figma-observability
Set up comprehensive observability for Figma integrations with metrics, traces, and alerts. Use when implementing monitoring for Figma operations, setting up dashboards, or configuring alerting for Figma integration health. Trigger with phrases like "figma monitoring", "figma metrics", "figma observability", "monitor figma", "figma alerts", "figma tracing".
Allowed Tools
Provided by Plugin
figma-pack
Claude Code skill pack for Figma (30 skills)
Installation
This skill is included in the figma-pack plugin:
/plugin install figma-pack@claude-code-plugins-plus
Click to copy
Instructions
Figma Observability
Overview
Set up comprehensive observability for Figma integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
figmarequeststotal |
Counter | Total API requests |
figmarequestduration_seconds |
Histogram | Request latency |
figmaerrorstotal |
Counter | Error count by type |
figmaratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'figma_requests_total',
help: 'Total Figma API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'figma_request_duration_seconds',
help: 'Figma request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'figma_errors_total',
help: 'Figma 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('figma-client');
async function tracedFigmaCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`figma.${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: 'figma',
level: process.env.LOG_LEVEL || 'info',
});
function logFigmaOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'figma',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# figma_alerts.yaml
groups:
- name: figma_alerts
rules:
- alert: FigmaHighErrorRate
expr: |
rate(figma_errors_total[5m]) /
rate(figma_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Figma error rate > 5%"
- alert: FigmaHighLatency
expr: |
histogram_quantile(0.95,
rate(figma_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Figma P95 latency > 2s"
- alert: FigmaDown
expr: up{job="figma"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Figma integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Figma Request Rate",
"targets": [{
"expr": "rate(figma_requests_total[5m])"
}]
},
{
"title": "Figma Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(figma_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 figma-incident-runbook.