Real-time Analytics Platform

Overview

Built a real-time analytics platform from scratch that processed millions of events per day for enterprise customers. This platform became the core data infrastructure for Slingshot Analytics.

Challenge

Existing analytics solutions couldn't handle:

• Real-time event processing at scale
• Complex multi-tenant data isolation
• Flexible querying across multiple dimensions
• Cost-effective storage and retrieval

Approach

Architecture

The platform was designed with these core principles:

• Event-driven architecture
• Horizontal scalability
• Multi-tenant data isolation
• Flexible querying layer

Key Components

1. Event Ingestion Pipeline: High-throughput event processing
2. Storage Layer: Optimized for time-series data
3. Query Engine: Fast aggregation and filtering
4. API Layer: RESTful APIs for all operations

Impact

• Processed 10M+ events per day at peak
• Sub-second query response times
• Served 100+ enterprise customers
• Maintained 99.9% uptime

Technical Stack

• Go (event processing)
• PostgreSQL (metadata)
• Redis (caching)
• React (dashboard)