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Learn how to set up health checks and monitoring for VectoriaDB.

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Health Check Endpoint

src/routes/health.ts
import { Router } from 'express';
import { toolIndex } from '../vectoriadb';

const router = Router();

router.get('/health', async (req, res) => {
  try {
    const stats = toolIndex.getStats();

    res.json({
      status: 'healthy',
      vectoriadb: {
        documents: toolIndex.size(),
        dimensions: stats.dimensions,
        memoryBytes: stats.estimatedMemoryBytes,
        model: stats.modelName,
      },
    });
  } catch (error) {
    res.status(503).json({
      status: 'unhealthy',
      error: error.message,
    });
  }
});

router.get('/ready', async (req, res) => {
  try {
    // Verify VectoriaDB is initialized and can search
    await toolIndex.search('health check', { topK: 1 });
    res.json({ status: 'ready' });
  } catch (error) {
    res.status(503).json({
      status: 'not ready',
      error: error.message,
    });
  }
});

export default router;

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Metrics Collection

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Basic Metrics

src/metrics.ts
import { toolIndex } from './vectoriadb';

export function collectMetrics() {
  const stats = toolIndex.getStats();

  return {
    // Capacity metrics
    vectoriadb_documents_total: toolIndex.size(),
    vectoriadb_memory_bytes: stats.estimatedMemoryBytes,
    vectoriadb_dimensions: stats.dimensions,
  };
}

​
Prometheus Metrics

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

const registry = new Registry();

// Search metrics
const searchCounter = new Counter({
  name: 'vectoriadb_search_total',
  help: 'Total number of searches',
  registers: [registry],
});

const searchLatency = new Histogram({
  name: 'vectoriadb_search_latency_seconds',
  help: 'Search latency in seconds',
  buckets: [0.001, 0.005, 0.01, 0.05, 0.1, 0.5],
  registers: [registry],
});

const documentCount = new Gauge({
  name: 'vectoriadb_documents_total',
  help: 'Total documents in index',
  registers: [registry],
});

// Instrumented search
export async function search(query: string, options?: SearchOptions) {
  const timer = searchLatency.startTimer();

  try {
    const results = await toolIndex.search(query, options);
    searchCounter.inc();
    return results;
  } finally {
    timer();
    documentCount.set(toolIndex.size());
  }
}

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

​
Logging

src/logging.ts
import { toolIndex } from './vectoriadb';

// Log search operations
export async function searchWithLogging(query: string, options?: SearchOptions) {
  const startTime = Date.now();

  try {
    const results = await toolIndex.search(query, options);

    console.log({
      event: 'vectoriadb_search',
      query: query.substring(0, 50),
      results: results.length,
      topScore: results[0]?.score,
      latencyMs: Date.now() - startTime,
    });

    return results;
  } catch (error) {
    console.error({
      event: 'vectoriadb_search_error',
      query: query.substring(0, 50),
      error: error.message,
      latencyMs: Date.now() - startTime,
    });
    throw error;
  }
}

​
Docker Health Check

Dockerfile
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s \
  CMD curl -f http://localhost:3000/health || exit 1

​
Kubernetes Probes

k8s/deployment.yaml
livenessProbe:
  httpGet:
    path: /health
    port: 3000
  initialDelaySeconds: 60
  periodSeconds: 30
  failureThreshold: 3

readinessProbe:
  httpGet:
    path: /ready
    port: 3000
  initialDelaySeconds: 30
  periodSeconds: 10
  failureThreshold: 3

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Alerting Recommendations

MetricWarningCritical
Search latency p99> 100ms> 500ms
Error rate> 1%> 5%
Memory usage> 70%> 90%
Document countN/A> maxDocuments

Production Config

Configuration options

Docker

Container deployment

Error Handling

Error types