Fulfill all your food delivery orders this December 31st by taming High Cardinality data 😉

In the early 1990s, as the digital world stood on the cusp of an explosive expansion, the foundational structure of the internet faced a critical challenge: the classful IP addressing system was buckling under its own rigidity and inefficiency. Locked into fixed classes (A, B, and C), this system squandered valuable IP space, leaving the burgeoning network gasping for air as it grappled with rapidly depleting IP addresses.

Managing incoming web traffic for your applications is essential to ensuring optimal performance, preventing abuse, and maintaining the security of your cloud infrastructure. To accomplish this, one of the tools HAProxy Enterprise users have at their disposal is rate limiting—the practice of preventing clients from making too many requests and using system resources unfairly.

One of the most frustrating moments as a Kubernetes developer is when you go to launch your pod, but it fails to start because of a problem during initialization. Init containers are incredibly useful for setting up a pod before handing it off to the main container, but they introduce an additional point of failure. In this post, we'll take an in-depth look at init containers in Kubernetes: what they are, how they work, how they can fail, and what that means for your Kubernetes deployments.

Monitoring the performance of your MySQL database will help identify performance bottlenecks, inefficient queries, and resource-intensive processes. By tracking metrics like query execution times, server load, and resource usage, administrators can optimize configurations and fine-tune the database for better efficiency and speed. Additionally, monitoring any running process allows for the early detection of potential problems such as server overload, disk space shortages, or network issues.