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jeremylongshore

ideogram-observability

by jeremylongshore

Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.

1,042🍴 135📅 Jan 23, 2026

SKILL.md


name: ideogram-observability description: | 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". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

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

MetricTypeDescription
ideogram_requests_totalCounterTotal API requests
ideogram_request_duration_secondsHistogramRequest latency
ideogram_errors_totalCounterError count by type
ideogram_rate_limit_remainingGaugeRate limit headroom

Prometheus Metrics

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

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('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

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

# 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

{
  "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

IssueCauseSolution
Missing metricsNo instrumentationWrap client calls
Trace gapsMissing propagationCheck context headers
Alert stormsWrong thresholdsTune alert rules
High cardinalityToo many labelsReduce 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 ideogram-incident-runbook.

Score

Total Score

85/100

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