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High-Throughput Analytics Platform
A real-time analytics pipeline processing 50,000+ events per minute using stream processing and in-memory data stores.
5
Technologies used
2
Features implemented
1
Challenges solved
Open Source
Status
Tech Stack
Backend
Go
Cloud & DevOps
KubernetesGrafana
Database
PostgreSQL
Impact
Processes 50,000+ events/minute with sub-100ms query latency.
Implementation Details
- Built with Go for high-throughput stream processing, Kafka for event buffering, and Kubernetes for orchestration.
- Grafana dashboards provide real-time visibility into system health.
Challenges & Solutions
- Ensuring exactly-once processing semantics in a distributed streaming system required careful coordination between Kafka offsets and database transactions.