Hands On System Design - Distributed Systems Implementation

Hands On System Design - Distributed Systems Implementation

Day 11: Implement Batching in the Log Shipper to Optimize Network Usage

May 22, 2025
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Table of Contents

  1. Introduction to Log Batching

  2. Core Concepts of Batch Processing

  3. System Design: Batching Architecture

  4. Implementing a Batch Log Shipper in Python

  5. Testing Your Implementation

  6. Containerization and Deployment

  7. Advanced Considerations and Optimizations

  8. Assignment: Building a Resilient Batching System

  9. 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.

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