Ideogram Observability
Overview
Monitor Ideogram AI image generation for latency, cost, error rates, and content safety rejections. Key metrics: generation duration (5-25s depending on model), credit burn rate, safety filter rejection rate, and API availability. Ideogram's API is synchronous, so all observability is request-level instrumentation.
Key Metrics
| Metric | Type | Labels | Alert Threshold |
|---|
ideogram_generation_duration_ms | Histogram | model, style, speed | P95 > 25s |
ideogram_generations_total | Counter | model, status | Error rate > 5% |
ideogram_credits_estimated | Counter | model | >$10/hour |
ideogram_safety_rejections | Counter | reason | >10% rejection rate |
ideogram_image_downloads | Counter | status | Download failures > 1% |
Instructions
Step 1: Instrumented Generation Wrapper
import { performance } from "perf_hooks";
interface GenerationMetrics {
duration: number;
model: string;
style: string;
status: "success" | "error" | "safety_rejected" | "rate_limited";
seed?: number;
resolution?: string;
}
const metricsLog: GenerationMetrics[] = [];
async function instrumentedGenerate(
prompt: string,
options: { model?: string; style_type?: string; aspect_ratio?: string } = {}
) {
const model = options.model ?? "V_2";
const style = options.style_type ?? "AUTO";
const start = performance.now();
try {
const response = await fetch("https://api.ideogram.ai/generate", {
method: "POST",
headers: {
"Api-Key": process.env.IDEOGRAM_API_KEY!,
"Content-Type": "application/json",
},
body: JSON.stringify({
image_request: { prompt, model, style_type: style, ...options, magic_prompt_option: "AUTO" },
}),
});
const duration = performance.now() - start;
if (response.status === 422) {
recordMetric({ duration, model, style, status: "safety_rejected" });
throw new Error("Safety filter rejected prompt");
}
if (response.status === 429) {
recordMetric({ duration, model, style, status: "rate_limited" });
throw new Error("Rate limited");
}
if (!response.ok) {
recordMetric({ duration, model, style, status: "error" });
throw new Error(`API error: ${response.status}`);
}
const result = await response.json();
const image = result.data[0];
recordMetric({
duration, model, style, status: "success",
seed: image.seed, resolution: image.resolution,
});
return result;
} catch (err) {
if (!metricsLog.find(m => m.duration === performance.now() - start)) {
recordMetric({ duration: performance.now() - start, model, style, status: "error" });
}
throw err;
}
}
function recordMetric(metric: GenerationMetrics) {
metricsLog.push(metric);
console.log(JSON.stringify({
event: "ideogram.generation",
...metric,
timestamp: new Date().toISOString(),
}));
}
Step 2: Cost Estimation Metrics
const MODEL_COST_USD: Record<string, number> = {
V_2_TURBO: 0.05, V_2: 0.08, V_2A: 0.04, V_2A_TURBO: 0.025,
};
function estimateCost(model: string, numImages: number = 1): number {
return (MODEL_COST_USD[model] ?? 0.08) * numImages;
}
function costReport(metrics: GenerationMetrics[]) {
const successful = metrics.filter(m => m.status === "success");
const totalCost = successful.reduce((sum, m) => sum + estimateCost(m.model), 0);
const byModel = Object.groupBy(successful, m => m.model);
console.log("=== Ideogram Cost Report ===");
console.();
.();
( [model, gens] .(byModel)) {
cost = (gens?. ?? ) * ([model] ?? );
.();
}
}
Step 3: Prometheus Metrics (Optional)
import { Counter, Histogram, register } from "prom-client";
const generationDuration = new Histogram({
name: "ideogram_generation_duration_seconds",
help: "Ideogram image generation duration",
labelNames: ["model", "style", "status"],
buckets: [2, 5, 10, 15, 20, 30, 60],
});
const generationTotal = new Counter({
name: "ideogram_generations_total",
help: "Total Ideogram generations",
labelNames: ["model", "status"],
});
const estimatedCostTotal = new Counter({
name: "ideogram_estimated_cost_usd",
help: "Estimated Ideogram API cost in USD",
labelNames: ["model"],
});
app.get("/metrics", async (req, res) => {
res.set("Content-Type", register.contentType);
res.end( register.());
});
Step 4: Alerting Rules
groups:
- name: ideogram
rules:
- alert: IdeogramGenerationSlow
expr: histogram_quantile(0.95, rate(ideogram_generation_duration_seconds_bucket[15m])) > 25
for: 5m
annotations:
summary: "Ideogram P95 generation time exceeds 25 seconds"
- alert: IdeogramHighErrorRate
expr: rate(ideogram_generations_total{status="error"}[10m]) / rate(ideogram_generations_total[10m]) > 0.05
for: 5m
annotations:
summary: "Ideogram error rate exceeds 5%"
- alert: IdeogramHighCostRate
expr: rate(ideogram_estimated_cost_usd[1h]) > 10
annotations:
summary: "Ideogram burning >$10/hour"
- alert: IdeogramSafetyRejectionSpike
expr: rate(ideogram_generations_total{status="safety_rejected"}[1h]) / rate(ideogram_generations_total[1h])
Step 5: Dashboard Panel Queries
# Grafana dashboard panels:
# 1. Generation volume: sum(rate(ideogram_generations_total[5m])) by (model)
# 2. Latency distribution: histogram_quantile(0.5, rate(ideogram_generation_duration_seconds_bucket[5m]))
# 3. Error rate: sum(rate(ideogram_generations_total{status!="success"}[5m])) / sum(rate(ideogram_generations_total[5m]))
# 4. Cost per hour: sum(rate(ideogram_estimated_cost_usd[1h]))
# 5. Safety rejections: sum(rate(ideogram_generations_total{status="safety_rejected"}[1h]))
Error Handling
| Issue | Cause | Solution |
|---|
| Generation timeout | Complex prompt or QUALITY speed | Alert at P95 > 25s, suggest TURBO |
| 402 credit error | Credits exhausted | Alert immediately, pause batch jobs |
| High rejection rate | User prompts hitting safety filter | Review prompt patterns, add pre-screening |
| 429 sustained | Concurrency too high | Reduce queue concurrency, alert ops |
Output
- Instrumented generation wrapper with metrics collection
- Cost estimation and reporting
- Prometheus metrics with alerting rules
- Grafana dashboard query templates
Resources
Next Steps
For incident response, see ideogram-incident-runbook.
