DDIA on EverythingPython

Reading DDIA - Part 3

Thu, 26 Sep 2024 00:00:00 +0000

Chapter 1 - Reliable, Scalable and Maintainable Applications

In [[Reading DDIA - Part 2]] , I read about the second way in which design decisions are typically driven - Scalability. This section is about what the book says is the third factor - Maintainability.

What is a maintainable system?

My thoughts prior to reading the section -

Something they said in the San Diego Machine Learning struck me as my reaction as well - Maintainability is not one of the “concerns” I would have listed for a data intensive system. But now that it is, let’s think about it - What does it mean to maintain a system? My interpretation is - how would the system be set up for functioning smoothly over time? To that end,

Reading DDIA - Part 2

Wed, 25 Sep 2024 00:00:00 +0000

Chapter 1 - Reliable, Scalable and Maintainable Applications

In [[Reading DDIA - Part 1]] , I read about Reliability. The next section is Scalability . First let me talk about the assumptions I made about the term Scalability, what I understand from it prior to reading Martin Kleppman’s thoughts on the topic -

What is a scalable system?

My thoughts prior to reading the section -

Scale refers to how does a system grow. Growth can be needed for multiple reasons -

Reading DDIA - Part 1

Mon, 23 Sep 2024 00:00:00 +0000

(Here’s the preface in case you missed it - [[Reading DDIA - Preface]])

Chapter 1 - Reliable, Scalable and Maintainable Applications

This chapter’s goal is to effectively give us a high level overview of what this book is fundamentally about -

Thinking about data systems along the axes of :

Reliability
Scalability
Maintainability

What is a reliable system?

My thoughts before reading the section :

A system that is available to return results/outputs that are expected of it when it is employed.
If I’m accessing an API, if the API is available 99 out of 100 times, then its reliability is 99%
If a server is available for 23 hrs 45 minutes per day then its availability is 23.75/24 = 98.9%
But is availability == reliability? Let’s see.
A reliable human is someone who does something that he says he will do or is expected to do every time. Similarly a reliable system is one that returns the expected results every time that they are used.
An ATM is reliable if I can withdraw money from it in the denominations that I want, when I want it. For example, the ATM in Puttenahalli , JP Nagar is perpetually unavailable. Everytime I go there, the system is under maintenance. It is 0% reliable.

Let’s read the chapter.

Reading DDIA - Preface

Sun, 22 Sep 2024 00:00:00 +0000

Over the next few weeks, I want to read a book that has been long-pending - “Designing Data Intensive Applications” by Martin Kleppman. I’ve been building data applications for a while now but most, if not all the learnings, have been through trial and error after error after error. I’ve learnt a decent bit from observing more senior engineers, architects, design documents and building architectures little by little on my own, but not yet I think, in a structured, deliberate manner. I’m hoping to learn that in this book along with the other books I will likely have to refer along the way.