Day 11: Implement Batching in the Log Shipper to Optimize Network Usage
Table of Contents
Introduction to Log Batching
Core Concepts of Batch Processing
System Design: Batching Architecture
Implementing a Batch Log Shipper in Python
Testing Your Implementation
Containerization and Deployment
Advanced Considerations and Optimizations
Assignment: Building a Resilient Batching System
Solution to the Assignment
1. Introduction to Log Batching
Welcome to Day 11 of our distributed systems journey! Yesterday, we implemented UDP support for high-throughput log shipping. Today, we're taking things to the next level by adding batching capabilities to our log shipper.
What is Batching and Why Do We Need It?
Imagine you're sending postcards to friends. You could make individual trips to the mailbox for each card (inefficient), or you could gather several postcards and mail them all in one trip (efficient batching).
In distributed systems, batching follows the same principle. Instead of sending each log message as soon as it's generated, we collect multiple log messages into a "batch" before transmitting them together. This dramatically reduces network overhead and improves system efficiency.