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 - ...
(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. ...
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. ...
Jupyterlab is a definite improvement on the older IPython notebook interface - both in features and in appearance. There is now even an in-built “Dark Theme” that can be enabled. But is that all? As we know, Jupyterlab is a browser based app and is ipso facto, written on a base of HTML, CSS and Javascript. So if we want to change the appearance over and above what we get out of the box with jupyterlab, we can. Now, it is possible to make any CSS changes by hacking into the internals of the notebook, but thanks to a nifty Jupyterlab extension by Adam Wallner, we don’t have to. ...