TwinMind Observability

TwinMind Observability

Overview

Set up comprehensive observability for TwinMind integrations including metrics, distributed tracing, logging, and alerting.

Prerequisites

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

Metrics Collection

Key Metrics

Prometheus Metrics Implementation

// src/​observability/​metrics.ts
import { Registry, Counter, Histogram, Gauge, Summary } from 'prom-client';

const registry = new Registry();

// Transcription metrics
export const transcriptionCounter = new Counter({
  name: 'twinmind_transcriptions_total',
  help: 'Total TwinMind transcription requests',
  labelNames: ['status', 'model', 'language'],
  registers: [registry],
});

export const transcriptionDuration = new Histogram({
  name: 'twinmind_transcription_duration_seconds',
  help: 'TwinMind transcription processing duration',
  labelNames: ['model'],
  buckets: [1, 5, 10, 30, 60, 120, 300, 600],  // Up to 10 minutes
  registers: [registry],
});

export const audioHoursProcessed = new Counter({
  name: 'twinmind_transcription_audio_hours',
  help: 'Total audio hours processed',
  labelNames: ['model'],
  registers: [registry],
});

// API metrics
export const apiRequestCounter = new Counter({
  name: 'twinmind_api_requests_total',
  help: 'Total TwinMind API requests',
  labelNames: ['method', 'endpoint', 'status'],
  registers: [registry],
});

export const apiLatency = new Histogram({
  name: 'twinmind_api_latency_seconds',
  help: 'TwinMind API request latency',
  labelNames: ['method', 'endpoint'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10],
  registers: [registry],
});

// Error metrics
export const errorCounter = new Counter({
  name: 'twinmind_errors_total',
  help: 'TwinMind errors by type',
  labelNames: ['error_type', 'operation'],
  registers: [registry],
});

// Rate limit metrics
export const rateLimitRemaining = new Gauge({
  name: 'twinmind_rate_limit_remaining',
  help: 'Remaining rate limit quota',
  labelNames: ['endpoint'],
  registers: [registry],
});

// AI usage metrics
export const aiTokensUsed = new Counter({
  name: 'twinmind_ai_tokens_used',
  help: 'AI tokens consumed',
  labelNames: ['operation'],
  registers: [registry],
});

// Summary generation
export const summaryCounter = new Counter({
  name: 'twinmind_summary_requests_total',
  help: 'Summary generation requests',
  labelNames: ['status', 'format'],
  registers: [registry],
});

export const actionItemsExtracted = new Counter({
  name: 'twinmind_action_items_extracted',
  help: 'Action items extracted from meetings',
  registers: [registry],
});

export { registry };

Instrumented Client

// src/​twinmind/​instrumented-client.ts
import {
  transcriptionCounter,
  transcriptionDuration,
  audioHoursProcessed,
  apiRequestCounter,
  apiLatency,
  errorCounter,
  rateLimitRemaining,
} from '../​observability/​metrics';

export class InstrumentedTwinMindClient {
  private client: TwinMindClient;

  constructor(config: TwinMindConfig) {
    this.client = new TwinMindClient(config);
  }

  async transcribe(audioUrl: string, options?: TranscriptionOptions): Promise<Transcript> {
    const timer = transcriptionDuration.startTimer({ model: options?.model || 'ear-3' });

    try {
      const result = await this.client.transcribe(audioUrl, options);

      // Record success metrics
      transcriptionCounter.inc({
        status: 'success',
        model: options?.model || 'ear-3',
        language: result.language,
      });

      // Record audio hours
      audioHoursProcessed.inc(
        { model: options?.model || 'ear-3' },
        result.duration_seconds / 3600
      );

      return result;
    } catch (error: any) {
      transcriptionCounter.inc({
        status: 'error',
        model: options?.model || 'ear-3',
        language: 'unknown',
      });

      errorCounter.inc({
        error_type: error.code || 'unknown',
        operation: 'transcribe',
      });

      throw error;
    } finally {
      timer();
    }
  }

  async request<T>(method: string, endpoint: string, data?: any): Promise<T> {
    const timer = apiLatency.startTimer({ method, endpoint });

    try {
      const response = await this.client.request(method, endpoint, data);

      apiRequestCounter.inc({ method, endpoint, status: 'success' });

      // Update rate limit gauge from response headers
      if (response.headers?.['x-ratelimit-remaining']) {
        rateLimitRemaining.set(
          { endpoint },
          parseInt(response.headers['x-ratelimit-remaining'])
        );
      }

      return response.data;
    } catch (error: any) {
      apiRequestCounter.inc({
        method,
        endpoint,
        status: error.response?.status || 'error',
      });

      throw error;
    } finally {
      timer();
    }
  }
}

Distributed Tracing

OpenTelemetry Setup

// src/​observability/​tracing.ts
import { NodeSDK } from '@opentelemetry/​sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/​auto-instrumentations-node';
import { OTLPTraceExporter } from '@opentelemetry/​exporter-trace-otlp-http';
import { Resource } from '@opentelemetry/​resources';
import { SemanticResourceAttributes } from '@opentelemetry/​semantic-conventions';
import { trace, SpanStatusCode, SpanKind } from '@opentelemetry/​api';

// Initialize SDK
const sdk = new NodeSDK({
  resource: new Resource({
    [SemanticResourceAttributes.SERVICE_NAME]: 'twinmind-integration',
    [SemanticResourceAttributes.SERVICE_VERSION]: process.env.npm_package_version,
    [SemanticResourceAttributes.DEPLOYMENT_ENVIRONMENT]: process.env.NODE_ENV,
  }),
  traceExporter: new OTLPTraceExporter({
    url: process.env.OTEL_EXPORTER_OTLP_ENDPOINT || 'http://localhost:4318/​v1/​traces',
  }),
  instrumentations: [getNodeAutoInstrumentations()],
});

sdk.start();

// Custom tracer for TwinMind operations
export const tracer = trace.getTracer('twinmind-client');

// Traced operation wrapper
export async function tracedOperation<T>(
  operationName: string,
  operation: () => Promise<T>,
  attributes?: Record<string, string | number>
): Promise<T> {
  return tracer.startActiveSpan(
    `twinmind.${operationName}`,
    { kind: SpanKind.CLIENT, attributes },
    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();
      }
    }
  );
}

// Traced TwinMind client
export class TracedTwinMindClient {
  private client: TwinMindClient;

  async transcribe(audioUrl: string, options?: TranscriptionOptions): Promise<Transcript> {
    return tracedOperation(
      'transcribe',
      () => this.client.transcribe(audioUrl, options),
      {
        'twinmind.audio_url': audioUrl,
        'twinmind.model': options?.model || 'ear-3',
        'twinmind.diarization': options?.diarization ? 'true' : 'false',
      }
    );
  }

  async summarize(transcriptId: string): Promise<Summary> {
    return tracedOperation(
      'summarize',
      () => this.client.summarize(transcriptId),
      { 'twinmind.transcript_id': transcriptId }
    );
  }
}

Structured Logging

// src/​observability/​logging.ts
import pino from 'pino';

export const logger = pino({
  name: 'twinmind',
  level: process.env.LOG_LEVEL || 'info',
  formatters: {
    level: (label) => ({ level: label }),
  },
  redact: ['apiKey', 'authorization', 'password'],
});

// Operation-specific logging
export function logTwinMindOperation(
  operation: string,
  data: Record<string, any>,
  duration?: number
): void {
  logger.info({
    service: 'twinmind',
    operation,
    duration_ms: duration,
    ...data,
  });
}

// Error logging
export function logTwinMindError(
  operation: string,
  error: Error,
  context?: Record<string, any>
): void {
  logger.error({
    service: 'twinmind',
    operation,
    error: {
      name: error.name,
      message: error.message,
      stack: error.stack,
    },
    ...context,
  });
}

Alert Configuration

Prometheus AlertManager Rules

# alerts/​twinmind_alerts.yaml
groups:
  - name: twinmind_alerts
    rules:
      - alert: TwinMindHighErrorRate
        expr: |
          rate(twinmind_errors_total[5m]) /
          rate(twinmind_api_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
          service: twinmind
        annotations:
          summary: "TwinMind error rate > 5%"
          description: "Error rate is {{ $value | humanizePercentage }}"

      - alert: TwinMindHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(twinmind_api_latency_seconds_bucket[5m])
          ) > 5
        for: 5m
        labels:
          severity: warning
          service: twinmind
        annotations:
          summary: "TwinMind P95 latency > 5s"
          description: "P95 latency is {{ $value | humanizeDuration }}"

      - alert: TwinMindTranscriptionFailures
        expr: |
          increase(twinmind_transcriptions_total{status="error"}[15m]) > 5
        for: 5m
        labels:
          severity: warning
          service: twinmind
        annotations:
          summary: "TwinMind transcription failures increasing"
          description: "{{ $value }} failures in last 15 minutes"

      - alert: TwinMindRateLimitApproaching
        expr: |
          twinmind_rate_limit_remaining < 10
        for: 1m
        labels:
          severity: warning
          service: twinmind
        annotations:
          summary: "TwinMind rate limit approaching"
          description: "Only {{ $value }} requests remaining"

      - alert: TwinMindRateLimitExceeded
        expr: |
          increase(twinmind_errors_total{error_type="RATE_LIMITED"}[5m]) > 0
        for: 1m
        labels:
          severity: critical
          service: twinmind
        annotations:
          summary: "TwinMind rate limit exceeded"
          description: "Rate limit errors detected"

      - alert: TwinMindAPIDown
        expr: |
          up{job="twinmind"} == 0
        for: 1m
        labels:
          severity: critical
          service: twinmind
        annotations:
          summary: "TwinMind integration is down"
          description: "Health check failing"

      - alert: TwinMindHighTokenUsage
        expr: |
          increase(twinmind_ai_tokens_used[24h]) > 1500000
        for: 5m
        labels:
          severity: warning
          service: twinmind
        annotations:
          summary: "High TwinMind token usage"
          description: "{{ $value }} tokens used in 24h (limit: 2M)"

Grafana Dashboard

{
  "dashboard": {
    "title": "TwinMind Integration",
    "panels": [
      {
        "title": "Transcription Rate",
        "type": "graph",
        "targets": [{
          "expr": "rate(twinmind_transcriptions_total[5m])",
          "legendFormat": "{{status}}"
        }]
      },
      {
        "title": "API Latency (P50/​P95/​P99)",
        "type": "graph",
        "targets": [
          {
            "expr": "histogram_quantile(0.5, rate(twinmind_api_latency_seconds_bucket[5m]))",
            "legendFormat": "P50"
          },
          {
            "expr": "histogram_quantile(0.95, rate(twinmind_api_latency_seconds_bucket[5m]))",
            "legendFormat": "P95"
          },
          {
            "expr": "histogram_quantile(0.99, rate(twinmind_api_latency_seconds_bucket[5m]))",
            "legendFormat": "P99"
          }
        ]
      },
      {
        "title": "Error Rate",
        "type": "graph",
        "targets": [{
          "expr": "rate(twinmind_errors_total[5m])",
          "legendFormat": "{{error_type}}"
        }]
      },
      {
        "title": "Rate Limit Remaining",
        "type": "gauge",
        "targets": [{
          "expr": "twinmind_rate_limit_remaining"
        }]
      },
      {
        "title": "Audio Hours Processed (24h)",
        "type": "stat",
        "targets": [{
          "expr": "increase(twinmind_transcription_audio_hours[24h])"
        }]
      },
      {
        "title": "AI Tokens Used (24h)",
        "type": "stat",
        "targets": [{
          "expr": "increase(twinmind_ai_tokens_used[24h])"
        }]
      }
    ]
  }
}

Metrics Endpoint

// src/​api/​metrics.ts
import express from 'express';
import { registry } from '../​observability/​metrics';

const router = express.Router();

router.get('/​metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

export default router;

Output

• Prometheus metrics implementation
• Distributed tracing with OpenTelemetry
• Structured logging with Pino
• AlertManager rules
• Grafana dashboard configuration
• Metrics endpoint

Error Handling

Resources

• Prometheus Best Practices
• OpenTelemetry Documentation
• Grafana Dashboard Examples

Next Steps

For incident response, see twinmind-incident-runbook.