Day 86: GraphQL for Flexible Log Queries – The Netflix Approach to Log Analytics

Hey everyone!

I’ve been working through this awesome 254-day system design series, and just completed Day 86 where I built a complete GraphQL API for log processing. Honestly didn’t expect to learn this much in one session.

What I built:

• GraphQL schema with flexible querying (no more multiple REST calls!)
• Real-time WebSocket subscriptions for live data streaming
• React frontend with Apollo Client integration
• DataLoader pattern to prevent N+1 queries
• Redis caching layer for performance
• Full Docker deployment setup

The „aha“ moment: Coming from REST APIs, I always wondered why companies like Netflix and Uber use GraphQL for their analytics dashboards. Now I get it – being able to write one query like this:

query { logs(filters: {service: "payment", level: "ERROR"}) { id message relatedLogs { service timestamp } stats { errorCount averageResponseTime } } } 

Instead of making 3-4 separate REST calls is game-changing for performance.

Coolest part: The real-time subscriptions. Watching logs stream live into the React dashboard felt like magic. It’s the same pattern Slack uses for real-time messaging.

Most challenging part: Getting the DataLoader pattern right. Easy to accidentally create N+1 query problems in GraphQL, but once you understand batching, it’s actually more efficient than REST.

The tutorial walks through everything step-by-step – from basic schema design to production deployment. Includes working code for both Python backend (FastAPI + Strawberry GraphQL) and React frontend.

For anyone curious about GraphQL but intimidated by the complexity, this was actually way more approachable than I expected. The schema-first approach makes everything really clear.

Link to full tutorial: Day 86: GraphQL for Flexible Log Queries – The Netflix Approach to Log Analytics

Happy to answer questions about GraphQL, the DataLoader pattern, or anything else! Still buzzing from getting the subscriptions working 😄