| name | supabase-observability |
| description | Set up comprehensive observability for Supabase integrations with metrics, traces, and alerts. Use when implementing monitoring for Supabase operations, setting up dashboards, or configuring alerting for Supabase integration health. Trigger with phrases like "supabase monitoring", "supabase metrics", "supabase observability", "monitor supabase", "supabase alerts", "supabase tracing". |
| allowed-tools | Read, Write, Edit |
| version | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
Supabase Observability
Overview
Set up comprehensive observability for Supabase integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
supabase_requests_total |
Counter | Total API requests |
supabase_request_duration_seconds |
Histogram | Request latency |
supabase_errors_total |
Counter | Error count by type |
supabase_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: 'supabase_requests_total',
help: 'Total Supabase API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'supabase_request_duration_seconds',
help: 'Supabase request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'supabase_errors_total',
help: 'Supabase 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('supabase-client');
async function tracedSupabaseCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`supabase.${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: 'supabase',
level: process.env.LOG_LEVEL || 'info',
});
function logSupabaseOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'supabase',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# supabase_alerts.yaml
groups:
- name: supabase_alerts
rules:
- alert: SupabaseHighErrorRate
expr: |
rate(supabase_errors_total[5m]) /
rate(supabase_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Supabase error rate > 5%"
- alert: SupabaseHighLatency
expr: |
histogram_quantile(0.95,
rate(supabase_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Supabase P95 latency > 2s"
- alert: SupabaseDown
expr: up{job="supabase"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Supabase integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Supabase Request Rate",
"targets": [{
"expr": "rate(supabase_requests_total[5m])"
}]
},
{
"title": "Supabase Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(supabase_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 supabase-incident-runbook.