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Chapter 3. 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.
3.1. 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.serviceExample 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:
pipelines:
traces:
receivers: [otlp]
processors: []
exporters: [jaeger]
metrics:
receivers: [otlp]
processors: []
exporters: [prometheus]- 1
- If a component is configured but not defined in the
servicesection, the component is not enabled.
| Parameter | Description | Values | Default |
|---|---|---|---|
| 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. |
| None |
| Processors run through the data between it is received and exported. By default, no processors are enabled. |
| None |
| 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. |
| None |
| 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. |
| None |
| Optional components for tasks that do not involve processing telemetry data. |
| None |
| Components are enabled by adding them to a pipeline under | ||
| You enable receivers for tracing by adding them under | None | |
| You enable processors for tracing by adding them under | None | |
| You enable exporters for tracing by adding them under | None | |
| You enable receivers for metrics by adding them under | None | |
| You enable processors for metircs by adding them under | None | |
| You enable exporters for metrics by adding them under | None |
3.1.1. OpenTelemetry Collector components
3.1.1.1. Receivers
Receivers get data into the Collector.
3.1.1.1.1. 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
tls:
ca_file: ca.pem
cert_file: cert.pem
key_file: key.pem
client_ca_file: client.pem
reload_interval: 1h
http:
endpoint: 0.0.0.0:4318
tls:
service:
pipelines:
traces:
receivers: [otlp]
metrics:
receivers: [otlp]- 1
- The OTLP gRPC endpoint. If omitted, the default
0.0.0.0:4317is 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
ClientCAsandClientAuthtoRequireAndVerifyClientCertin theTLSConfig. For more information, see theConfigof 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_intervalaccepts a string containing valid units of time such asns,us(orµs),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
grpcprotocol configuration section.
3.1.1.1.2. 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
thrift_http:
endpoint: 0.0.0.0:14268
thrift_compact:
endpoint: 0.0.0.0:6831
thrift_binary:
endpoint: 0.0.0.0:6832
tls:
service:
pipelines:
traces:
receivers: [jaeger]- 1
- The Jaeger gRPC endpoint. If omitted, the default
0.0.0.0:14250is used. - 2
- The Jaeger Thrift HTTP endpoint. If omitted, the default
0.0.0.0:14268is used. - 3
- The Jaeger Thrift Compact endpoint. If omitted, the default
0.0.0.0:6831is used. - 4
- The Jaeger Thrift Binary endpoint. If omitted, the default
0.0.0.0:6832is used. - 5
- The server-side TLS configuration. See the OTLP receiver configuration section for more details.
3.1.1.1.3. 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:
- job_name: 'my-app'
scrape_interval: 5s
static_configs:
- targets: ['my-app.example.svc.cluster.local:8888']
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-appapplication in theexampleproject.
3.1.1.1.4. 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
tls:
service:
pipelines:
traces:
receivers: [zipkin]3.1.1.1.5. 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"]
protocol_version: 2.0.0
topic: otlp_spans
auth:
plain_text:
username: example
password: example
tls:
ca_file: ca.pem
cert_file: cert.pem
key_file: key.pem
insecure: false
server_name_override: kafka.example.corp
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.
3.1.1.1.6. 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
tls:
cors_allowed_origins:
- 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 thecors_allowed_origins. To match any origin, enter only*.
3.1.1.2. Processors
Processors run through the data between it is received and exported.
3.1.1.2.1. 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]| Parameter | Description | Default |
|---|---|---|
| Sends the batch after a specific time duration and irrespective of the batch size. |
|
| Sends the batch of telemetry data after the specified number of spans or metrics. |
|
| The maximum allowable size of the batch. Must be equal or greater than the |
|
| When activated, a batcher instance is created for each unique set of values found in the |
|
| When the |
|
3.1.1.2.2. 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]| Parameter | Description | Default |
|---|---|---|
| Time between memory usage measurements. The optimal value is |
|
| 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. |
|
| Spike limit, which is the maximum expected spike of memory usage in MiB. The optimal value is approximately 20% of | 20% of |
| Same as the |
|
| Same as the |
|
3.1.1.2.3. 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_ATTRIBUTESOpenShift 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]
timeout: 2s
override: false- 1
- Specifies which detector to use. In this example, the environment detector is specified.
3.1.1.2.4. 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_attributessetting 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: int3.1.1.2.5. 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: deleteAttributes represent the actions that are applied to the resource attributes, such as delete the attribute, insert the attribute, or upsert the attribute.
3.1.1.2.6. 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_attributesOpenTelemetry Collector using the Span processor for renaming a span
config: |
processor:
span:
name:
from_attributes: [<key1>, <key2>, ...]
separator: <value> 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
- 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
documentIDattibute is created. In this example, if the input span name is/api/v1/document/12345678/update, this results in the/api/v1/document/{documentId}/updateoutput 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>"3.1.1.2.7. 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_NAME3.1.1.3. 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
traces:
span:
- 'attributes["container.name"] == "app_container_1"'
- 'resource.attributes["host.name"] == "localhost"' - 1
- Defines the error mode. When set to
ignore, ignores errors returned by conditions. When set topropagate, 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_1attribute. - 3
- Filters the spans that have the
host.name == localhostresource attribute.
3.1.1.4. 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
default_exporters:
- jaeger
table:
- value: acme
exporters: [jaeger/acme]
exporters:
jaeger:
endpoint: localhost:14250
jaeger/acme:
endpoint: localhost:24250You can optionally create an
attribute_sourcefrom_attributecontextresource3.1.1.5. Exporters
Exporters send data to one or more back ends or destinations.
3.1.1.5.1. 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
tls:
ca_file: ca.pem
cert_file: cert.pem
key_file: key.pem
insecure: false
insecure_skip_verify: false #
reload_interval: 1h
server_name_override: <name>
headers:
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 theinsecuresetting in thetls. - 2
- The client-side TLS configuration. Defines paths to TLS certificates.
- 3
- Disables client transport security when set to
true. The default value isfalseby default. - 4
- Skips verifying the certificate when set to
true. The default value isfalse. - 5
- Specifies the time interval at which the certificate is reloaded. If the value is not set, the certificate is never reloaded. The
reload_intervalaccepts a string containing valid units of time such asns,us(orµs),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.
3.1.1.5.2. 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
tls:
headers:
X-Scope-OrgID: "dev"
disable_keep_alives: false
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 theinsecuresetting in thetls. - 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.
3.1.1.5.3. 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
service:
pipelines:
traces:
exporters: [logging]
metrics:
exporters: [logging]- 1
- Verbosity of the debug export:
detailedornormalorbasic. When set todetailed, pipeline data is verbosely logged. Defaults tonormal.
3.1.1.5.4. 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
port: 8889
protocol: TCP
config: |
exporters:
prometheus:
endpoint: 0.0.0.0:8889
tls:
ca_file: ca.pem
cert_file: cert.pem
key_file: key.pem
namespace: prefix
const_labels:
label1: value1
enable_open_metrics: true
resource_to_telemetry_conversion:
enabled: true
metric_expiration: 180m
add_metric_suffixes: false
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
ServiceMonitororPodMonitorcustom 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 ascounter. Disabled by default. - 7
- If
enabledistrue, 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.
3.1.1.5.5. 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"]
protocol_version: 2.0.0
topic: otlp_spans
auth:
plain_text:
username: example
password: example
tls:
ca_file: ca.pem
cert_file: cert.pem
key_file: key.pem
insecure: false
server_name_override: kafka.example.corp
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_spansfor traces,otlp_metricsfor metrics,otlp_logsfor 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.
3.1.1.6. Connectors
Connectors connect two pipelines.
3.1.1.6.1. 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
service:
pipelines:
traces:
exporters: [spanmetrics]
metrics:
receivers: [spanmetrics]- 1
- Defines the flush interval of the generated metrics. Defaults to
15s.
3.1.1.7. Extensions
Extensions add capabilities to the Collector.
3.1.1.7.1. 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"
token: "<token>"
filename: "<token_file>"
receivers:
otlp:
protocols:
http:
auth:
authenticator: bearertokenauth
exporters:
otlp:
auth:
authenticator: bearertokenauth
service:
extensions: [bearertokenauth]
pipelines:
traces:
receivers: [otlp]
exporters: [otlp]- 1
- You can configure the BearerTokenAuth extension to send a custom
scheme. The default isBearer. - 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.
3.1.1.7.2. 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>
client_secret: <client_secret>
endpoint_params:
audience: <audience>
token_url: https://example.com/oauth2/default/v1/token
scopes: ["api.metrics"]
# tls settings for the token client
tls:
insecure: true
ca_file: /var/lib/mycert.pem
cert_file: <cert_file>
key_file: <key_file>
timeout: 2s
receivers:
otlp:
protocols:
http:
exporters:
otlp:
auth:
authenticator: oauth2client
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,
audiencespecifies 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.
3.1.1.7.3. 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
remote:
endpoint: jaeger-collector:14250
file: /etc/otelcol/sampling_strategies.json
receivers:
otlp:
protocols:
http:
exporters:
otlp:
service:
extensions: [jaegerremotesampling]
pipelines:
traces:
receivers: [otlp]
exporters: [otlp]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
}
]
}
}3.1.1.7.4. Performance Profiler extension
The Performance Profiler extension is currently a Technology Preview feature only.
The Performance Profiler extension enables the Go
net/http/pprofOpenTelemetry Collector custom resource with the configured Performance Profiler extension
config: |
extensions:
pprof:
endpoint: localhost:1777
block_profile_fraction: 0
mutex_profile_fraction: 0
save_to_file: test.pprof
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 islocalhost:1777. - 2
- Sets a fraction of blocking events to be profiled. To disable profiling, set this to
0or a negative integer. See the documentation for theruntimepackage. The default value is0. - 3
- Set a fraction of mutex contention events to be profiled. To disable profiling, set this to
0or a negative integer. See the documentation for theruntimepackage. The default value is0. - 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.
3.1.1.7.5. 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"
tls:
ca_file: "/path/to/ca.crt"
cert_file: "/path/to/cert.crt"
key_file: "/path/to/key.key"
path: "/health/status"
check_collector_pipeline:
enabled: true
interval: "5m"
exporter_failure_threshold: 5
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.
3.1.1.7.6. 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
size_in_percentage: 20
receivers:
otlp:
protocols:
http:
exporters:
otlp:
service:
extensions: [memory_ballast]
pipelines:
traces:
receivers: [otlp]
exporters: [otlp]3.1.1.7.7. 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"
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 islocalhost:55679.
3.2. 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
Mount the following certificates in the OpenTelemetry Collector instance, skipping already mounted certificates.
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: {}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.ioA CA issuer.
apiVersion: cert-manager.io/v1 kind: Issuer metadata: name: test-ca-issuer spec: ca: secretName: ca-secretThe 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
Create a service account for the OpenTelemetry Collector instance.
Example ServiceAccount
apiVersion: v1 kind: ServiceAccount metadata: name: otel-collector-deploymentCreate 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"]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.ioCreate the YAML file to define the
custom resource (CR) in the edge clusters.OpenTelemetryCollectorExample
OpenTelemetryCollectorcustom resource for the edge clustersapiVersion: 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:4431 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.
Create the YAML file to define the
custom resource (CR) in the central cluster.OpenTelemetryCollectorExample
OpenTelemetryCollectorcustom resource for the central clusterapiVersion: 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
3.3. Configuration for sending metrics to the monitoring stack
The OpenTelemetry Collector custom resource (CR) can be configured to create a Prometheus
ServiceMonitorExample of the OpenTelemetry Collector custom resource with the Prometheus exporter
spec:
mode: deployment
observability:
metrics:
enableMetrics: true
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
ServiceMonitorCR 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
PodMonitorExample 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`
podMetricsEndpoints:
- port: metrics
- port: promexporter
relabelings:
- action: labeldrop
regex: pod
- action: labeldrop
regex: container
- action: labeldrop
regex: endpoint
metricRelabelings:
- action: labeldrop
regex: instance
- action: labeldrop
regex: job3.4. 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.
3.4.1. 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
field tospec.observability.metrics.enableMetrics:trueapiVersion: 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 format have the Up status.opentelemetry-collector-<instance_name>
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