OpenTelemetry - Kestrel AI

The OpenTelemetry integration enables the Kestrel Operator to receive and store OTLP metrics from your OpenTelemetry Collectors. These metrics are used during incident root cause analysis to correlate infrastructure and application performance data with Kubernetes events.

Prerequisites

Kestrel Operator deployed in your cluster (see Kubernetes)
OpenTelemetry Collector deployed in your cluster with the k8sattributes processor

The k8sattributes processor is required for metrics to include Kubernetes context (namespace, workload, pod names). Without it, the operator cannot map metrics to workloads and RCA agents cannot correlate metrics with Kubernetes resources.

Setup

Enable OpenTelemetry in the operator

During cluster onboarding, select OpenTelemetry as the Metrics Source in the Kestrel Dashboard.Alternatively, configure via Helm values:

operator:
  otel:
    enabled: true
    receiverPort: 4317
  metricsStore:
    retention: "30m"
    maxSeries: 100000
    ringSize: 60

Configure the k8sattributes processor

Ensure your OTEL Collector has the k8sattributes processor configured:

processors:
  k8sattributes:
    auth_type: "serviceAccount"
    passthrough: false
    extract:
      metadata:
        - k8s.namespace.name
        - k8s.pod.name
        - k8s.pod.uid
        - k8s.deployment.name
        - k8s.statefulset.name
        - k8s.daemonset.name
        - k8s.replicaset.name
        - k8s.container.name
        - k8s.node.name
    pod_association:
      - sources:
          - from: resource_attribute
            name: k8s.pod.ip
          - from: resource_attribute
            name: ip
          - from: connection

Point the collector at the Kestrel Operator

Add a Kestrel exporter to your OTEL Collector config:

exporters:
  otlp/kestrel:
    endpoint: kestrel-operator.kestrel-ai.svc.cluster.local:4317
    tls:
      insecure: true

service:
  pipelines:
    metrics:
      receivers: [otlp, prometheus]
      processors: [k8sattributes, batch]
      exporters: [otlp/kestrel]

The operator supports gzip compression. The OTEL Collector enables gzip by default. If using the Go SDK directly, enable it via OTEL_EXPORTER_OTLP_COMPRESSION=gzip.

How It’s Used

In Workflows

Action blocks: Query stored OTEL metrics as workflow steps to check thresholds, compare metric values, or enrich workflow context with performance data

In Incident Response

Metrics correlation — during root cause analysis, Kestrel queries stored OTEL metrics for CPU, memory, network, and application-level metrics around the incident timeframe
Workload-aware queries — thanks to k8sattributes, metrics are queryable by namespace, deployment, pod, and container

In Cloud AI Copilot

Ask questions that leverage your OpenTelemetry metrics:

What was the request latency for the API service in the last 30 minutes?
Show me CPU usage trends for the payments namespace
Are there any workloads with high error rates right now?

Configuration Reference

Key	Type	Default	Description
`operator.otel.enabled`	boolean	`false`	Enable OTLP gRPC receiver
`operator.otel.receiverPort`	integer	`4317`	OTLP gRPC receiver port
`operator.metricsStore.retention`	string	`"30m"`	Rolling retention window
`operator.metricsStore.maxSeries`	integer	`100000`	Max unique metric series
`operator.metricsStore.ringSize`	integer	`60`	Data points per series

​Prerequisites

​Setup

​How It’s Used

​In Workflows

​In Incident Response

​In Cloud AI Copilot

​Configuration Reference

Prerequisites

Setup

How It’s Used

In Workflows

In Incident Response

In Cloud AI Copilot

Configuration Reference