miro-observability
Set up comprehensive observability for Miro integrations with metrics, traces, and alerts. Use when implementing monitoring for Miro operations, setting up dashboards, or configuring alerting for Miro integration health. Trigger with phrases like "miro monitoring", "miro metrics", "miro observability", "monitor miro", "miro alerts", "miro tracing".
Allowed Tools
Provided by Plugin
miro-pack
Claude Code skill pack for Miro (24 skills)
Installation
This skill is included in the miro-pack plugin:
/plugin install miro-pack@claude-code-plugins-plus
Click to copy
Instructions
Miro Observability
Overview
Set up comprehensive observability for Miro integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
mirorequeststotal |
Counter | Total API requests |
mirorequestduration_seconds |
Histogram | Request latency |
miroerrorstotal |
Counter | Error count by type |
miroratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'miro_requests_total',
help: 'Total Miro API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'miro_request_duration_seconds',
help: 'Miro request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'miro_errors_total',
help: 'Miro 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('miro-client');
async function tracedMiroCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`miro.${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: 'miro',
level: process.env.LOG_LEVEL || 'info',
});
function logMiroOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'miro',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# miro_alerts.yaml
groups:
- name: miro_alerts
rules:
- alert: MiroHighErrorRate
expr: |
rate(miro_errors_total[5m]) /
rate(miro_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Miro error rate > 5%"
- alert: MiroHighLatency
expr: |
histogram_quantile(0.95,
rate(miro_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Miro P95 latency > 2s"
- alert: MiroDown
expr: up{job="miro"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Miro integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Miro Request Rate",
"targets": [{
"expr": "rate(miro_requests_total[5m])"
}]
},
{
"title": "Miro Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(miro_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 miro-incident-runbook.