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".

claude-code
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intercom-pack Plugin
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intercom-pack

Claude Code skill pack for Intercom (24 skills)

saas packs v1.0.0
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Installation

This skill is included in the intercom-pack plugin:

/plugin install intercom-pack@claude-code-plugins-plus

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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.

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