kbabuji

Promises in Python

What Are Promises? #

In JavaScript, Promises are objects that represent the eventual completion (or failure) of an asynchronous operation and its resulting value. They provide a powerful way to manage asynchronous code, enabling developers to write cleaner and more maintainable logic.

Promises allow us to associate handlers for both the success and failure of an asynchronous operation. By treating asynchronous code similarly to synchronous code, they reduce the complexity and improve the readability of workflows that would otherwise be riddled with convoluted callbacks—commonly referred to as “callback hell.”

Read more ...

From Jekyll to Hugo

Hugo logo

I recently moved my blog from Jekyll, a Ruby-based static site generator, to Hugo, a popular alternative built in Golang. In this article, I’ll walk through the rationale behind this migration, share the steps I took, and include a few custom code snippets I created along the way. This is not intended as a tutorial on setting up a blog with Hugo — there are plenty of excellent videos and documentation on Hugo’s site for that. Instead, I’ll focus on my experience, insights, and the lessons learned that may be helpful for anyone considering a similar transition.

You could find an older version of my site at archive.

Read more ...

Understanding Skip lists

Suppose you have a sorted collection of elements and need to perform add, delete, and search operations efficiently. Skip lists offer an efficient, probabilistic approach to these operations, achieving an average time complexity of \(O(\log{n})\) for search, insertion, and deletion. While other data structures, such as red-black trees and AVL trees, can provide the same \(O(\log{n})\) efficiency guarantees in both the average and worst cases, skip lists have the advantage of being simpler to implement and understand.

With basic data structures like sorted arrays, you can search for elements in \(O(\log{n})\) time using binary search. However, insertion and deletion require shifting elements, leading to \(O(n)\) time complexity for these operations. Conversely, linked lists allow efficient \(O(1)\) insertions and deletions once the target location is found, but finding that location requires \(O(n)\) time in the worst case.

How Skip Lists improve efficiency #

So, how do skip lists achieve \(O(\log{n})\) efficiency for all three operations? Skip lists accomplish this by introducing multiple levels, each serving as an “express lane” that allows you to skip over sections of the list. The highest levels contain fewer nodes, allowing you to make large jumps, while the lowest level contains all nodes, allowing for precise adjustments when needed. This structure enables fast traversal through the express lanes and, when necessary, you can exit to a lower level for finer-grained searching.

Read more ...

Refining Load Balancer

In the last article, we covered the basics of building a Layer 7 load balancer in Go, touching on routing, SSL termination, and rate limiting. Since then, the focus has been on improving performance, maintainability, and scalability.

This article highlights key upgrades like adopting clean architecture, switching to configuration files, and using connection pooling to enhance backend communication. These changes make the system more flexible and set the stage for even more optimizations, including advanced health checkers, which we’ll explore in the next article.

Read more ...

Building a Layer 7 Load Balancer

Load balancers are essential for applications or services that handle high volumes of traffic, ensuring that they can scale efficiently to meet demand. Modern load balancers have evolved into comprehensive traffic management solutions, often incorporating rate limiting, caching, DDoS protection, and more, making them indispensable for high-scale systems.

What is a load balancer? #

Imagine you’re at an airport, standing in line for the security check. There is a single line of passengers, but there are five booths with agents checking boarding passes and IDs. At the front of the line, there is an agent directing passengers to available booths. This agent acts like a basic load balancer, distributing incoming requests (passengers) to backend servers (TSA agents) for processing.

Read more ...