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    observability-bootstrapper

    by Markus Isaksson

    Production-grade instrumentation: adds OpenTelemetry tracing, structured logging, RED metrics, and health probes.

    Updated May 2026
    Security scanned
    One-time purchase

    $12

    One-time purchase

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Add OpenTelemetry distributed tracing to a microservice architecture.
    • Implement structured JSON logging with automated PII redaction.
    • network automation included
    • Includes example output and usage patterns
    • Instant install

    See it in action

    Generated src/middleware/tracing.ts (OpenTelemetry SDK initialization with OTLP exporter).
    Updated k8s/deployment.yaml:
    readinessProbe:
      httpGet:
        path: /health/ready
        port: 3000
      initialDelaySeconds: 5
      periodSeconds: 10
    JSON logs now include trace_id and span_id for correlation.

    About This Skill

    What it does

    This skill transforms standard application code into production-ready services by automating the setup of comprehensive observability. It instruments your code with distributed tracing, structured JSON logging, health probes (liveness, readiness, and startup), and RED metrics (Rate, Errors, Duration). It supports major frameworks across Node.js, Python, Go, Java, Ruby, .NET, and PHP.

    How it works

    The skill audits your existing stack and deployment platform (Docker, Kubernetes, ECS, Lambda) to generate specific configuration and middleware. Instead of basic console logs, it implements structured logging with trace ID correlation and automated redaction of sensitive data. It defaults to vendor-neutral OpenTelemetry but also supports Datadog, New Relic, and cloud-native APM tools.

    Why use this skill

    Manual instrumentation is error-prone and tedious. This skill ensures best practices are followed—like preventing high-cardinality label explosions in metrics or skipping health checks in trace sampling—so your on-call engineers can pinpoint failures in minutes. It also generates the necessary infrastructure manifests, such as Kubernetes probe blocks and Docker health checks, ensuring your orchestrator knows exactly when to restart or route traffic away from a failing service.

    📖 Learn more: Best DevOps & Deployment Skills for Claude Code →

    Use Cases

    • Add OpenTelemetry distributed tracing to a microservice architecture.
    • Implement structured JSON logging with automated PII redaction.
    • Configure K8s liveness/readiness probes with dependency health checks.
    • Generate RED method metrics (Rate, Error, Duration) for HTTP endpoints.
    • Scale a service to production with standardized observability scaffolding.

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    $12

    One-time