Rocketlog enriches your logs by attaching deployment and Kubernetes instance context so you can correlate issues with a specific deploy or pod without digging through raw metadata.

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What we add

  • Deployment — Which deployment or release the log line belongs to (e.g. from CI/CD or Git SHA).
  • Kubernetes instance ID — Which pod or node produced the log, so you can tie logs to a specific instance in your cluster.
Enriched logs appear in the Rocketlog UI with these tags. When you pick a time window and use AI root cause analysis, you can filter and group by deployment or instance to see what changed or which node was affected.

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How it works

Rocketlog uses OpenTelemetry resource attributes and standard semantic conventions where possible:
  • Deployment — We look for attributes such as deployment.environment, service.version, or your CI/CD–injected deployment ID. You can set these in your SDK or via the OpenTelemetry resource (e.g. OTEL_RESOURCE_ATTRIBUTES=service.version=1.2.3,deployment.environment=prod).
  • Kubernetes — When you run in Kubernetes, the OpenTelemetry collector or SDK can add k8s.pod.name, k8s.node.name, k8s.namespace.name, etc. We use these to tag logs with the relevant instance and node.
No extra app code is required if your telemetry pipeline already attaches these resource attributes. If not, add them in your collector or SDK configuration.

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Setting resource attributes

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In your app (Python)

export OTEL_RESOURCE_ATTRIBUTES="service.version=1.2.3,deployment.environment=production"
opentelemetry-instrument python app.py

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In your app (Node.js)

export OTEL_RESOURCE_ATTRIBUTES="service.version=1.2.3,deployment.environment=production"
node --require '@opentelemetry/auto-instrumentations-node/register' app.js

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In Kubernetes

If you use the OpenTelemetry Operator or a sidecar collector, configure the collector to add Kubernetes attributes (pod name, node name, namespace) to the resource. Rocketlog will then tag logs with the corresponding Kubernetes instance ID and deployment context when available.

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Using enriched logs in Rocketlog

  1. Open the Rocketlog dashboard and select a time window.
  2. In logs view, filter or group by deployment or instance (e.g. pod name).
  3. Use AI root cause analysis; the model can use these tags to narrow down which deployment or instance was involved.
This makes it easier to answer questions like “what changed in deployment 1.2.3?” or “which pod was failing at that time?”