anthropic-observability

Set up comprehensive observability for Anthropic integrations with metrics, traces, and alerts. Use when implementing monitoring for Anthropic operations, setting up dashboards, or configuring alerting for Anthropic integration health. Trigger with phrases like "anthropic monitoring", "anthropic metrics", "anthropic observability", "monitor anthropic", "anthropic alerts", "anthropic tracing".

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anthropic-pack Plugin
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anthropic-pack

Claude Code skill pack for Anthropic (30 skills)

saas packs v1.0.0
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Installation

This skill is included in the anthropic-pack plugin:

/plugin install anthropic-pack@claude-code-plugins-plus

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Instructions

Anthropic Observability

Overview

Set up comprehensive observability for Anthropic integrations.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed
  • Grafana or similar dashboarding tool
  • AlertManager configured

Metrics Collection

Key Metrics

Metric Type Description
anthropicrequeststotal Counter Total API requests
anthropicrequestduration_seconds Histogram Request latency
anthropicerrorstotal Counter Error count by type
anthropicratelimit_remaining Gauge Rate limit headroom

Prometheus Metrics


import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'anthropic_requests_total',
  help: 'Total Anthropic API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'anthropic_request_duration_seconds',
  help: 'Anthropic request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'anthropic_errors_total',
  help: 'Anthropic errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});

Instrumented Client


async function instrumentedRequest<T>(
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = requestDuration.startTimer({ method });

  try {
    const result = await operation();
    requestCounter.inc({ method, status: 'success' });
    return result;
  } catch (error: any) {
    requestCounter.inc({ method, status: 'error' });
    errorCounter.inc({ error_type: error.code || 'unknown' });
    throw error;
  } finally {
    timer();
  }
}

Distributed Tracing

OpenTelemetry Setup


import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('anthropic-client');

async function tracedAnthropicCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`anthropic.${operationName}`, async (span) => {
    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Logging Strategy

Structured Logging


import pino from 'pino';

const logger = pino({
  name: 'anthropic',
  level: process.env.LOG_LEVEL || 'info',
});

function logAnthropicOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'anthropic',
    operation,
    duration_ms: duration,
    ...data,
  });
}

Alert Configuration

Prometheus AlertManager Rules


# anthropic_alerts.yaml
groups:
  - name: anthropic_alerts
    rules:
      - alert: AnthropicHighErrorRate
        expr: |
          rate(anthropic_errors_total[5m]) /
          rate(anthropic_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Anthropic error rate > 5%"

      - alert: AnthropicHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(anthropic_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Anthropic P95 latency > 2s"

      - alert: AnthropicDown
        expr: up{job="anthropic"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Anthropic integration is down"

Dashboard

Grafana Panel Queries


{
  "panels": [
    {
      "title": "Anthropic Request Rate",
      "targets": [{
        "expr": "rate(anthropic_requests_total[5m])"
      }]
    },
    {
      "title": "Anthropic Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(anthropic_request_duration_seconds_bucket[5m]))"
      }]
    }
  ]
}

Instructions

Step 1: Set Up Metrics Collection

Implement Prometheus counters, histograms, and gauges for key operations.

Step 2: Add Distributed Tracing

Integrate OpenTelemetry for end-to-end request tracing.

Step 3: Configure Structured Logging

Set up JSON logging with consistent field names.

Step 4: Create Alert Rules

Define Prometheus alerting rules for error rates and latency.

Output

  • Metrics collection enabled
  • Distributed tracing configured
  • Structured logging implemented
  • Alert rules deployed

Error Handling

Issue Cause Solution
Missing metrics No instrumentation Wrap client calls
Trace gaps Missing propagation Check context headers
Alert storms Wrong thresholds Tune alert rules
High cardinality Too many labels Reduce label values

Examples

Quick Metrics Endpoint


app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Resources

Next Steps

For incident response, see anthropic-incident-runbook.

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