Skills Artificial Intelligence Claude API Observability Logging Wrapper

Claude API Observability Logging Wrapper

v20260423
clade-observability
A logging wrapper designed to instrument and monitor calls to the Claude API. It automatically tracks critical metrics including token usage, API latency, estimated cost, and error details. Essential for implementing robust observability patterns and setting up proactive alerts in production environments.
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Overview

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

MetricSourceAlert Threshold
Error rateerror logs> 5% over 5 minutes
p95 latencyduration_ms> 10s (Sonnet)
Daily costestimated_cost sum> 2x daily average
429 rateerrortype = ratelimit> 10/minute
529 rateerror_type = overloaded> 5/minute
Token usageinputtokens + outputtokens> 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

ErrorCauseSolution
API ErrorCheck error type and status codeSee 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.

Info
Name clade-observability
Version v20260423
Size 3.05KB
Updated At 2026-04-27
Language