Operations | Monitoring | ITSM | DevOps | Cloud

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.

Last week, I attended the Gartner IT Infrastructure, Operations & Cloud Strategies Conference (IOCS). Gartner IOCS is my favorite conference every year because of the quality and level of the presentations. Gartner analysts deliver most sessions and put a lot of effort into the presentations and supporting research. ‍ I’d like to highlight two sessions that I found to be very informative.

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.

Your images are 404ing all over the place. You’ve got an angry email from a client. Their site is “broken”, images aren’t loading, cumulative layout shift is running riot, and everything is messed up. The crowds are mocking your broken code on Twitter. A fun GIF loaded via a Giphy URL no longer exists. And someone has accidentally deleted an image from the CMS.

When it comes to the best cloud monitoring tools, there are various services you can rely on or choose to support your IT infrastructure. After all, cloud monitoring is critical to ensure the performance, uptime, and overall health of cloud services. Numerous teams in modern IT, SaaS, and app development companies, including DevOps, SREs, and security analysts depend on cloud monitoring solutions.

Table of contents This is the seventh part of our 12-day Advent of Monitoring series. In this series, Checkly's engineers will share practical monitoring tips from their own experience. At Checkly, we manage various scheduled jobs, some of which play a crucial role in our application's functionality, and others exist to support different teams within Checkly.

Despite the siren song of AI in the keynotes, visitors were far more focused on solving real-world problems. These are the issues that have plagued IT practitioners for years, if not decades: troubleshooting and validating performance and availability of their applications, services, and infrastructure.

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.

The holiday season is here and it’s time for everyone’s favorite guessing game: predictions for next year. It’s an interesting one this year because there are a lot of dynamics to consider, and trying to dial in on just a few is a slight to many other topics. Geopolitics, regional economic recessions — these are covered in a wide variety of industry publications, and I’ll yield the floor to them this year.

In part 1 of this 2 part blog we looked at some common engineering tradeoffs. But how might someone navigate these tradeoffs and build a model that works for their product? Here are some core concepts that can help along the way.