Day 22: Low-Latency Consumer Optimization
Building StreamSocial’s Lightning-Fast Notification Engine
What We’re Building Today
Today you’ll build a Kafka consumer that delivers notifications faster than you can blink. We’re talking about processing messages in under 50 milliseconds - that’s half the time it takes to snap your fingers. Here’s what we’ll cover:
Optimize Kafka consumers for ultra-fast message processing
Configure poll timeouts and fetch settings for minimal latency
Build StreamSocial’s real-time notification delivery pipeline
Create a monitoring dashboard to track every millisecond
Understanding the Speed Challenge
Think about Instagram or Twitter. When someone likes your post, you get a notification almost instantly. That’s not magic - it’s a carefully optimized system that processes millions of events every hour while keeping latency under 100ms.
StreamSocial needs the same performance. Our users expect instant notifications for messages, likes, and trending content. Default Kafka settings prioritize throughput (handling lots of messages) over latency (processing each message quickly). Today, we flip that equation.
The Three Performance Levers
Poll Timeout: Your Response Time
The poll(duration) method tells Kafka how long to wait for new messages. Think of it like checking your phone:
Short timeout (1-10ms): You check constantly, see messages immediately, but use more battery (CPU)
Long timeout (500ms+): You check occasionally, messages pile up, but save battery
For notifications, we want near-instant responses, so we’ll use 1ms timeouts.
Fetch Size: How Much to Grab
These settings control how Kafka batches messages:
fetch.min.bytes: Minimum data before returning (we’ll use 1 byte - don’t wait!)fetch.max.wait.ms: Maximum wait time for batching (we’ll use 10ms - barely any wait!)
Smaller fetches mean lower latency but more network calls. For notifications, speed wins.
Processing Loop: The Engine
Your processing loop determines how fast you handle each message:
Single-threaded: Simple, predictable
Multi-threaded: Parallel processing
Async: Non-blocking I/O for downstream services
We’ll use async processing to prevent slow operations from blocking other messages.
How This Fits Into StreamSocial
