Adobe observability

Adobe Observability

Overview

Set up comprehensive observability for Adobe API integrations covering four pillars: metrics (Prometheus), traces (OpenTelemetry), logs (structured JSON), and alerts. Each Adobe API has different latency profiles requiring specific monitoring.

Prerequisites

• Prometheus or compatible metrics backend
• OpenTelemetry SDK (@opentelemetry/api)
• Grafana or similar dashboarding tool
• AlertManager or PagerDuty for alerts

Instructions

Step 1: Define Key Metrics by API

Metric	Type	Labels	Description
adobe_ims_token_requests_total	Counter	status	Token generation attempts
adobe_api_requests_total	Counter	api,operation,status	API calls by type
adobe_api_duration_seconds	Histogram	api,operation	Latency per operation
adobe_api_errors_total	Counter	api,error_code	Errors by code (401,403,429,500)
adobe_job_poll_count	Histogram	api	Polls before async job completes
adobe_rate_limit_retries_total	Counter	api	429 retries
adobe_pdf_transactions_used	Gauge	—	Monthly PDF Services usage

Step 2: Instrumented Adobe Client

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

const registry = new Registry();

const apiRequests = new Counter({
  name: 'adobe_api_requests_total',
  help: 'Total Adobe API requests',
  labelNames: ['api', 'operation', 'status'] as const,
  registers: [registry],
});

const apiDuration = new Histogram({
  name: 'adobe_api_duration_seconds',
  help: 'Adobe API request duration in seconds',
  labelNames: ['api', 'operation'] as const,
  buckets: [0.5, 1, 2, 5, 10, 20, 30, 60], // Adobe APIs are slow
  registers: [registry],
});

const apiErrors = new Counter({
  name: 'adobe_api_errors_total',
  help: 'Adobe API errors by code',
  labelNames: ['api', 'error_code'] as const,
  registers: [registry],
});

export async function instrumentedAdobeCall<T>(
  api: string,
  operation: string,
  fn: () => Promise<T>
): Promise<T> {
  const timer = apiDuration.startTimer({ api, operation });
  try {
    const result = await fn();
    apiRequests.inc({ api, operation, status: 'success' });
    return result;
  } catch (error: any) {
    const errorCode = error.status || error.httpStatus || 'unknown';
    apiRequests.inc({ api, operation, status: 'error' });
    apiErrors.inc({ api, error_code: String(errorCode) });
    throw error;
  } finally {
    timer();
  }
}

// Usage
const image = await instrumentedAdobeCall('firefly', 'generate', () =>
  generateImage({ prompt: 'sunset landscape' })
);

Step 3: OpenTelemetry Distributed Tracing

import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('adobe-integration');

export async function tracedAdobeCall<T>(
  api: string,
  operation: string,
  fn: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`adobe.${api}.${operation}`, async (span) => {
    span.setAttribute('adobe.api', api);
    span.setAttribute('adobe.operation', operation);
    span.setAttribute('adobe.client_id', process.env.ADOBE_CLIENT_ID!);

    try {
      const result = await fn();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.setAttribute('adobe.error_code', error.status || 'unknown');
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Step 4: Structured Logging

import pino from 'pino';

const logger = pino({
  name: 'adobe',
  level: process.env.LOG_LEVEL || 'info',
  redact: ['clientSecret', 'accessToken', 'req.headers.authorization'],
});

export function logAdobeOperation(entry: {
  api: string;
  operation: string;
  durationMs: number;
  status: 'success' | 'error';
  httpStatus?: number;
  jobId?: string;
  error?: string;
}) {
  if (entry.status === 'error') {
    logger.error(entry, `Adobe ${entry.api}.${entry.operation} failed`);
  } else {
    logger.info(entry, `Adobe ${entry.api}.${entry.operation} completed`);
  }
}

Step 5: Alert Rules

# prometheus/adobe-alerts.yml
groups:
  - name: adobe_alerts
    rules:
      - alert: AdobeAuthFailure
        expr: increase(adobe_api_errors_total{error_code="401"}[5m]) > 0
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Adobe authentication failure — credentials may be expired or revoked"

      - alert: AdobeRateLimited
        expr: rate(adobe_api_errors_total{error_code="429"}[5m]) > 0.1
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Adobe API rate limited — reduce throughput or upgrade tier"

      - alert: AdobeHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(adobe_api_duration_seconds_bucket{api="firefly"}[5m])
          ) > 30
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "Adobe Firefly P95 latency > 30s"

      - alert: AdobeApiDown
        expr: |
          rate(adobe_api_errors_total{error_code=~"5.."}[5m]) /
          rate(adobe_api_requests_total[5m]) > 0.1
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Adobe API server error rate > 10%"

      - alert: AdobePdfQuotaLow
        expr: adobe_pdf_transactions_used > 450
        labels:
          severity: warning
        annotations:
          summary: "PDF Services: < 50 free tier transactions remaining"

Metrics Endpoint

app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Output

• Prometheus metrics for all Adobe API calls (latency, errors, rate limits)
• OpenTelemetry traces with Adobe-specific span attributes
• Structured JSON logging with credential redaction
• Alert rules for auth failures, rate limiting, latency, and quota

Error Handling

Issue	Cause	Solution
High cardinality metrics	Too many label values	Use fixed set of operation names
Alert storms	Thresholds too sensitive	Increase for duration
Missing traces	No OTel propagation	Verify context propagation setup
Redacted data in logs	Over-aggressive redaction	Whitelist safe fields

Resources

• Prometheus Best Practices
• OpenTelemetry Node.js
• Adobe Status Page

Next Steps

For incident response, see adobe-incident-runbook.