Agent skill

ideogram-observability

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

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/ideogram-observability

SKILL.md

Ideogram Observability

Overview

Set up comprehensive observability for Ideogram integrations.

Prerequisites

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

Metrics Collection

Key Metrics

Metric Type Description
ideogram_requests_total Counter Total API requests
ideogram_request_duration_seconds Histogram Request latency
ideogram_errors_total Counter Error count by type
ideogram_rate_limit_remaining Gauge Rate limit headroom

Prometheus Metrics

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

const registry = new Registry();

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

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

const errorCounter = new Counter({
  name: 'ideogram_errors_total',
  help: 'Ideogram errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});

Instrumented Client

typescript
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

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

const tracer = trace.getTracer('ideogram-client');

async function tracedIdeogramCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`ideogram.${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

typescript
import pino from 'pino';

const logger = pino({
  name: 'ideogram',
  level: process.env.LOG_LEVEL || 'info',
});

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

Alert Configuration

Prometheus AlertManager Rules

yaml
# ideogram_alerts.yaml
groups:
  - name: ideogram_alerts
    rules:
      - alert: IdeogramHighErrorRate
        expr: |
          rate(ideogram_errors_total[5m]) /
          rate(ideogram_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Ideogram error rate > 5%"

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

      - alert: IdeogramDown
        expr: up{job="ideogram"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Ideogram integration is down"

Dashboard

Grafana Panel Queries

json
{
  "panels": [
    {
      "title": "Ideogram Request Rate",
      "targets": [{
        "expr": "rate(ideogram_requests_total[5m])"
      }]
    },
    {
      "title": "Ideogram Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(ideogram_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

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

Resources

Next Steps

For incident response, see ideogram-incident-runbook.

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