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speak-observability

speak-observability

Set up comprehensive observability for Speak integrations with metrics, traces, and alerts. Use when implementing monitoring for Speak operations, setting up dashboards, or configuring alerting for language learning feature health. Trigger with phrases like "speak monitoring", "speak metrics", "speak observability", "monitor speak", "speak alerts", "speak t…

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Skill 문서

GitHub

name: speak-observability description: | Set up comprehensive observability for Speak integrations with metrics, traces, and alerts. Use when implementing monitoring for Speak operations, setting up dashboards, or configuring alerting for language learning feature health. Trigger with phrases like "speak monitoring", "speak metrics", "speak observability", "monitor speak", "speak alerts", "speak tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Speak Observability

Overview

Set up comprehensive observability for Speak language learning integrations.

Prerequisites

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

Key Metrics for Language Learning

Business Metrics

MetricTypeDescription
speak_lessons_started_totalCounterLessons initiated
speak_lessons_completed_totalCounterLessons completed
speak_lessons_abandoned_totalCounterLessons abandoned mid-session
speak_pronunciation_scoreHistogramPronunciation scores distribution
speak_active_sessionsGaugeCurrently active lesson sessions
speak_daily_active_learnersGaugeUnique learners today

Technical Metrics

MetricTypeDescription
speak_api_requests_totalCounterTotal API requests
speak_api_duration_secondsHistogramRequest latency
speak_api_errors_totalCounterError count by type
speak_speech_recognition_duration_secondsHistogramAudio processing time
speak_rate_limit_remainingGaugeRate limit headroom

Prometheus Metrics Implementation

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

const registry = new Registry();

// Business metrics
const lessonsStarted = new Counter({
  name: 'speak_lessons_started_total',
  help: 'Total lessons started',
  labelNames: ['language', 'topic', 'difficulty'],
  registers: [registry],
});

const lessonsCompleted = new Counter({
  name: 'speak_lessons_completed_total',
  help: 'Total lessons completed',
  labelNames: ['language', 'topic', 'difficulty'],
  registers: [registry],
});

const pronunciationScore = new Histogram({
  name: 'speak_pronunciation_score',
  help: 'Pronunciation scores distribution',
  labelNames: ['language'],
  buckets: [40, 50, 60, 70, 80, 85, 90, 95, 100],
  registers: [registry],
});

const activeSessions = new Gauge({
  name: 'speak_active_sessions',
  help: 'Currently active lesson sessions',
  labelNames: ['language'],
  registers: [registry],
});

// Technical metrics
const apiRequests = new Counter({
  name: 'speak_api_requests_total',
  help: 'Total Speak API requests',
  labelNames: ['method', 'endpoint', 'status'],
  registers: [registry],
});

const apiDuration = new Histogram({
  name: 'speak_api_duration_seconds',
  help: 'Speak API request duration',
  labelNames: ['method', 'endpoint'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10],
  registers: [registry],
});

const speechRecognitionDuration = new Histogram({
  name: 'speak_speech_recognition_duration_seconds',
  help: 'Speech recognition processing time',
  labelNames: ['language'],
  buckets: [0.5, 1, 2, 3, 5, 10],
  registers: [registry],
});

Instrumented Speak Client

async function instrumentedSpeakRequest<T>(
  method: string,
  endpoint: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = apiDuration.startTimer({ method, endpoint });

  try {
    const result = await operation();
    apiRequests.inc({ method, endpoint, status: 'success' });
    return result;
  } catch (error: any) {
    apiRequests.inc({ method, endpoint, status: 'error' });
    throw error;
  } finally {
    timer();
  }
}

// Lesson tracking
async function trackLessonStart(session: LessonSession): Promise<void> {
  lessonsStarted.inc({
    language: session.language,
    topic: session.topic,
    difficulty: session.difficulty,
  });
  activeSessions.inc({ language: session.language });
}

async function trackLessonEnd(
  session: LessonSession,
  summary: SessionSummary
): Promise<void> {
  const labels = {
    language: session.language,
    topic: session.topic,
    difficulty: session.difficulty,
  };

  if (summary.completed) {
    lessonsCompleted.inc(labels);
  } else {
    lessonsAbandoned.inc({
      ...labels,
      abandonReason: summary.abandonReason || 'unknown',
    });
  }

  activeSessions.dec({ language: session.language });

  // Record pronunciation score
  if (summary.averagePronunciationScore) {
    pronunciationScore.observe(
      { language: session.language },
      summary.averagePronunciationScore
    );
  }
}

Distributed Tracing

OpenTelemetry Setup

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

const tracer = trace.getTracer('speak-service');

async function tracedSpeakCall<T>(
  operationName: string,
  attributes: Record<string, string>,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`speak.${operationName}`, async (span) => {
    span.setAttributes(attributes);

    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();
    }
  });
}

// Trace a complete lesson session
async function tracedLessonSession(
  userId: string,
  config: LessonConfig
): Promise<SessionSummary> {
  return tracedSpeakCall(
    'lesson.session',
    {
      'user.id': userId,
      'lesson.language': config.language,
      'lesson.topic': config.topic,
    },
    async () => {
      const session = await speakService.startSession(config);

      // Create child spans for each exchange
      while (!session.isComplete) {
        await tracedSpeakCall(
          'lesson.exchange',
          { 'session.id': session.id },
          async () => {
            const prompt = await session.getPrompt();
            const response = await getUserResponse();
            return session.submitResponse(response);
          }
        );
      }

      return session.getSummary();
    }
  );
}

Structured Logging

import pino from 'pino';

const logger = pino({
  name: 'speak-service',
  level: process.env.LOG_LEVEL || 'info',
  formatters: {
    level: (label) => ({ level: label }),
  },
});

interface SpeakLogContext {
  service: 'speak';
  operation: string;
  sessionId?: string;
  userId?: string;
  language?: string;
  duration_ms?: number;
  pronunciationScore?: number;
  error?: any;
}

function logSpeakOperation(
  level: 'info' | 'warn' | 'error',
  operation: string,
  context: Partial<SpeakLogContext>
): void {
  const logContext: SpeakLogContext = {
    service: 'speak',
    operation,
    ...context,
  };

  logger[level](logContext, `Speak ${operation}`);
}

// Usage
logSpeakOperation('info', 'lesson.completed', {
  sessionId: session.id,
  userId: session.userId,
  language: session.language,
  duration_ms: summary.duration,
  pronunciationScore: summary.averagePronunciationScore,
});

Alert Configuration

Prometheus AlertManager Rules

# speak_alerts.yaml
groups:
  - name: speak_alerts
    rules:
      # High error rate
      - alert: SpeakHighErrorRate
        expr: |
          rate(speak_api_errors_total[5m]) /
          rate(speak_api_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
          service: speak
        annotations:
          summary: "Speak API error rate > 5%"
          description: "Error rate is {{ $value | humanizePercentage }}"

      # Speech recognition slow
      - alert: SpeakSpeechRecognitionSlow
        expr: |
          histogram_quantile(0.95,
            rate(speak_speech_recognition_duration_seconds_bucket[5m])
          ) > 5
        for: 5m
        labels:
          severity: warning
          service: speak
        annotations:
          summary: "Speech recognition P95 latency > 5s"

      # Low lesson completion rate
      - alert: SpeakLowCompletionRate
        expr: |
          rate(speak_lessons_completed_total[1h]) /
          rate(speak_lessons_started_total[1h]) < 0.5
        for: 30m
        labels:
          severity: warning
          service: speak
        annotations:
          summary: "Lesson completion rate < 50%"

      # Speak API down
      - alert: SpeakAPIDown
        expr: up{job="speak"} == 0
        for: 1m
        labels:
          severity: critical
          service: speak
        annotations:
          summary: "Speak API is unreachable"

      # Pronunciation scores dropping
      - alert: SpeakPronunciationScoresDrop
        expr: |
          avg(speak_pronunciation_score) < 60
        for: 1h
        labels:
          severity: info
          service: speak
        annotations:
          summary: "Average pronunciation scores below 60%"

Grafana Dashboard

{
  "title": "Speak Language Learning",
  "panels": [
    {
      "title": "Active Lesson Sessions",
      "type": "stat",
      "targets": [{
        "expr": "sum(speak_active_sessions)"
      }]
    },
    {
      "title": "Lessons Started vs Completed",
      "type": "graph",
      "targets": [
        { "expr": "rate(speak_lessons_started_total[5m])", "legendFormat": "Started" },
        { "expr": "rate(speak_lessons_completed_total[5m])", "legendFormat": "Completed" }
      ]
    },
    {
      "title": "Pronunciation Score Distribution",
      "type": "heatmap",
      "targets": [{
        "expr": "sum by (le) (rate(speak_pronunciation_score_bucket[5m]))"
      }]
    },
    {
      "title": "API Latency P50/P95/P99",
      "type": "graph",
      "targets": [
        { "expr": "histogram_quantile(0.5, rate(speak_api_duration_seconds_bucket[5m]))", "legendFormat": "P50" },
        { "expr": "histogram_quantile(0.95, rate(speak_api_duration_seconds_bucket[5m]))", "legendFormat": "P95" },
        { "expr": "histogram_quantile(0.99, rate(speak_api_duration_seconds_bucket[5m]))", "legendFormat": "P99" }
      ]
    },
    {
      "title": "Speech Recognition Duration",
      "type": "graph",
      "targets": [{
        "expr": "histogram_quantile(0.95, rate(speak_speech_recognition_duration_seconds_bucket[5m]))"
      }]
    },
    {
      "title": "Error Rate by Type",
      "type": "graph",
      "targets": [{
        "expr": "sum by (error_type) (rate(speak_api_errors_total[5m]))"
      }]
    }
  ]
}

Output

  • Business and technical metrics
  • Distributed tracing configured
  • Structured logging implemented
  • Alert rules deployed
  • Grafana dashboard ready

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 speak-incident-runbook.

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