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Coderabbit Observability

ASecurity

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

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  • Added September 1, 2026
developmenttypescriptapibackenddocumentation

Works with

  • cli
  • api

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A100/100

Scanned September 1, 2026

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SKILL.md
---
name: coderabbit-observability
description: |
  Set up comprehensive observability for CodeRabbit integrations with metrics, traces, and alerts.
  Use when implementing monitoring for CodeRabbit operations, setting up dashboards,
  or configuring alerting for CodeRabbit integration health.
  Trigger with phrases like "coderabbit monitoring", "coderabbit metrics",
  "coderabbit observability", "monitor coderabbit", "coderabbit alerts", "coderabbit tracing".
allowed-tools: Read, Write, Edit
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
---

# CodeRabbit Observability

## Overview
Set up comprehensive observability for CodeRabbit integrations.

## Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured

## Metrics Collection

### Key Metrics
| Metric | Type | Description |
|--------|------|-------------|
| `coderabbit_requests_total` | Counter | Total API requests |
| `coderabbit_request_duration_seconds` | Histogram | Request latency |
| `coderabbit_errors_total` | Counter | Error count by type |
| `coderabbit_rate_limit_remaining` | Gauge | Rate limit headroom |

### Prometheus Metrics

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

const registry = new Registry();

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

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

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

### Instrumented Client

```typescript
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

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

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

async function tracedCodeRabbitCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`coderabbit.${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

```typescript
import pino from 'pino';

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

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

## Alert Configuration

### Prometheus AlertManager Rules

```yaml
# coderabbit_alerts.yaml
groups:
  - name: coderabbit_alerts
    rules:
      - alert: CodeRabbitHighErrorRate
        expr: |
          rate(coderabbit_errors_total[5m]) /
          rate(coderabbit_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "CodeRabbit error rate > 5%"

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

      - alert: CodeRabbitDown
        expr: up{job="coderabbit"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "CodeRabbit integration is down"
```

## Dashboard

### Grafana Panel Queries

```json
{
  "panels": [
    {
      "title": "CodeRabbit Request Rate",
      "targets": [{
        "expr": "rate(coderabbit_requests_total[5m])"
      }]
    },
    {
      "title": "CodeRabbit Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(coderabbit_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
```typescript
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});
```

## Resources
- [Prometheus Best Practices](https://prometheus.io/docs/practices/naming/)
- [OpenTelemetry Documentation](https://opentelemetry.io/docs/)
- [CodeRabbit Observability Guide](https://docs.coderabbit.com/observability)

## Next Steps
For incident response, see `coderabbit-incident-runbook`.

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