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