Anthropic Observability
Overview
Every messages.create call should be instrumented. Track tokens, latency, cost, model, and errors.
Logging Wrapper
import Anthropic from '@claude-ai/sdk';
const client = new Anthropic();
async function trackedCreate(params: Anthropic.MessageCreateParams) {
const start = performance.now();
try {
const message = await client.messages.create(params);
const durationMs = Math.round(performance.now() - start);
const log = {
timestamp: new Date().toISOString(),
model: message.model,
input_tokens: message.usage.input_tokens,
output_tokens: message.usage.output_tokens,
cache_read_tokens: message.usage.cache_read_input_tokens || 0,
duration_ms: durationMs,
stop_reason: message.stop_reason,
estimated_cost: estimateCost(message.model, message.usage),
};
console.log('anthropic_request', JSON.stringify(log));
return message;
} catch (err) {
const durationMs = Math.round(performance.now() - start);
console.error('anthropic_error', JSON.stringify({
timestamp: new Date().toISOString(),
model: params.model,
error_type: err instanceof Anthropic.APIError ? err.error?.type : 'unknown',
status: err instanceof Anthropic.APIError ? err.status : null,
request_id: err instanceof Anthropic.APIError ? err.headers?.['request-id'] : null,
duration_ms: durationMs,
}));
throw err;
}
}
function estimateCost(model: string, usage: Anthropic.Usage): number {
const rates: Record<string, [number, number]> = {
'claude-opus-4-20250514': [15, 75],
'claude-sonnet-4-20250514': [3, 15],
'claude-haiku-4-5-20251001': [0.80, 4],
};
const [inputRate, outputRate] = rates[model] || [3, 15];
return (usage.input_tokens * inputRate + usage.output_tokens * outputRate) / 1_000_000;
}
Key Metrics to Track
| Metric |
Source |
Alert Threshold |
| Error rate |
error logs |
> 5% over 5 minutes |
| p95 latency |
duration_ms |
> 10s (Sonnet) |
| Daily cost |
estimated_cost sum |
> 2x daily average |
| 429 rate |
error_type = rate_limit |
> 10/minute |
| 529 rate |
error_type = overloaded |
> 5/minute |
| Token usage |
input_tokens + output_tokens |
> daily budget |
Anthropic Console Monitoring
- Usage dashboard: console.anthropic.com → Usage
- Spending limits: console.anthropic.com → Settings → Limits
- API logs: Not available via API — use your own logging
Output
- Every Claude API call logged with tokens, latency, cost estimate, and model
- Error calls logged with request ID, status code, and error type
- Metrics dashboarded: error rate, p95 latency, daily cost, 429/529 rates
- Spending alerts configured in Anthropic console
Error Handling
| Error |
Cause |
Solution |
| API Error |
Check error type and status code |
See clade-common-errors |
Examples
See Logging Wrapper with trackedCreate(), estimateCost() function, Key Metrics table with alert thresholds, and Anthropic Console Monitoring section above.
Resources
Next Steps
See clade-incident-runbook for when things go wrong.
Prerequisites
- Completed
clade-install-auth
- Logging infrastructure (console, structured logs, or observability platform)
- Production Claude integration to monitor
Instructions
Step 1: Review the patterns below
Each section contains production-ready code examples. Copy and adapt them to your use case.
Step 2: Apply to your codebase
Integrate the patterns that match your requirements. Test each change individually.
Step 3: Verify
Run your test suite to confirm the integration works correctly.
1---2name: clade-observability3description: Monitor Claude API calls — log tokens, latency, costs, errors, and Use when working with observability patterns. set up alerts for production Claude integrations. Trigger with "anthropic monitoring", "claude observability", "track claude usage", "anthropic logging".4license: MIT5---67# Anthropic Observability89## Overview10Every `messages.create` call should be instrumented. Track tokens, latency, cost, model, and errors.1112## Logging Wrapper13```typescript14import Anthropic from '@claude-ai/sdk';1516const client = new Anthropic();1718async function trackedCreate(params: Anthropic.MessageCreateParams) {19 const start = performance.now();20 try {21 const message = await client.messages.create(params);22 const durationMs = Math.round(performance.now() - start);2324 const log = {25 timestamp: new Date().toISOString(),26 model: message.model,27 input_tokens: message.usage.input_tokens,28 output_tokens: message.usage.output_tokens,29 cache_read_tokens: message.usage.cache_read_input_tokens || 0,30 duration_ms: durationMs,31 stop_reason: message.stop_reason,32 estimated_cost: estimateCost(message.model, message.usage),33 };34 console.log('anthropic_request', JSON.stringify(log));3536 return message;37 } catch (err) {38 const durationMs = Math.round(performance.now() - start);39 console.error('anthropic_error', JSON.stringify({40 timestamp: new Date().toISOString(),41 model: params.model,42 error_type: err instanceof Anthropic.APIError ? err.error?.type : 'unknown',43 status: err instanceof Anthropic.APIError ? err.status : null,44 request_id: err instanceof Anthropic.APIError ? err.headers?.['request-id'] : null,45 duration_ms: durationMs,46 }));47 throw err;48 }49}5051function estimateCost(model: string, usage: Anthropic.Usage): number {52 const rates: Record<string, [number, number]> = {53 'claude-opus-4-20250514': [15, 75],54 'claude-sonnet-4-20250514': [3, 15],55 'claude-haiku-4-5-20251001': [0.80, 4],56 };57 const [inputRate, outputRate] = rates[model] || [3, 15];58 return (usage.input_tokens * inputRate + usage.output_tokens * outputRate) / 1_000_000;59}60```6162## Key Metrics to Track63| Metric | Source | Alert Threshold |64|--------|--------|----------------|65| Error rate | error logs | > 5% over 5 minutes |66| p95 latency | duration_ms | > 10s (Sonnet) |67| Daily cost | estimated_cost sum | > 2x daily average |68| 429 rate | error_type = rate_limit | > 10/minute |69| 529 rate | error_type = overloaded | > 5/minute |70| Token usage | input_tokens + output_tokens | > daily budget |7172## Anthropic Console Monitoring73- **Usage dashboard**: console.anthropic.com → Usage74- **Spending limits**: console.anthropic.com → Settings → Limits75- **API logs**: Not available via API — use your own logging7677## Output78- Every Claude API call logged with tokens, latency, cost estimate, and model79- Error calls logged with request ID, status code, and error type80- Metrics dashboarded: error rate, p95 latency, daily cost, 429/529 rates81- Spending alerts configured in Anthropic console8283## Error Handling84| Error | Cause | Solution |85|-------|-------|----------|86| API Error | Check error type and status code | See `clade-common-errors` |8788## Examples89See Logging Wrapper with `trackedCreate()`, `estimateCost()` function, Key Metrics table with alert thresholds, and Anthropic Console Monitoring section above.9091## Resources92- [Usage Dashboard](https://console.anthropic.com/settings/usage)93- [Rate Limits](https://docs.anthropic.com/en/api/rate-limits)9495## Next Steps96See `clade-incident-runbook` for when things go wrong.9798## Prerequisites99- Completed `clade-install-auth`100- Logging infrastructure (console, structured logs, or observability platform)101- Production Claude integration to monitor102103## Instructions104105### Step 1: Review the patterns below106Each section contains production-ready code examples. Copy and adapt them to your use case.107108### Step 2: Apply to your codebase109Integrate the patterns that match your requirements. Test each change individually.110111### Step 3: Verify112Run your test suite to confirm the integration works correctly.113