From deepgram-pack
Set up comprehensive observability for Deepgram integrations. Use when implementing monitoring, setting up dashboards, or configuring alerting for Deepgram integration health. Trigger: "deepgram monitoring", "deepgram metrics", "deepgram observability", "monitor deepgram", "deepgram alerts", "deepgram dashboard".
npx claudepluginhub flight505/skill-forge --plugin deepgram-packThis skill is limited to using the following tools:
Full observability stack for Deepgram: Prometheus metrics (request counts, latency histograms, audio processed, cost tracking), OpenTelemetry distributed tracing, structured JSON logging with Pino, Grafana dashboard JSON, and AlertManager rules.
Guides Next.js Cache Components and Partial Prerendering (PPR): 'use cache' directives, cacheLife(), cacheTag(), revalidateTag() for caching, invalidation, static/dynamic optimization. Auto-activates on cacheComponents: true.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
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Full observability stack for Deepgram: Prometheus metrics (request counts, latency histograms, audio processed, cost tracking), OpenTelemetry distributed tracing, structured JSON logging with Pino, Grafana dashboard JSON, and AlertManager rules.
| Pillar | Tool | What It Tracks |
|---|---|---|
| Metrics | Prometheus | Request rate, latency, error rate, audio minutes, estimated cost |
| Traces | OpenTelemetry | End-to-end request flow, Deepgram API span timing |
| Logs | Pino (JSON) | Request details, errors, audit trail |
| Alerts | AlertManager | Error rate >5%, P95 latency >10s, rate limit hits |
import { Counter, Histogram, Gauge, Registry, collectDefaultMetrics } from 'prom-client';
const registry = new Registry();
collectDefaultMetrics({ register: registry });
// Request metrics
const requestsTotal = new Counter({
name: 'deepgram_requests_total',
help: 'Total Deepgram API requests',
labelNames: ['method', 'model', 'status'] as const,
registers: [registry],
});
const latencyHistogram = new Histogram({
name: 'deepgram_request_duration_seconds',
help: 'Deepgram API request duration',
labelNames: ['method', 'model'] as const,
buckets: [0.1, 0.5, 1, 2, 5, 10, 30, 60],
registers: [registry],
});
// Usage metrics
const audioProcessedSeconds = new Counter({
name: 'deepgram_audio_processed_seconds_total',
help: 'Total audio seconds processed',
labelNames: ['model'] as const,
registers: [registry],
});
const estimatedCostDollars = new Counter({
name: 'deepgram_estimated_cost_dollars_total',
help: 'Estimated cost in USD',
labelNames: ['model', 'method'] as const,
registers: [registry],
});
// Operational metrics
const activeConnections = new Gauge({
name: 'deepgram_active_websocket_connections',
help: 'Currently active WebSocket connections',
registers: [registry],
});
const rateLimitHits = new Counter({
name: 'deepgram_rate_limit_hits_total',
help: 'Number of 429 rate limit responses',
registers: [registry],
});
export { registry, requestsTotal, latencyHistogram, audioProcessedSeconds,
estimatedCostDollars, activeConnections, rateLimitHits };
import { createClient, DeepgramClient } from '@deepgram/sdk';
class InstrumentedDeepgram {
private client: DeepgramClient;
private costPerMinute: Record<string, number> = {
'nova-3': 0.0043, 'nova-2': 0.0043, 'base': 0.0048, 'whisper-large': 0.0048,
};
constructor(apiKey: string) {
this.client = createClient(apiKey);
}
async transcribeUrl(url: string, options: Record<string, any> = {}) {
const model = options.model ?? 'nova-3';
const timer = latencyHistogram.startTimer({ method: 'prerecorded', model });
try {
const { result, error } = await this.client.listen.prerecorded.transcribeUrl(
{ url }, { model, smart_format: true, ...options }
);
const status = error ? 'error' : 'success';
timer();
requestsTotal.inc({ method: 'prerecorded', model, status });
if (error) {
if ((error as any).status === 429) rateLimitHits.inc();
throw error;
}
// Track usage
const duration = result.metadata.duration;
audioProcessedSeconds.inc({ model }, duration);
estimatedCostDollars.inc(
{ model, method: 'prerecorded' },
(duration / 60) * (this.costPerMinute[model] ?? 0.0043)
);
return result;
} catch (err) {
timer();
requestsTotal.inc({ method: 'prerecorded', model, status: 'error' });
throw err;
}
}
// Live transcription with connection tracking
connectLive(options: Record<string, any>) {
const model = options.model ?? 'nova-3';
activeConnections.inc();
const connection = this.client.listen.live(options);
const originalFinish = connection.finish.bind(connection);
connection.finish = () => {
activeConnections.dec();
return originalFinish();
};
return connection;
}
}
import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import { Resource } from '@opentelemetry/resources';
import { SEMRESATTRS_SERVICE_NAME } from '@opentelemetry/semantic-conventions';
import { trace } from '@opentelemetry/api';
const sdk = new NodeSDK({
resource: new Resource({
[SEMRESATTRS_SERVICE_NAME]: 'deepgram-service',
'deployment.environment': process.env.NODE_ENV ?? 'development',
}),
traceExporter: new OTLPTraceExporter({
url: process.env.OTEL_EXPORTER_OTLP_ENDPOINT ?? 'http://localhost:4318/v1/traces',
}),
instrumentations: [
getNodeAutoInstrumentations({
'@opentelemetry/instrumentation-http': {
ignoreIncomingPaths: ['/health', '/metrics'],
},
}),
],
});
sdk.start();
// Add custom spans for Deepgram operations
const tracer = trace.getTracer('deepgram');
async function tracedTranscribe(url: string, model: string) {
return tracer.startActiveSpan('deepgram.transcribe', async (span) => {
span.setAttribute('deepgram.model', model);
span.setAttribute('deepgram.audio_url', url.substring(0, 100));
try {
const instrumented = new InstrumentedDeepgram(process.env.DEEPGRAM_API_KEY!);
const result = await instrumented.transcribeUrl(url, { model });
span.setAttribute('deepgram.duration_seconds', result.metadata.duration);
span.setAttribute('deepgram.request_id', result.metadata.request_id);
span.setAttribute('deepgram.confidence',
result.results.channels[0].alternatives[0].confidence);
return result;
} catch (err: any) {
span.recordException(err);
span.setStatus({ code: 2, message: err.message });
throw err;
} finally {
span.end();
}
});
}
import pino from 'pino';
const logger = pino({
level: process.env.LOG_LEVEL ?? 'info',
formatters: {
level: (label) => ({ level: label }),
},
timestamp: pino.stdTimeFunctions.isoTime,
base: {
service: 'deepgram-integration',
env: process.env.NODE_ENV,
},
});
// Child loggers per component
const transcriptionLog = logger.child({ component: 'transcription' });
const metricsLog = logger.child({ component: 'metrics' });
// Usage:
transcriptionLog.info({
action: 'transcribe',
model: 'nova-3',
audioUrl: url.substring(0, 100),
requestId: result.metadata.request_id,
duration: result.metadata.duration,
confidence: result.results.channels[0].alternatives[0].confidence,
}, 'Transcription completed');
transcriptionLog.error({
action: 'transcribe',
model: 'nova-3',
error: err.message,
statusCode: err.status,
}, 'Transcription failed');
{
"title": "Deepgram Observability",
"panels": [
{
"title": "Request Rate",
"type": "timeseries",
"targets": [{ "expr": "rate(deepgram_requests_total[5m])" }]
},
{
"title": "P95 Latency",
"type": "gauge",
"targets": [{ "expr": "histogram_quantile(0.95, rate(deepgram_request_duration_seconds_bucket[5m]))" }]
},
{
"title": "Error Rate %",
"type": "stat",
"targets": [{ "expr": "rate(deepgram_requests_total{status='error'}[5m]) / rate(deepgram_requests_total[5m]) * 100" }]
},
{
"title": "Audio Processed (min/hr)",
"type": "timeseries",
"targets": [{ "expr": "rate(deepgram_audio_processed_seconds_total[1h]) / 60" }]
},
{
"title": "Estimated Daily Cost",
"type": "stat",
"targets": [{ "expr": "increase(deepgram_estimated_cost_dollars_total[24h])" }]
},
{
"title": "Active WebSocket Connections",
"type": "gauge",
"targets": [{ "expr": "deepgram_active_websocket_connections" }]
}
]
}
groups:
- name: deepgram-alerts
rules:
- alert: DeepgramHighErrorRate
expr: >
rate(deepgram_requests_total{status="error"}[5m])
/ rate(deepgram_requests_total[5m]) > 0.05
for: 5m
labels: { severity: critical }
annotations:
summary: "Deepgram error rate > 5% for 5 minutes"
- alert: DeepgramHighLatency
expr: >
histogram_quantile(0.95,
rate(deepgram_request_duration_seconds_bucket[5m])
) > 10
for: 5m
labels: { severity: warning }
annotations:
summary: "Deepgram P95 latency > 10 seconds"
- alert: DeepgramRateLimited
expr: rate(deepgram_rate_limit_hits_total[1h]) > 10
for: 10m
labels: { severity: warning }
annotations:
summary: "Deepgram rate limit hits > 10/hour"
- alert: DeepgramCostSpike
expr: >
increase(deepgram_estimated_cost_dollars_total[24h])
> 2 * increase(deepgram_estimated_cost_dollars_total[24h] offset 1d)
for: 30m
labels: { severity: warning }
annotations:
summary: "Deepgram daily cost > 2x yesterday"
- alert: DeepgramZeroRequests
expr: rate(deepgram_requests_total[15m]) == 0
for: 15m
labels: { severity: warning }
annotations:
summary: "No Deepgram requests for 15 minutes"
import express from 'express';
const app = express();
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
| Issue | Cause | Solution |
|---|---|---|
| Metrics not appearing | Registry not exported | Check /metrics endpoint |
| High cardinality | Too many label values | Limit labels to known set |
| Alert storms | Thresholds too sensitive | Add for: duration, tune values |
| Missing traces | OTEL exporter not configured | Set OTEL_EXPORTER_OTLP_ENDPOINT |