| 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
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
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('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
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
# 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
{
"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
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
Resources
Next Steps
For incident response, see coderabbit-incident-runbook.