      pipelines:
        traces:
          receivers: [otlp]
        metrics:
          receivers: [otlp]
1 The OTLP gRPC endpoint. If omitted, the default 0.0.0.0:4317 is used.
2 The server-side TLS configuration. Defines paths to TLS certificates. If omitted, TLS is disabled.
3 The path to the TLS certificate at which the server verifies a client certificate. This sets the value of ClientCAs and ClientAuth to RequireAndVerifyClientCert in the TLSConfig. For more information, see the Config of the Golang TLS package.
4 Specifies the time interval at which the certificate is reloaded. If the value is not set, the certificate is never reloaded. The reload_interval accepts a string containing valid units of time such as ns, us (or µs), ms, s, m, h.
5 The OTLP HTTP endpoint. The default value is 0.0.0.0:4318.
6 The server-side TLS configuration. For more information, see the grpc protocol configuration section.
Jaeger Receiver

The Jaeger receiver ingests traces in the Jaeger formats.

OpenTelemetry Collector custom resource with an enabled Jaeger receiver
  config: |
    receivers:
      jaeger:
        protocols:
          grpc:
            endpoint: 0.0.0.0:14250 (1)
          thrift_http:
            endpoint: 0.0.0.0:14268 (2)
          thrift_compact:
            endpoint: 0.0.0.0:6831 (3)
          thrift_binary:
            endpoint: 0.0.0.0:6832 (4)
          tls: (5)

    service:
      pipelines:
        traces:
          receivers: [jaeger]
1 The Jaeger gRPC endpoint. If omitted, the default 0.0.0.0:14250 is used.
2 The Jaeger Thrift HTTP endpoint. If omitted, the default 0.0.0.0:14268 is used.
3 The Jaeger Thrift Compact endpoint. If omitted, the default 0.0.0.0:6831 is used.
4 The Jaeger Thrift Binary endpoint. If omitted, the default 0.0.0.0:6832 is used.
5 The server-side TLS configuration. See the OTLP receiver configuration section for more details.
Prometheus Receiver

The Prometheus receiver is currently a Technology Preview feature only.

The Prometheus receiver scrapes the metrics endpoints.

OpenTelemetry Collector custom resource with an enabled Prometheus receiver
  config: |
    receivers:
        prometheus:
          config:
            scrape_configs: (1)
              - job_name: 'my-app'  (2)
                scrape_interval: 5s (3)
                static_configs:
                  - targets: ['my-app.example.svc.cluster.local:8888'] (4)
    service:
      pipelines:
        metrics:
          receivers: [prometheus]
1 Scrapes configurations using the Prometheus format.
2 The Prometheus job name.
3 The lnterval for scraping the metrics data. Accepts time units. The default value is 1m.
4 The targets at which the metrics are exposed. This example scrapes the metrics from a my-app application in the example project.
Zipkin Receiver

The Zipkin receiver ingests traces in the Zipkin v1 and v2 formats.

OpenTelemetry Collector custom resource with the enabled Zipkin receiver
  config: |
    receivers:
      zipkin:
        endpoint: 0.0.0.0:9411 (1)
        tls: (2)

    service:
      pipelines:
        traces:
          receivers: [zipkin]
1 The Zipkin HTTP endpoint. If omitted, the default 0.0.0.0:9411 is used.
2 The server-side TLS configuration. See the OTLP receiver configuration section for more details.
Kafka Receiver

The Kafka receiver is currently a Technology Preview feature only.

The Kafka receiver receives traces, metrics, and logs from Kafka in the OTLP format.

OpenTelemetry Collector custom resource with the enabled Kafka receiver
  config: |
    receivers:
      kafka:
        brokers: ["localhost:9092"] (1)
        protocol_version: 2.0.0 (2)
        topic: otlp_spans (3)
        auth:
          plain_text: (4)
            username: example
            password: example
          tls: (5)
            ca_file: ca.pem
            cert_file: cert.pem
            key_file: key.pem
            insecure: false (6)
            server_name_override: kafka.example.corp (7)
    service:
      pipelines:
        traces:
          receivers: [kafka]
1 The list of Kafka brokers. The default is localhost:9092.
2 The Kafka protocol version. For example, 2.0.0. This is a required field.
3 The name of the Kafka topic to read from. The default is otlp_spans.
4 The plaintext authentication configuration. If omitted, plaintext authentication is disabled.
5 The client-side TLS configuration. Defines paths to the TLS certificates. If omitted, TLS authentication is disabled.
6 Disables verifying the server’s certificate chain and host name. The default is false.
7 ServerName indicates the name of the server requested by the client to support virtual hosting.
OpenCensus receiver

The OpenCensus receiver provides backwards compatibility with the OpenCensus project for easier migration of instrumented codebases. It receives metrics and traces in the OpenCensus format via gRPC or HTTP and Json.

OpenTelemetry Collector custom resource with the enabled OpenCensus receiver
  config: |
    receivers:
      opencensus:
        endpoint: 0.0.0.0:9411 (1)
        tls: (2)
        cors_allowed_origins: (3)
          - https://*.<example>.com
    service:
      pipelines:
        traces:
          receivers: [opencensus]
          ...
1 The OpenCensus endpoint. If omitted, the default is 0.0.0.0:55678.
2 The server-side TLS configuration. See the OTLP receiver configuration section for more details.
3 You can also use the HTTP JSON endpoint to optionally configure CORS, which is enabled by specifying a list of allowed CORS origins in this field. Wildcards with * are accepted under the cors_allowed_origins. To match any origin, enter only *.

Processors

Processors run through the data between it is received and exported.

Batch processor

The Batch processor batches traces and metrics to reduce the number of outgoing connections needed to transfer the telemetry information.

Example of the OpenTelemetry Collector custom resource when using the Batch processor
  config: |
    processor:
      batch:
        timeout: 5s
        send_batch_max_size: 10000
    service:
      pipelines:
        traces:
          processors: [batch]
        metrics:
          processors: [batch]
Table 2. Parameters used by the Batch processor
Parameter Description Default 
timeout

Sends the batch after a specific time duration and irrespective of the batch size.

200ms

 
send_batch_size

Sends the batch of telemetry data after the specified number of spans or metrics.

8192

 
send_batch_max_size

The maximum allowable size of the batch. Must be equal or greater than the send_batch_size.

0

 
metadata_keys

When activated, a batcher instance is created for each unique set of values found in the client.Metadata.

[]

 
metadata_cardinality_limit

When the metadata_keys are populated, this configuration restricts the number of distinct metadata key-value combinations processed throughout the duration of the process.

1000
Memory Limiter processor

The Memory Limiter processor periodically checks the Collector’s memory usage and pauses data processing when the soft memory limit is reached. This processor supports traces, metrics, and logs. The preceding component, which is typically a receiver, is expected to retry sending the same data and may apply a backpressure to the incoming data. When memory usage exceeds the hard limit, the Memory Limiter processor forces garbage collection to run.

Example of the OpenTelemetry Collector custom resource when using the Memory Limiter processor
  config: |
    processor:
      memory_limiter:
        check_interval: 1s
        limit_mib: 4000
        spike_limit_mib: 800
    service:
      pipelines:
        traces:
          processors: [batch]
        metrics:
          processors: [batch]
Table 3. Parameters used by the Memory Limiter processor
Parameter Description Default 
check_interval

Time between memory usage measurements. The optimal value is 1s. For spiky traffic patterns, you can decrease the check_interval or increase the spike_limit_mib.

0s

 
limit_mib

The hard limit, which is the maximum amount of memory in MiB allocated on the heap. Typically, the total memory usage of the OpenTelemetry Collector is about 50 MiB greater than this value.

0

 
spike_limit_mib

Spike limit, which is the maximum expected spike of memory usage in MiB. The optimal value is approximately 20% of limit_mib. To calculate the soft limit, subtract the spike_limit_mib from the limit_mib.

20% of limit_mib

 
limit_percentage

Same as the limit_mib but expressed as a percentage of the total available memory. The limit_mib setting takes precedence over this setting.

0

 
spike_limit_percentage

Same as the spike_limit_mib but expressed as a percentage of the total available memory. Intended to be used with the limit_percentage setting.

0
Resource Detection processor

The Resource Detection processor is currently a Technology Preview feature only.

The Resource Detection processor identifies host resource details in alignment with OpenTelemetry’s resource semantic standards. Using the detected information, it can add or replace the resource values in telemetry data. This processor supports traces, metrics, and can be used with multiple detectors such as the Docket metadata detector or the OTEL_RESOURCE_ATTRIBUTES environment variable detector.

OpenShift Container Platform permissions required for the Resource Detection processor
kind: ClusterRole
metadata:
  name: otel-collector
rules:
- apiGroups: ["config.openshift.io"]
  resources: ["infrastructures", "infrastructures/status"]
  verbs: ["get", "watch", "list"]
OpenTelemetry Collector using the Resource Detection processor
  config: |
    processor:
      resourcedetection:
        detectors: [openshift]
        override: true
    service:
      pipelines:
        traces:
          processors: [resourcedetection]
        metrics:
          processors: [resourcedetection]
OpenTelemetry Collector using the Resource Detection Processor with an environment variable detector
  config: |
    processors:
      resourcedetection/env:
        detectors: [env] (1)
        timeout: 2s
        override: false
1 Specifies which detector to use. In this example, the environment detector is specified.
Attributes processor

The Attributes processor is currently a Technology Preview feature only.

The Attributes processor can modify attributes of a span, log, or metric. You can configure this processor to filter and match input data and include or exclude such data for specific actions.

The processor operates on a list of actions, executing them in the order specified in the configuration. The following actions are supported:

Insert

Inserts a new attribute into the input data when the specified key does not already exist.

Update

Updates an attribute in the input data if the key already exists.

Upsert

Combines the insert and update actions: Inserts a new attribute if the key does not exist yet. Updates the attribute if the key already exists.

Delete

Removes an attribute from the input data.

Hash

Hashes an existing attribute value as SHA1.

Extract

Extracts values by using a regular expression rule from the input key to the target keys defined in the rule. If a target key already exists, it will be overridden similarly to the Span processor’s to_attributes setting with the existing attribute as the source.

Convert

Converts an existing attribute to a specified type.

OpenTelemetry Collector using the Attributes processor
  config: |
    processors:
      attributes/example:
        actions:
          - key: db.table
            action: delete
          - key: redacted_span
            value: true
            action: upsert
          - key: copy_key
            from_attribute: key_original
            action: update
          - key: account_id
            value: 2245
            action: insert
          - key: account_password
            action: delete
          - key: account_email
            action: hash
          - key: http.status_code
            action: convert
            converted_type: int
Resource processor

The Resource processor is currently a Technology Preview feature only.

The Resource processor applies changes to the resource attributes. This processor supports traces, metrics, and logs.

OpenTelemetry Collector using the Resource Detection processor
  config: |
    processor:
      attributes:
      - key: cloud.availability_zone
        value: "zone-1"
        action: upsert
      - key: k8s.cluster.name
        from_attribute: k8s-cluster
        action: insert
      - key: redundant-attribute
        action: delete

Attributes represent the actions that are applied to the resource attributes, such as delete the attribute, insert the attribute, or upsert the attribute.

Span processor

The Span processor is currently a Technology Preview feature only.

The Span processor modifies the span name based on its attributes or extracts the span attributes from the span name. It can also change the span status. It can also include or exclude spans. This processor supports traces.

Span renaming requires specifying attributes for the new name by using the from_attributes configuration.

OpenTelemetry Collector using the Span processor for renaming a span
  config: |
    processor:
      span:
        name:
          from_attributes: [<key1>, <key2>, ...] (1)
          separator: <value> (2)
1 Defines the keys to form the new span name.
2 An optional separator.

You can use the processor to extract attributes from the span name.

OpenTelemetry Collector using the Span processor for extracting attributes from a span name
  config: |
    processor:
      span/to_attributes:
        name:
          to_attributes:
            rules:
              - ^\/api\/v1\/document\/(?P<documentId>.*)\/update$ (1)
1 This rule defines how the extraction is to be executed. You can define more rules: for example, in this case, if the regular expression matches the name, a documentID attibute is created. In this example, if the input span name is /api/v1/document/12345678/update, this results in the /api/v1/document/{documentId}/update output span name, and a new "documentId"="12345678" attribute is added to the span.

You can have the span status modified.

OpenTelemetry Collector using the Span Processor for status change
  config: |
    processor:
      span/set_status:
        status:
          code: Error
          description: "<error_description>"
Kubernetes Attributes processor

The Kubernetes Attributes processor is currently a Technology Preview feature only.

The Kubernetes Attributes processor enables automatic configuration of spans, metrics, and log resource attributes by using the Kubernetes metadata. This processor supports traces, metrics, and logs. This processor automatically identifies the Kubernetes resources, extracts the metadata from them, and incorporates this extracted metadata as resource attributes into relevant spans, metrics, and logs. It utilizes the Kubernetes API to discover all pods operating within a cluster, maintaining records of their IP addresses, pod UIDs, and other relevant metadata.

Minimum OpenShift Container Platform permissions required for the Kubernetes Attributes processor
kind: ClusterRole
metadata:
  name: otel-collector
rules:
  - apiGroups: ['']
    resources: ['pods', 'namespaces']
    verbs: ['get', 'watch', 'list']
OpenTelemetry Collector using the Kubernetes Attributes processor
  config: |
    processors:
         k8sattributes:
             filter:
                 node_from_env_var: KUBE_NODE_NAME

Filter processor

The Filter processor is currently a Technology Preview feature only.

The Filter processor leverages the OpenTelemetry Transformation Language to establish criteria for discarding telemetry data. If any of these conditions are satisfied, the telemetry data are discarded. The conditions can be combined by using the logical OR operator. This processor supports traces, metrics, and logs.

OpenTelemetry Collector custom resource with an enabled OTLP exporter
config: |
  processors:
    filter/ottl:
      error_mode: ignore (1)
      traces:
        span:
          - 'attributes["container.name"] == "app_container_1"' (2)
          - 'resource.attributes["host.name"] == "localhost"' (3)
1 Defines the error mode. When set to ignore, ignores errors returned by conditions. When set to propagate, returns the error up the pipeline. An error causes the payload to be dropped from the Collector.
2 Filters the spans that have the container.name == app_container_1 attribute.
3 Filters the spans that have the host.name == localhost resource attribute.

Routing processor

The Routing processor is currently a Technology Preview feature only.

The Routing processor routes logs, metrics, or traces to specific exporters. This processor can read a header from an incoming HTTP request (gRPC or plain HTTP) or can read a resource attribute, and then directs the trace information to relevant exporters according to the read value.

OpenTelemetry Collector custom resource with an enabled OTLP exporter
config: |
  processors:
    routing:
      from_attribute: X-Tenant (1)
      default_exporters: (2)
      - jaeger
      table: (3)
      - value: acme
        exporters: [jaeger/acme]
  exporters:
    jaeger:
      endpoint: localhost:14250
    jaeger/acme:
      endpoint: localhost:24250
1 The HTTP header name for the lookup value when performing the route.
2 The default exporter when the attribute value is not present in the table in the next section.
3 The table that defines which values are to be routed to which exporters.

You can optionally create an attribute_source configuratiion, which defines where to look for the attribute in from_attribute. The allowed value is context to search the context, which includes the HTTP headers, or resource to search the resource attributes.

Exporters

Exporters send data to one or more back ends or destinations.

OTLP exporter

The OTLP gRPC exporter exports traces and metrics using the OpenTelemetry protocol (OTLP).

OpenTelemetry Collector custom resource with an enabled OTLP exporter
  config: |
    exporters:
      otlp:
        endpoint: tempo-ingester:4317 (1)
        tls: (2)
          ca_file: ca.pem
          cert_file: cert.pem
          key_file: key.pem
          insecure: false (3)
          insecure_skip_verify: false # (4)
          reload_interval: 1h (5)
          server_name_override: <name> (6)
        headers: (7)
          X-Scope-OrgID: "dev"
    service:
      pipelines:
        traces:
          exporters: [otlp]
        metrics:
          exporters: [otlp]
1 The OTLP gRPC endpoint. If the https:// scheme is used, then client transport security is enabled and overrides the insecure setting in the tls.
2 The client-side TLS configuration. Defines paths to TLS certificates.
3 Disables client transport security when set to true. The default value is false by default.
4 Skips verifying the certificate when set to true. The default value is false.
5 Specifies the time interval at which the certificate is reloaded. If the value is not set, the certificate is never reloaded. The reload_interval accepts a string containing valid units of time such as ns, us (or µs), ms, s, m, h.
6 Overrides the virtual host name of authority such as the authority header field in requests. You can use this for testing.
7 Headers are sent for every request performed during an established connection.
OTLP HTTP exporter

The OTLP HTTP exporter exports traces and metrics using the OpenTelemetry protocol (OTLP).

OpenTelemetry Collector custom resource with an enabled OTLP exporter
  config: |
    exporters:
      otlphttp:
        endpoint: http://tempo-ingester:4318 (1)
        tls: (2)
        headers: (3)
          X-Scope-OrgID: "dev"
        disable_keep_alives: false (4)

    service:
      pipelines:
        traces:
          exporters: [otlphttp]
        metrics:
          exporters: [otlphttp]
1 The OTLP HTTP endpoint. If the https:// scheme is used, then client transport security is enabled and overrides the insecure setting in the tls.
2 The client side TLS configuration. Defines paths to TLS certificates.
3 Headers are sent in every HTTP request.
4 If true, disables HTTP keep-alives. It will only use the connection to the server for a single HTTP request.
Debug exporter

The Debug exporter prints traces and metrics to the standard output.

OpenTelemetry Collector custom resource with an enabled Debug exporter
  config: |
    exporters:
      debug:
        verbosity: detailed (1)
    service:
      pipelines:
        traces:
          exporters: [logging]
        metrics:
          exporters: [logging]
1 Verbosity of the debug export: detailed or normal or basic. When set to detailed, pipeline data is verbosely logged. Defaults to normal.
Prometheus exporter

The Prometheus exporter is currently a Technology Preview feature only.

The Prometheus exporter exports metrics in the Prometheus or OpenMetrics formats.

OpenTelemetry Collector custom resource with an enabled Prometheus exporter
  ports:
  - name: promexporter (1)
    port: 8889
    protocol: TCP
  config: |
    exporters:
      prometheus:
        endpoint: 0.0.0.0:8889 (2)
        tls: (3)
          ca_file: ca.pem
          cert_file: cert.pem
          key_file: key.pem
        namespace: prefix (4)
        const_labels: (5)
          label1: value1
        enable_open_metrics: true (6)
        resource_to_telemetry_conversion: (7)
          enabled: true
        metric_expiration: 180m (8)
        add_metric_suffixes: false (9)
    service:
      pipelines:
        metrics:
          exporters: [prometheus]
1 Exposes the Prometheus port from the Collector pod and service. You can enable scraping of metrics by Prometheus by using the port name in ServiceMonitor or PodMonitor custom resource.
2 The network endpoint where the metrics are exposed.
3 The server-side TLS configuration. Defines paths to TLS certificates.
4 If set, exports metrics under the provided value. No default.
5 Key-value pair labels that are applied for every exported metric. No default.
6 If true, metrics are exported using the OpenMetrics format. Exemplars are only exported in the OpenMetrics format and only for histogram and monotonic sum metrics such as counter. Disabled by default.
7 If enabled is true, all the resource attributes are converted to metric labels by default. Disabled by default.
8 Defines how long metrics are exposed without updates. The default is 5m.
9 Adds the metrics types and units suffixes. Must be disabled if the monitor tab in Jaeger console is enabled. The default is true.
Kafka exporter

The Kafka exporter is currently a Technology Preview feature only.

The Kafka exporter exports logs, metrics, and traces to Kafka. This exporter uses a synchronous producer that blocks and does not batch messages. It must be used with batch and queued retry processors for higher throughput and resiliency.

OpenTelemetry Collector custom resource with an enabled Kafka exporter
  config: |
    exporters:
      kafka:
        brokers: ["localhost:9092"] (1)
        protocol_version: 2.0.0 (2)
        topic: otlp_spans (3)
        auth:
          plain_text: (4)
            username: example
            password: example
          tls: (5)
            ca_file: ca.pem
            cert_file: cert.pem
            key_file: key.pem
            insecure: false (6)
            server_name_override: kafka.example.corp (7)
    service:
      pipelines:
        traces:
          exporters: [kafka]
1 The list of Kafka brokers. The default is localhost:9092.
2 The Kafka protocol version. For example, 2.0.0. This is a required field.
3 The name of the Kafka topic to read from. The following are the defaults: otlp_spans for traces, otlp_metrics for metrics, otlp_logs for logs.
4 The plaintext authentication configuration. If omitted, plaintext authentication is disabled.
5 The client-side TLS configuration. Defines paths to the TLS certificates. If omitted, TLS authentication is disabled.
6 Disables verifying the server’s certificate chain and host name. The default is false.
7 ServerName indicates the name of the server requested by the client to support virtual hosting.

Connectors

Connectors connect two pipelines.

Spanmetrics connector

The Spanmetrics connector is currently a Technology Preview feature only.

The Spanmetrics connector aggregates Request, Error, and Duration (R.E.D) OpenTelemetry metrics from span data.

OpenTelemetry Collector custom resource with an enabled spanmetrics connector
  config: |
    connectors:
      spanmetrics:
        metrics_flush_interval: 15s (1)
    service:
      pipelines:
        traces:
          exporters: [spanmetrics]
        metrics:
          receivers: [spanmetrics]
1 Defines the flush interval of the generated metrics. Defaults to 15s.

Extensions

Extensions add capabilities to the Collector.

BearerTokenAuth extension

The BearerTokenAuth extension is currently a Technology Preview feature only.

The BearerTokenAuth extension is an authenticator for receivers and exporters that are based on the HTTP and the gRPC protocol. You can use the OpenTelemetry Collector custom resource to configure client authentication and server authentication for the BearerTokenAuth extension on the receiver and exporter side. This extension supports traces, metrics, and logs.

OpenTelemetry Collector custom resource with client and server authentication configured for the BearerTokenAuth extension
  config: |
    extensions:
      bearertokenauth:
        scheme: "Bearer" (1)
        token: "<token>" (2)
        filename: "<token_file>" (3)

    receivers:
      otlp:
        protocols:
          http:
            auth:
              authenticator: bearertokenauth (4)
    exporters:
      otlp:
        auth:
          authenticator: bearertokenauth (5)

    service:
      extensions: [bearertokenauth]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 You can configure the BearerTokenAuth extension to send a custom scheme. The default is Bearer.
2 You can add the BearerTokenAuth extension token as metadata to identify a message.
3 Path to a file that contains an authorization token that is transmitted with every message.
4 You can assign the authenticator configuration to an OTLP receiver.
5 You can assign the authenticator configuration to an OTLP exporter.
OAuth2Client extension

The OAuth2Client extension is currently a Technology Preview feature only.

The OAuth2Client extension is an authenticator for exporters that are based on the HTTP and the gRPC protocol. Client authentication for the OAuth2Client extension is configured in a separate section in the OpenTelemetry Collector custom resource. This extension supports traces, metrics, and logs.

OpenTelemetry Collector custom resource with client authentication configured for the OAuth2Client extension
  config: |
    extensions:
      oauth2client:
        client_id: <client_id> (1)
        client_secret: <client_secret> (2)
        endpoint_params: (3)
          audience: <audience>
        token_url: https://example.com/oauth2/default/v1/token (4)
        scopes: ["api.metrics"] (5)
        # tls settings for the token client
        tls: (6)
          insecure: true (7)
          ca_file: /var/lib/mycert.pem (8)
          cert_file: <cert_file> (9)
          key_file: <key_file> (10)
        timeout: 2s (11)

    receivers:
      otlp:
        protocols:
          http:

    exporters:
      otlp:
        auth:
          authenticator: oauth2client (12)

    service:
      extensions: [oauth2client]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 Client identifier, which is provided by the identity provider.
2 Confidential key used to authenticate the client to the identity provider.
3 Further metadata, in the key-value pair format, which is transferred during authentication. For example, audience specifies the intended audience for the access token, indicating the recipient of the token.
4 The URL of the OAuth2 token endpoint, where the Collector requests access tokens.
5 The scopes define the specific permissions or access levels requested by the client.
6 The Transport Layer Security (TLS) settings for the token client, which is used to establish a secure connection when requesting tokens.
7 When set to true, configures the Collector to use an insecure or non-verified TLS connection to call the configured token endpoint.
8 The path to a Certificate Authority (CA) file that is used to verify the server’s certificate during the TLS handshake.
9 The path to the client certificate file that the client must use to authenticate itself to the OAuth2 server if required.
10 The path to the client’s private key file that is used with the client certificate if needed for authentication.
11 Sets a timeout for the token client’s request.
12 You can assign the authenticator configuration to an OTLP exporter.
Jaeger Remote Sampling extension

The Jaeger Remote Sampling extension is currently a Technology Preview feature only.

The Jaeger Remote Sampling extension allows serving sampling strategies after Jaeger’s remote sampling API. You can configure this extension to proxy requests to a backing remote sampling server such as a Jaeger collector down the pipeline or to a static JSON file from the local file system.

OpenTelemetry Collector custom resource with a configured Jaeger Remote Sampling extension
  config: |
    extensions:
      jaegerremotesampling:
        source:
          reload_interval: 30s (1)
          remote:
            endpoint: jaeger-collector:14250 (2)
          file: /etc/otelcol/sampling_strategies.json (3)

    receivers:
      otlp:
        protocols:
          http:

    exporters:
      otlp:

    service:
      extensions: [jaegerremotesampling]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 The time interval at which the sampling configuration is updated.
2 The endpoint for reaching the Jaeger remote sampling strategy provider.
3 The path to a local file that contains a sampling strategy configuration in the JSON format.
Example of a Jaeger Remote Sampling strategy file
{
  "service_strategies": [
    {
      "service": "foo",
      "type": "probabilistic",
      "param": 0.8,
      "operation_strategies": [
        {
          "operation": "op1",
          "type": "probabilistic",
          "param": 0.2
        },
        {
          "operation": "op2",
          "type": "probabilistic",
          "param": 0.4
        }
      ]
    },
    {
      "service": "bar",
      "type": "ratelimiting",
      "param": 5
    }
  ],
  "default_strategy": {
    "type": "probabilistic",
    "param": 0.5,
    "operation_strategies": [
      {
        "operation": "/health",
        "type": "probabilistic",
        "param": 0.0
      },
      {
        "operation": "/metrics",
        "type": "probabilistic",
        "param": 0.0
      }
    ]
  }
}
Performance Profiler extension

The Performance Profiler extension is currently a Technology Preview feature only.

The Performance Profiler extension enables the Go net/http/pprof endpoint. This is typically used by developers to collect performance profiles and investigate issues with the service.

OpenTelemetry Collector custom resource with the configured Performance Profiler extension
  config: |
    extensions:
      pprof:
        endpoint: localhost:1777 (1)
        block_profile_fraction: 0 (2)
        mutex_profile_fraction: 0 (3)
        save_to_file: test.pprof (4)

    receivers:
      otlp:
        protocols:
          http:

    exporters:
      otlp:

    service:
      extensions: [pprof]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 The endpoint at which this extension listens. Use localhost: to make it available only locally or ":" to make it available on all network interfaces. The default value is localhost:1777.
2 Sets a fraction of blocking events to be profiled. To disable profiling, set this to 0 or a negative integer. See the documentation for the runtime package. The default value is 0.
3 Set a fraction of mutex contention events to be profiled. To disable profiling, set this to 0 or a negative integer. See the documentation for the runtime package. The default value is 0.
4 The name of the file in which the CPU profile is to be saved. Profiling starts when the Collector starts. Profiling is saved to the file when the Collector is terminated.
Health Check extension

The Health Check extension is currently a Technology Preview feature only.

The Health Check extension provides an HTTP URL for checking the status of the OpenTelemetry Collector. You can use this extension as a liveness and readiness probe on OpenShift.

OpenTelemetry Collector custom resource with the configured Health Check extension
  config: |
    extensions:
      health_check:
        endpoint: "0.0.0.0:13133" (1)
        tls: (2)
          ca_file: "/path/to/ca.crt"
          cert_file: "/path/to/cert.crt"
          key_file: "/path/to/key.key"
        path: "/health/status" (3)
        check_collector_pipeline: (4)
          enabled: true (5)
          interval: "5m" (6)
          exporter_failure_threshold: 5 (7)

    receivers:
      otlp:
        protocols:
          http:

    exporters:
      otlp:

    service:
      extensions: [health_check]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 The target IP address for publishing the health check status. The default is 0.0.0.0:13133.
2 The TLS server-side configuration. Defines paths to TLS certificates. If omitted, the TLS is disabled.
3 The path for the health check server. The default is /.
4 Settings for the Collector pipeline health check.
5 Enables the Collector pipeline health check. The default is false.
6 The time interval for checking the number of failures. The default is 5m.
7 The threshold of a number of failures until which a container is still marked as healthy. The default is 5.
Memory Ballast extension

The Memory Ballast extension is currently a Technology Preview feature only.

The Memory Ballast extension enables applications to configure memory ballast for the process.

OpenTelemetry Collector custom resource with the configured Memory Ballast extension
  config: |
    extensions:
      memory_ballast:
        size_mib: 64 (1)
        size_in_percentage: 20 (2)

    receivers:
      otlp:
        protocols:
          http:

    exporters:
      otlp:

    service:
      extensions: [memory_ballast]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 Sets the memory ballast size in MiB. Takes priority over the size_in_percentage if both are specified.
2 Sets the memory ballast as a percentage, 1-100, of the total memory. Supports containerized and physical host environments.
zPages extension

The zPages extension is currently a Technology Preview feature only.

The zPages extension provides an HTTP endpoint for extensions that serve zPages. At the endpoint, this extension serves live data for debugging instrumented components. All core exporters and receivers provide some zPages instrumentation.

zPages are useful for in-process diagnostics without having to depend on a back end to examine traces or metrics.

OpenTelemetry Collector custom resource with the configured zPages extension
  config: |
    extensions:
      zpages:
        endpoint: "localhost:55679" (1)

    receivers:
      otlp:
        protocols:
          http:
    exporters:
      otlp:

    service:
      extensions: [zpages]
      pipelines:
        traces:
          receivers: [otlp]
          exporters: [otlp]
1 Specifies the HTTP endpoint that serves zPages. Use localhost: to make it available only locally, or ":" to make it available on all network interfaces. The default is localhost:55679.

Gathering the observability data from different clusters with the OpenTelemetry Collector

For a multicluster configuration, you can create one OpenTelemetry Collector instance in each one of the remote clusters and then forward all the telemetry data to one OpenTelemetry Collector instance.

Prerequisites

  • The Red Hat build of OpenTelemetry Operator is installed.

  • The Tempo Operator is installed.

  • A TempoStack instance is deployed on the cluster.

  • The following mounted certificates: Issuer, self-signed certificate, CA issuer, client and server certificates. To create any of these certificates, see step 1.

Procedure

  1. Mount the following certificates in the OpenTelemetry Collector instance, skipping already mounted certificates.

    1. An Issuer to generate the certificates by using the cert-manager Operator for Red Hat OpenShift.

      apiVersion: cert-manager.io/v1
kind: Issuer
metadata:
  name: selfsigned-issuer
spec:
  selfSigned: {}

    2. A self-signed certificate.

      apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: ca
spec:
  isCA: true
  commonName: ca
  subject:
    organizations:
      - Organization # <your_organization_name>
    organizationalUnits:
      - Widgets
  secretName: ca-secret
  privateKey:
    algorithm: ECDSA
    size: 256
  issuerRef:
    name: selfsigned-issuer
    kind: Issuer
    group: cert-manager.io

    3. A CA issuer.

      apiVersion: cert-manager.io/v1
kind: Issuer
metadata:
  name: test-ca-issuer
spec:
  ca:
    secretName: ca-secret

    4. The client and server certificates.

      apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: server
spec:
  secretName: server-tls
  isCA: false
  usages:
    - server auth
    - client auth
  dnsNames:
  - "otel.observability.svc.cluster.local" (1)
  issuerRef:
    name: ca-issuer
---
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: client
spec:
  secretName: client-tls
  isCA: false
  usages:
    - server auth
    - client auth
  dnsNames:
  - "otel.observability.svc.cluster.local" (2)
  issuerRef:
    name: ca-issuer
      1 List of exact DNS names to be mapped to a solver in the server OpenTelemetry Collector instance.
      2 List of exact DNS names to be mapped to a solver in the client OpenTelemetry Collector instance.

  2. Create a service account for the OpenTelemetry Collector instance.

    Example ServiceAccount
    apiVersion: v1
kind: ServiceAccount
metadata:
  name: otel-collector-deployment

  3. Create a cluster role for the service account.

    Example ClusterRole
    apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: otel-collector
rules:
  (1)
  (2)
- apiGroups: ["", "config.openshift.io"]
  resources: ["pods", "namespaces", "infrastructures", "infrastructures/status"]
  verbs: ["get", "watch", "list"]
    1 The k8sattributesprocessor requires permissions for pods and namespace resources.
    2 The resourcedetectionprocessor requires permissions for infrastructures and status.

  4. Bind the cluster role to the service account.

    Example ClusterRoleBinding
    apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: otel-collector
subjects:
- kind: ServiceAccount
  name: otel-collector-deployment
  namespace: otel-collector-<example>
roleRef:
  kind: ClusterRole
  name: otel-collector
  apiGroup: rbac.authorization.k8s.io

  5. Create the YAML file to define the OpenTelemetryCollector custom resource (CR) in the edge clusters.

    Example OpenTelemetryCollector custom resource for the edge clusters
    apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: otel
  namespace: otel-collector-<example>
spec:
  mode: daemonset
  serviceAccount: otel-collector-deployment
  config: |
    receivers:
      jaeger:
        protocols:
          grpc:
          thrift_binary:
          thrift_compact:
          thrift_http:
      opencensus:
      otlp:
        protocols:
          grpc:
          http:
      zipkin:
    processors:
      batch:
      k8sattributes:
      memory_limiter:
        check_interval: 1s
        limit_percentage: 50
        spike_limit_percentage: 30
      resourcedetection:
        detectors: [openshift]
    exporters:
      otlphttp:
        endpoint: https://observability-cluster.com:443 (1)
        tls:
          insecure: false
          cert_file: /certs/server.crt
          key_file: /certs/server.key
          ca_file: /certs/ca.crt
    service:
      pipelines:
        traces:
          receivers: [jaeger, opencensus, otlp, zipkin]
          processors: [memory_limiter, k8sattributes, resourcedetection, batch]
          exporters: [otlp]
  volumes:
    - name: otel-certs
      secret:
        name: otel-certs
  volumeMounts:
    - name: otel-certs
      mountPath: /certs
    1 The Collector exporter is configured to export OTLP HTTP and points to the OpenTelemetry Collector from the central cluster.

  6. Create the YAML file to define the OpenTelemetryCollector custom resource (CR) in the central cluster.

    Example OpenTelemetryCollector custom resource for the central cluster
    apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: otlp-receiver
  namespace: observability
spec:
  mode: "deployment"
  ingress:
    type: route
    route:
      termination: "passthrough"
  config: |
    receivers:
      otlp:
        protocols:
          http:
            tls: (1)
              cert_file: /certs/server.crt
              key_file: /certs/server.key
              client_ca_file: /certs/ca.crt
    exporters:
      logging:
      otlp:
        endpoint: "tempo-<simplest>-distributor:4317" (2)
        tls:
          insecure: true
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: []
          exporters: [otlp]
  volumes:
    - name: otel-certs
      secret:
        name: otel-certs
  volumeMounts:
    - name: otel-certs
      mountPath: /certs
    1 The Collector receiver requires the certificates listed in the first step.
    2 The Collector exporter is configured to export OTLP and points to the Tempo distributor endpoint, which in this example is "tempo-simplest-distributor:4317" and already created.

Configuration for sending metrics to the monitoring stack

The OpenTelemetry Collector custom resource (CR) can be configured to create a Prometheus ServiceMonitor CR for scraping the Collector’s pipeline metrics and the enabled Prometheus exporters.

Example of the OpenTelemetry Collector custom resource with the Prometheus exporter
spec:
  mode: deployment
  observability:
    metrics:
      enableMetrics: true (1)
  config: |
    exporters:
      prometheus:
        endpoint: 0.0.0.0:8889
        resource_to_telemetry_conversion:
          enabled: true # by default resource attributes are dropped
    service:
      telemetry:
        metrics:
          address: ":8888"
      pipelines:
        metrics:
          receivers: [otlp]
          exporters: [prometheus]
1 Configures the operator to create the Prometheus ServiceMonitor CR to scrape the collector’s internal metrics endpoint and Prometheus exporter metric endpoints. The metrics will be stored in the OpenShift monitoring stack.

Alternatively, a manually created Prometheus PodMonitor can provide fine control, for example removing duplicated labels added during Prometheus scraping.

Example of the PodMonitor custom resource that configures the monitoring stack to scrape the Collector metrics
apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
  name: otel-collector
spec:
  selector:
    matchLabels:
      app.kubernetes.io/name: `<cr_name>-collector` (1)
  podMetricsEndpoints:
  - port: metrics (2)
  - port: promexporter (3)
    relabelings:
    - action: labeldrop
      regex: pod
    - action: labeldrop
      regex: container
    - action: labeldrop
      regex: endpoint
    metricRelabelings:
    - action: labeldrop
      regex: instance
    - action: labeldrop
      regex: job
1 The name of the OpenTelemetry Collector custom resource.
2 The name of the internal metrics port for the OpenTelemetry Collector. This port name is always metrics.
3 The name of the Prometheus exporter port for the OpenTelemetry Collector.

Setting up monitoring for the Red Hat build of OpenTelemetry

The Red Hat build of OpenTelemetry Operator supports monitoring and alerting of each OpenTelemtry Collector instance and exposes upgrade and operational metrics about the Operator itself.

Configuring the OpenTelemetry Collector metrics

You can enable metrics and alerts of OpenTelemetry Collector instances.

Prerequisites

  • Monitoring for user-defined projects is enabled in the cluster.

Procedure

  • To enable metrics of a OpenTelemetry Collector instance, set the spec.observability.metrics.enableMetrics field to true:

    apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: <name>
spec:
  observability:
    metrics:
      enableMetrics: true
Verification

You can use the Administrator view of the web console to verify successful configuration:

  • Go to Observe → Targets, filter by Source: User, and check that the ServiceMonitors in the opentelemetry-collector-<instance_name> format have the Up status.

Additional resources