hubspot-observability

Set up comprehensive observability for HubSpot integrations with metrics, traces, and alerts. Use when implementing monitoring for HubSpot operations, setting up dashboards, or configuring alerting for HubSpot integration health. Trigger with phrases like "hubspot monitoring", "hubspot metrics", "hubspot observability", "monitor hubspot", "hubspot alerts", "hubspot tracing".

claude-code
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hubspot-pack Plugin
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hubspot-pack

Claude Code skill pack for HubSpot (30 skills)

saas packs v1.0.0
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Installation

This skill is included in the hubspot-pack plugin:

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

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Instructions

HubSpot Observability

Overview

Set up comprehensive observability for HubSpot integrations.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed
  • Grafana or similar dashboarding tool
  • AlertManager configured

Metrics Collection

Key Metrics

Metric Type Description
hubspotrequeststotal Counter Total API requests
hubspotrequestduration_seconds Histogram Request latency
hubspoterrorstotal Counter Error count by type
hubspotratelimit_remaining Gauge Rate limit headroom

Prometheus Metrics


import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'hubspot_requests_total',
  help: 'Total HubSpot API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'hubspot_request_duration_seconds',
  help: 'HubSpot request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'hubspot_errors_total',
  help: 'HubSpot 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('hubspot-client');

async function tracedHubSpotCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`hubspot.${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: 'hubspot',
  level: process.env.LOG_LEVEL || 'info',
});

function logHubSpotOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'hubspot',
    operation,
    duration_ms: duration,
    ...data,
  });
}

Alert Configuration

Prometheus AlertManager Rules


# hubspot_alerts.yaml
groups:
  - name: hubspot_alerts
    rules:
      - alert: HubSpotHighErrorRate
        expr: |
          rate(hubspot_errors_total[5m]) /
          rate(hubspot_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "HubSpot error rate > 5%"

      - alert: HubSpotHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(hubspot_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "HubSpot P95 latency > 2s"

      - alert: HubSpotDown
        expr: up{job="hubspot"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "HubSpot integration is down"

Dashboard

Grafana Panel Queries


{
  "panels": [
    {
      "title": "HubSpot Request Rate",
      "targets": [{
        "expr": "rate(hubspot_requests_total[5m])"
      }]
    },
    {
      "title": "HubSpot Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(hubspot_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 hubspot-incident-runbook.

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