Skills Development Algolia Observability Instrumentation Guide

Algolia Observability Instrumentation Guide

v20260423
algolia-observability
This skill provides a comprehensive guide to instrumenting Algolia search services for enterprise-grade observability. It integrates core monitoring patterns, including Prometheus metrics (latency, error rates, request counts), OpenTelemetry distributed tracing, and structured logging. Use this to achieve deep insights into search performance, user experience, and system health in production environments.
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Overview

Algolia Observability

Overview

Algolia provides built-in analytics in the dashboard, but production systems need application-level observability: latency histograms, error rate counters, distributed traces, and alerts. This skill instruments the algoliasearch v5 client with Prometheus, OpenTelemetry, and structured logging.

Key Metrics to Track

MetricTypeWhy It Matters
Search latency (P50/P95/P99)HistogramUser experience, SLA compliance
Search requests/secCounterCapacity planning, cost tracking
Error rate by typeCounterDetect API issues before users report
Index freshness (last updated)GaugeData pipeline health
Record countGaugeCost monitoring, data integrity

Instructions

Step 1: Instrumented Algolia Client Wrapper

// src/algolia/instrumented-client.ts
import { algoliasearch, ApiError } from 'algoliasearch';
import { Counter, Histogram, Gauge, Registry } from 'prom-client';

const registry = new Registry();

const searchLatency = new Histogram({
  name: 'algolia_search_duration_seconds',
  help: 'Algolia search request duration in seconds',
  labelNames: ['index', 'status'],
  buckets: [0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5],
  registers: [registry],
});

const searchTotal = new Counter({
  name: 'algolia_search_requests_total',
  help: 'Total Algolia search requests',
  labelNames: ['index', 'status'],
  registers: [registry],
});

const searchErrors = new Counter({
  name: 'algolia_errors_total',
  help: 'Total Algolia errors by type',
  labelNames: ['index', 'error_type', 'status_code'],
  registers: [registry],
});

const indexRecords = new Gauge({
  name: 'algolia_index_records',
  help: 'Number of records in Algolia index',
  labelNames: ['index'],
  registers: [registry],
});

const client = algoliasearch(process.env.ALGOLIA_APP_ID!, process.env.ALGOLIA_ADMIN_KEY!);

export async function instrumentedSearch<T = any>(
  indexName: string,
  searchParams: Record<string, any>
) {
  const timer = searchLatency.startTimer({ index: indexName });

  try {
    const result = await client.searchSingleIndex<T>({ indexName, searchParams });
    timer({ status: 'success' });
    searchTotal.inc({ index: indexName, status: 'success' });
    return result;
  } catch (error) {
    timer({ status: 'error' });
    searchTotal.inc({ index: indexName, status: 'error' });

    if (error instanceof ApiError) {
      searchErrors.inc({
        index: indexName,
        error_type: error.status === 429 ? 'rate_limit' : 'api_error',
        status_code: String(error.status),
      });
    } else {
      searchErrors.inc({
        index: indexName,
        error_type: 'network',
        status_code: '0',
      });
    }
    throw error;
  }
}

// Periodic index stats collection (run every 5 minutes)
export async function collectIndexMetrics() {
  const { items } = await client.listIndices();
  for (const idx of items) {
    indexRecords.set({ index: idx.name }, idx.entries || 0);
  }
}

export { registry };

Step 2: Prometheus Metrics Endpoint

// src/api/metrics.ts (Express example)
import express from 'express';
import { registry, collectIndexMetrics } from '../algolia/instrumented-client';

const app = express();

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

// Collect index stats every 5 minutes
setInterval(collectIndexMetrics, 5 * 60 * 1000);

Step 3: OpenTelemetry Distributed Tracing

// src/algolia/tracing.ts
import { trace, SpanStatusCode, type Span } from '@opentelemetry/api';

const tracer = trace.getTracer('algolia-service', '1.0.0');

export async function tracedSearch<T>(
  indexName: string,
  query: string,
  searchParams: Record<string, any> = {}
): Promise<T> {
  return tracer.startActiveSpan(`algolia.search ${indexName}`, async (span: Span) => {
    span.setAttribute('algolia.index', indexName);
    span.setAttribute('algolia.query', query);
    span.setAttribute('algolia.hitsPerPage', searchParams.hitsPerPage || 20);

    try {
      const result = await client.searchSingleIndex<T>({
        indexName,
        searchParams: { query, ...searchParams },
      });

      span.setAttribute('algolia.nbHits', result.nbHits);
      span.setAttribute('algolia.processingTimeMS', result.processingTimeMS);
      span.setStatus({ code: SpanStatusCode.OK });
      return result as T;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Step 4: Structured Logging

// src/algolia/logger.ts
import pino from 'pino';

const logger = pino({ name: 'algolia', level: process.env.LOG_LEVEL || 'info' });

export function logSearch(params: {
  index: string;
  query: string;
  nbHits: number;
  processingTimeMS: number;
  page: number;
  userId?: string;
}) {
  logger.info({
    event: 'algolia.search',
    index: params.index,
    query: params.query,
    hits: params.nbHits,
    latency_ms: params.processingTimeMS,
    page: params.page,
    user: params.userId,
  });
}

export function logSearchError(params: {
  index: string;
  query: string;
  error: string;
  statusCode?: number;
}) {
  logger.error({
    event: 'algolia.search.error',
    index: params.index,
    query: params.query,
    error: params.error,
    status_code: params.statusCode,
  });
}

Step 5: Alert Rules (Prometheus AlertManager)

# alerts/algolia.yml
groups:
  - name: algolia
    rules:
      - alert: AlgoliaHighErrorRate
        expr: |
          rate(algolia_errors_total[5m]) /
          rate(algolia_search_requests_total[5m]) > 0.05
        for: 5m
        labels: { severity: warning }
        annotations:
          summary: "Algolia error rate > 5% for 5 minutes"

      - alert: AlgoliaHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(algolia_search_duration_seconds_bucket[5m])
          ) > 0.5
        for: 5m
        labels: { severity: warning }
        annotations:
          summary: "Algolia P95 search latency > 500ms"

      - alert: AlgoliaRateLimited
        expr: rate(algolia_errors_total{error_type="rate_limit"}[5m]) > 0
        for: 2m
        labels: { severity: critical }
        annotations:
          summary: "Algolia returning 429 rate limit errors"

      - alert: AlgoliaIndexStale
        expr: algolia_index_records == 0
        for: 10m
        labels: { severity: warning }
        annotations:
          summary: "Algolia index has 0 records — possible sync failure"

Grafana Dashboard Queries

# Search rate: rate(algolia_search_requests_total[5m])
# Error rate: rate(algolia_errors_total[5m]) / rate(algolia_search_requests_total[5m])
# P50 latency: histogram_quantile(0.5, rate(algolia_search_duration_seconds_bucket[5m]))
# P95 latency: histogram_quantile(0.95, rate(algolia_search_duration_seconds_bucket[5m]))
# Records per index: algolia_index_records

Error Handling

IssueCauseSolution
Missing metricsClient not instrumentedUse instrumentedSearch wrapper
High cardinalityToo many label valuesDon't use query text as label
Trace gapsMissing context propagationEnsure OTel context flows through async
Alert stormsThresholds too sensitiveAdd for: 5m minimum duration

Resources

Next Steps

For incident response, see algolia-incident-runbook.

Info
Category Development
Name algolia-observability
Version v20260423
Size 8.25KB
Updated At 2026-04-28
Language