Outages are unexpected events that can suddenly stop an organization's operations. Whether it's a network issue, a key application going down, or a system crash, these problems can cause confusion and disrupt work. Teams scramble to identify the problem, while employees are left in the dark, uncertain about the impact or duration of the issue. A lack of real-time communication can lead to frustrated employees, delayed responses, and prolonged recovery times.

In the first post, we introduced system tables and how to use them to inspect your cluster. In this follow up, we’ll explain some techniques to improve the speed of system table queries.

Keeping a Kafka cluster optimized can feel like a balancing act. Every piece—brokers, partitions, producers, and consumers—has to work in harmony, or you’ll start running into bottlenecks. To get Kafka to run smoothly and handle growing traffic loads, balancing load across the system is key. Let’s go over practical load-balancing techniques that can improve Kafka performance, keep everything running efficiently, and prevent data slowdowns from building up.

This month, Fortune.com reported that TikTok’s web scraper — known as Bytespider — is aggressively sucking up content to fuel generative AI models. We noticed the same thing when looking at bot management analytics produced by HAProxy Edge — our global network that we ourselves use to serve traffic for haproxy.com. Some of the numbers we are seeing are fairly shocking, so let’s review the traffic sources and where they originate.

You’ve found some Long Animation Frames (LoAFs) impacting your site, now you need to fix them! LoAFs can make animations feel sluggish, delay user interactions, and generally reduce your site’s responsiveness, all of which contribute to a frustrating experience for users. Fortunately, by analyzing LoAF data and addressing common performance bottlenecks, you can dramatically improve how smoothly your site runs.

Though you might not immediately notice it the next time you log in, Grafana’s frontend has undergone a major upgrade. We recently migrated our dashboard architecture to utilize the Grafana Scenes library, enabling the creation of more stable, dynamic, and flexible Scenes-powered dashboards. Yes, the UI is pretty much the same, but under the hood, the engine responsible for visualizing the dashboards used by millions of people around the world has largely been rewritten.

This is an updated version of an earlier blog post that now includes links to our documentation. Full-text searches are a marvel of modern computing. In less than a second, search engines can match a query against hundreds of millions of documents. In the early days of search engines, you often had to use specific search operators and terms to get accurate results.

Developer productivity is ultimately a measure of the efficiency and effectiveness with which software developers produce high-quality code and complete projects. Where this becomes a bit more complicated is in the relationships between those efforts and the measurements that reflect them.