Over the past several years, one topic that has become of increasing importance for DevOps and site reliability engineering (SRE) teams is AIOps. Artificial intelligence for IT Operations (AIOps) is the application of artificial intelligence (AI), machine learning (ML), and analytics to improve the day-to-day operational work for IT operations teams.

It’s 5:00 pm on a Friday. You’re wrapping up work, ready to head into the weekend, when one of your high-value customers Slacks you that something’s not right. Requests to their service are randomly timing out and nobody can figure out what’s causing it, so they’re looking to your team for help. You sigh as you know it’s one of those all-hands-on-deck situations, so you dig out your phone and type the "going to miss dinner" text.

For many of us in the software development world, observability tools are a must-have for effectively debugging applications and infrastructure. And doing the job right means selecting the right observability tool. Some might look for a fully featured enterprise solution, while others may simply search for the best open-source solution. But regardless of your approach, you have a number of considerations when selecting the right observability tool.

You know the old saying, I’m sure: “April deploys bring May joys.” Okay, maybe it doesn’t go exactly like that, but after reading what we’ve been up to for the past month, I think it might be time for an update. Let’s dive into our Feature Focus April 2023 edition.

Code instrumentation is closely tied to debugging. Ask one of the experienced developers and they will swear by it for their day-to-day debugging needs. With modest beginnings in the form of print statements that label program execution checkpoints, present-day developers employ a host of advanced techniques for code instrumentation. When carried out in the right way, it improves developer productivity and also reduces the number of intermediate build/deployment cycles for every bug fix.