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Getting Started - PaaS Full Observability

Coming Soon

This feature is currently being tested internally and is not yet available. The documentation here describes the planned functionality. We'll announce when it's ready for use.

If you are new to OpenTelemetry, start with the OpenTelemetry tutorial, which covers what OTel is and how telemetry flows through Platon. This page covers only the PaaS-specific setup.

For the full set of signals — logs, metrics, and traces — instrument your application with OpenTelemetry and send data over OTLP.

What OTLP gives you​

Beyond stdout logging, OpenTelemetry instrumentation provides:

  • Metrics — application-specific measurements (request counts, latencies, custom business metrics).
  • Traces — distributed tracing across services, with request flow and timing.
  • Structured logs — logs correlated with traces.

Prerequisites​

  • Application running on Platon PaaS
  • Tenant set up by Platon team (see PaaS Logging for how to request this)

Instrument your application​

Add the OpenTelemetry SDK to your application. The exact steps depend on your language:

Configure the exporter​

Point your OTLP exporter to the in-cluster Alloy collector. Set these environment variables in your deployment:

env:
  - name: OTEL_EXPORTER_OTLP_ENDPOINT
    value: "http://alloy.alloy.svc.cluster.local:4318"
  - name: OTEL_EXPORTER_OTLP_PROTOCOL
    value: "http/protobuf"
  - name: OTEL_SERVICE_NAME
    value: "your-service-name"
  - name: OTEL_RESOURCE_ATTRIBUTES
    value: "service.version=1.0.0"
Tenancy is handled by Alloy

You do not configure the tenant in your application. Alloy (the in-cluster collector) assigns telemetry to a tenant based on the Kubernetes namespace your workload runs in. Your application exports OTLP to Alloy, and the rest is automatic.

Available ports​

ProtocolPortUse case
OTLP/HTTP4318Recommended (simpler, works everywhere)
OTLP/gRPC4317When gRPC is specifically needed

View your data​

Once your application is instrumented:

  1. Logs — Explore, then select your Loki data source.
  2. Metrics — Explore, then select your Mimir data source.
  3. Traces — Explore, then select your Tempo data source.

All three data sources are pre-configured in your Grafana organization.

Next steps​

  • Logs — search and filter your logs.
  • Metrics — working with metrics data.
  • Traces — working with distributed traces.
  • Alerting — notifications when something goes wrong.