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Real-Time Analytics Engine

High-performance analytics engine processing millions of events per day with microservices architecture and event-driven design.

Real-Time Analytics Engine - Backend Service

Overview

Real-Time Analytics Engine is an event-driven system that turns product telemetry into live dashboards and queryable metrics. It's built for high throughput with low latency and a clean data contract.

Goal: process 10M+ events/day with sub-100ms query experiences for key dashboards.

Pipeline

  1. Ingest: events published to Kafka with schema validation
  2. Process: stream consumers aggregate and enrich
  3. Store: PostgreSQL for canonical data + caches for hot paths
  4. Serve: GraphQL API for flexible slicing and filtering

Features

  • Metric definitions with consistent naming and lineage
  • Dashboards for real-time monitoring and growth insights
  • Anomaly detection with alerting hooks
  • Retention: configurable policies and sampling

Operational excellence

I added guardrails for production readiness: backpressure handling, retries, and observability. Documentation includes runnable examples with links and rich notes.

  • Tracing: request IDs across services
  • Reliability: replayable consumers and idempotent writes
  • Docs: design doc and metric catalog

Result: stable performance during traffic spikes with clear dashboards that teams can trust.

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