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".
Allowed Tools
Provided by Plugin
anthropic-pack
Claude Code skill pack for Anthropic (30 skills)
Installation
This skill is included in the anthropic-pack plugin:
/plugin install anthropic-pack@claude-code-plugins-plus
Click to copy
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.