| 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
| 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
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
| 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 ideogram-incident-runbook.