Quickstart

Go from zero to full cluster observability in 5 minutes.

Prerequisites

A running Kubernetes cluster (any provider)
kubectl configured and pointing to the cluster
An Obtrace API key (obt_live_...)

Step 1: Install the CLI

curl -fsSL https://github.com/obtrace/obtrace-zero/releases/latest/download/obtrace-zero-$(uname -s | tr '[:upper:]' '[:lower:]')-$(uname -m) \
  -o /usr/local/bin/obtrace-zero && chmod +x /usr/local/bin/obtrace-zero

Verify:

obtrace-zero version
# obtrace-zero v0.1.0

Step 2: Discover what would be instrumented

Before installing anything, see what the operator would do:

obtrace-zero discover

NAMESPACE    NAME              KIND         LANGUAGE  FRAMEWORK  STRATEGY  IMAGE
production   checkout-api      Deployment   nodejs    nextjs     sdk       node:20-alpine
production   payment-svc       Deployment   java      spring     sdk       eclipse-temurin:21
production   api-gateway       Deployment   go                   ebpf      my-registry/gateway:v2
staging      ml-pipeline       Deployment   python    fastapi    sdk       python:3.12-slim

4 workloads discovered. Run 'obtrace-zero install --api-key=xxx' to instrument them.

This is a dry run — nothing is installed yet.

Step 3: Install the operator

obtrace-zero install --api-key=obt_live_xxx

The CLI will:

Check cluster connectivity
Install the operator via Helm (falls back to kubectl apply if Helm is not available)
Create the obtrace-system namespace
Deploy the webhook, RBAC, and default ObtraceInstrumentation

Output:

🔍 Checking cluster connectivity...
📦 Installing obtrace-zero operator...

✅ obtrace-zero installed successfully!
   Operator is now watching for pods and auto-instrumenting.
   Strategy: auto
   Ingest: https://ingest-edge.obtrace.svc.cluster.local:8080
   Namespaces: all (cluster-wide)

   Run 'obtrace-zero status' to check instrumentation state.

Step 4: Trigger a rollout

Existing Pods are not modified — instrumentation is applied on Pod creation. Trigger a rollout restart to instrument existing workloads:

kubectl rollout restart deployment -n production

New Pods will be created with instrumentation automatically injected.

Step 5: Verify

obtrace-zero status

Operator:
NAMESPACE        NAME                              READY   STATUS    AGE
obtrace-system   obtrace-zero-operator-7f8b9...    1/1     Running   2m

Instrumented Pods:
NAMESPACE    NAME                         LANGUAGE  STRATEGY  FRAMEWORK
production   checkout-api-6b8f9...        nodejs    sdk       nextjs
production   payment-svc-8a2c4...         java      sdk       spring
production   api-gateway-3c7d1...         go        ebpf
staging      ml-pipeline-5d9e2...         python    sdk       fastapi

You can also check individual Pods:

kubectl get pods -l obtrace.io/instrumented=true --all-namespaces

Or inspect annotations on a specific Pod:

kubectl get pod checkout-api-6b8f9 -n production -o jsonpath='{.metadata.annotations}' | jq

{
  "obtrace.io/injected": "true",
  "obtrace.io/detected-language": "nodejs",
  "obtrace.io/strategy": "sdk",
  "obtrace.io/detected-framework": "nextjs"
}

Step 6: See telemetry in the Obtrace dashboard

Open the Obtrace frontend. Within seconds of the rollout completing, you will see:

Traces — HTTP server spans for every inbound request, with method, route, status code, and duration
Logs — Errors, warnings, and uncaught exceptions with stack traces, correlated to the trace that caused them
Metrics — Memory usage, CPU time, GC pressure, and HTTP latency histograms per service

All of this without touching application code.

Scoping to specific namespaces

If you prefer to instrument only specific namespaces:

obtrace-zero install --api-key=obt_live_xxx --namespaces=production,staging

Or instrument one namespace at a time:

obtrace-zero instrument --namespace=production --api-key=obt_live_xxx

Choosing a strategy

By default, Obtrace Zero uses auto — SDK for interpreted languages, eBPF for compiled. You can force a specific strategy:

obtrace-zero install --api-key=obt_live_xxx --strategy=ebpf

See Strategies for details on when to use each.

Next steps

How it works — understand the mutation and injection flow
Language agents — what each agent captures
CRD reference — advanced configuration via GitOps
Troubleshooting — common issues and fixes

Quickstart

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