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