Configure Helm for Kubernetes 🔗

After you’ve installed the Collector for Kubernetes, these are the available settings you can configure. Additionally, see also the advanced configuration options and Configure logs and events for Kubernetes.

Caution

The values.yaml file lists all supported configurable parameters for the Helm chart, along with a detailed explanation of each parameter. Review it to understand how to configure this chart.

The Helm chart can also be configured to support different use cases, such as trace sampling and sending data through a proxy server. See Examples of chart configuration for more information.

Configure the Kubernetes distribution 🔗

If applicable, use the distribution parameter to provide information about the underlying Kubernetes deployment. This parameter allows the connector to automatically scrape additional metadata. The following options are supported:

aks for Azure AKS
eks for Amazon EKS
eks/fargate for Amazon EKS with Fargate profiles
gke for Google GKE or Standard mode
gke/autopilot for Google GKE or Autopilot mode
openshift for Red Hat OpenShift

Apply the following to configure your distribution:

# aks deployment
--set distribution=aks,cloudProvider=azure

# eks deployment
--set distribution=eks,cloudProvider=aws

# eks/fargate deployment (with recommended gateway)
--set distribution=eks/fargate,gateway.enabled=true,cloudProvider=aws

# gke deployment
--set distribution=gke,cloudProvider=gcp

# gke/autopilot deployment
--set distribution=gke/autopilot,cloudProvider=gcp

# openshift deployment (openshift can run on multiple cloud providers, so cloudProvider is excluded here)
--set distribution=openshift

For example:

splunkObservability:
  accessToken: xxxxxx
  realm: us0
clusterName: my-k8s-cluster
distribution: gke

Configure Google Kubernetes Engine 🔗

Configure GKE Autopilot 🔗

To run the Collector in GKE Autopilot mode, set the distribution option to gke/autopilot:

distribution: gke/autopilot

Search for “Autopilot overview” on the Google Cloud documentation site for more information.

Note

GKE Autopilot doesn’t support native OpenTelemetry logs collection.

The Collector agent daemonset can have problems scheduling in Autopilot mode. If this happens, do the following to assign the daemonset a higher priority class to ensure that the daemonset pods are always present on each node:

Create a new priority class for the Collector agent:

cat <<EOF | kubectl apply -f -
apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: splunk-otel-agent-priority
value: 1000000
globalDefault: false
description: "Higher priority class for the Splunk Distribution of OpenTelemetry Collector pods."
EOF

Use the created priority class in the helm install/upgrade command using the --set="priorityClassName=splunk-otel-agent-priority" argument, or add the following line to your custom values.yaml:

priorityClassName: splunk-otel-agent-priority

GKE ARM support 🔗

The default configuration of the Helm chart supports ARM workloads on GKE. Make sure to set the distribution value to gke:

distribution: gke

Configure Amazon Elastic Kubernetes Service Fargate 🔗

To run the Collector in the Amazon EKS with Fargate profiles, set the required distribution value to eks/fargate, as shown in the following example:

distribution: eks/fargate

Note

Fluentd and native OpenTelemetry logs collection are not automatically configured in EKS with Fargate profiles.

This distribution operates similarly to the eks distribution, but with the following distinctions:

The Collector agent daemonset is not applied since Fargate does not support daemonsets. Any desired Collector instances running as agents must be configured manually as sidecar containers in your custom deployments. This includes any application logging services like Fluentd. Set gateway.enabled to true and configure your instrumented applications to report metrics, traces, and logs to the gateway <installed-chart-name>-splunk-otel-collector service address. Any desired agent instances that would run as a daemonset should instead run as sidecar containers in your pods.
Since Fargate nodes use a VM boundary to prevent access to host-based resources used by other pods, pods are not able to reach their own kubelet. The cluster receiver for the Fargate distribution has two primary differences between regular eks to work around this limitation:
- The configured cluster receiver is deployed as a two-replica StatefulSet instead of a Deployment, and uses a Kubernetes Observer extension that discovers the cluster’s nodes and, on the second replica, its pods for user-configurable receiver creator additions.Using this observer dynamically creates the Kubelet Stats receiver instances that report kubelet metrics for all observed Fargate nodes. The first replica monitors the cluster with a k8s_cluster receiver, and the second cluster monitors all kubelets except its own (due to an EKS/Fargate networking restriction).
- The first replica’s Collector monitors the second’s kubelet. This is made possible by a Fargate-specific splunk-otel-eks-fargate-kubeletstats-receiver-node node label. The Collector ClusterRole for eks/fargate allows the patch verb on nodes resources for the default API groups to allow the cluster receiver’s init container to add this node label for designated self monitoring.

Configure the deployment environment 🔗

If applicable, use the environment parameter to specify an additional deployment.environment attribute to be added to all telemetry data. This attribute helps Splunk Observability Cloud users investigate data coming from different sources separately. Example values include development, staging, and production.

splunkObservability:
  accessToken: xxxxxx
  realm: us0
environment: production

Configure a cloud provider 🔗

If applicable, use the cloudProvider parameter to provide information about your cloud provider. The following options are supported:

aws for Amazon Web Services
gcp for Google Cloud Platform
azure for Microsoft Azure

To set your cloud provider and configure cloud.platform for the resource detection processor, use:

--set cloudProvider={azure|gcp|eks|openshift}

For example:

splunkObservability:
  accessToken: xxxxxx
  realm: us0
clusterName: my-k8s-cluster
cloudProvider: aws

Activate AlwaysOn Profiling 🔗

AlwaysOn Profiling in Splunk APM continuously captures stack traces, helping you identify performance bottlenecks or issues in your code. Activating profiling lets your Kubernetes applications produce and forward this data to Splunk Observability Cloud for visualization.

The Collector ingests profiling data using the logs pipeline.

Learn more at Splunk OpenTelemetry Zero Configuration Auto Instrumentation and Introduction to AlwaysOn Profiling for Splunk APM.

Set up profiling 🔗

You can activate profiling while installing the Collector for Kubernetes using the UI wizard, or by modifying your configuration files.

Profiling uses two main components: the Collector, responsible for receiving and exporting the profiling data to Splunk Observability Cloud, and the Operator, which auto-instruments applications so they can generate and emit traces along with profiling data.

There are two main scenarios:

Profiling using both Collector and Operator: The Operator auto-instruments your applications, which then send the profiling data to the Collector.
Profiling using only the Collector: You manually instrument your applications to generate profiling data, which is then sent directly to the Collector.

Activate profiling with the Collector and the Operator 🔗

To activate profiling with the Collector and the Operator, activate the Profiling option in the UI, or deploy the Helm chart with the following configuration:

For the Collector:

splunkObservability:
  accessToken: CHANGEME
  realm: us0
  logsEnabled: true
  profilingEnabled: true

For the Operator:

operator:
  enabled: true

Additionally, deploy the cert-manager for the Operator if it hasn’t been already.

certmanager:
  enabled: true

With the above configuration:

The Collector is set up to receive profiling data.
The Operator is deployed and auto-instruments applications based on target pod annotations, allowing these applications to generate profiling data.

Activate profiling only with the Collector 🔗

If you want to only use the Collector and have manually instrumented applications, ensure that splunkObservability.logsEnabled=true and splunkObservability.profilingEnabled=true is set in your configuration.

Caution

With this option, you need to manually set up instrumented applications to send profiling data directly to the Collector.

Provide tokens as a secret 🔗

Instead of having the tokens as clear text in the config file, you can provide them as a secret created before deploying the chart. See secret-splunk.yaml for the required fields.

secret:
  create: false
  name: your-secret

Add additional telemetry sources 🔗

Use the autodetect configuration option to activate additional telemetry sources.

Set autodetect.prometheus=true if you want the Collector to scrape Prometheus metrics from pods that have generic Prometheus-style annotations. Add the following annotations on pods to allow a fine control of the scraping process:

prometheus.io/scrape: true: The default configuration scrapes all pods. If set to false, this annotation excludes the pod from the scraping process.
prometheus.io/path: The path to scrape the metrics from. The default value is /metrics.
prometheus.io/port: The port to scrape the metrics from. The default value is 9090.

If the Collector is running in an Istio environment, set autodetect.istio=true to make sure that all traces, metrics, and logs reported by Istio are collected in a unified manner.

For example, use the following configuration to activate automatic detection of both Prometheus and Istio telemetry sources:

splunkObservability:
  accessToken: xxxxxx
  realm: us0
clusterName: my-k8s-cluster
autodetect:
  istio: true
  prometheus: true

Deactivate particular types of telemetry 🔗

By default, OpenTelemetry sends only metrics and traces to Splunk Observability Cloud and sends only logs to Splunk Platform. You can activate or deactivate any kind of telemetry data collection for a specific destination.

For example, the following configuration allows the Collector to send all collected telemetry data to Splunk Observability Cloud and the Splunk Platform if you’ve properly configured them:

splunkObservability:
  metricsEnabled: true
  tracesEnabled: true
  logsEnabled: true
splunkPlatform:
  metricsEnabled: true
  logsEnabled: true

Configure Windows worker nodes 🔗

The Splunk Distribution of OpenTelemetry Collector for Kubernetes supports collecting metrics, traces, and logs (using OpenTelemetry native logs collection only) from Windows nodes. All Windows images are available in the quay.io/signalfx/splunk-otel-collector-windows repository.

Use the following configuration to install the Helm chart on Windows worker nodes:

isWindows: true
image:
  otelcol:
    repository: quay.io/signalfx/splunk-otel-collector-windows
logsEngine: otel
readinessProbe:
  initialDelaySeconds: 60
livenessProbe:
  initialDelaySeconds: 60

If you have both Windows and Linux worker nodes in your Kubernetes cluster, you need to install the Helm chart twice. One of the installations with the default configuration set to isWindows: false is applied on Linux nodes. The second installation with the values.yaml configuration (shown in the previous example) is applied on Windows nodes.

Deactivate the clusterReceiver on one of the installations to avoid cluster-wide metrics duplication. To do this, add the following lines to the configuration of one of the installations:

clusterReceiver:
  enabled: false

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