adobe-observability

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

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adobe-pack Plugin
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adobe-pack

Claude Code skill pack for Adobe (30 skills)

saas packs v1.0.0
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Installation

This skill is included in the adobe-pack plugin:

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

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Instructions

Adobe Observability

Overview

Set up comprehensive observability for Adobe integrations.

Prerequisites

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

Metrics Collection

Key Metrics

Metric Type Description
adoberequeststotal Counter Total API requests
adoberequestduration_seconds Histogram Request latency
adobeerrorstotal Counter Error count by type
adoberatelimit_remaining Gauge Rate limit headroom

Prometheus Metrics


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

const registry = new Registry();

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

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

const errorCounter = new Counter({
  name: 'adobe_errors_total',
  help: 'Adobe 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('adobe-client');

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

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

Alert Configuration

Prometheus AlertManager Rules


# adobe_alerts.yaml
groups:
  - name: adobe_alerts
    rules:
      - alert: AdobeHighErrorRate
        expr: |
          rate(adobe_errors_total[5m]) /
          rate(adobe_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Adobe error rate > 5%"

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

      - alert: AdobeDown
        expr: up{job="adobe"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Adobe integration is down"

Dashboard

Grafana Panel Queries


{
  "panels": [
    {
      "title": "Adobe Request Rate",
      "targets": [{
        "expr": "rate(adobe_requests_total[5m])"
      }]
    },
    {
      "title": "Adobe Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(adobe_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 adobe-incident-runbook.

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