Operations | Monitoring | ITSM | DevOps | Cloud

A couple of years ago, Laravel introduced a great feature which allows to run PHPUnit / Pest tests in parallel. This results in a big boost in performance. By default, it determines the concurrency level by taking a look at the number of CPU cores your machine has. So, if you're using a modern Mac that has 10 CPU cores, it will run 10 tests at the same time, greatly cutting down on the time your testsuite needs to run completely.

In a pretty significant shift for internet security and subsequently certificate management, the CA/Browser Forum has officially voted to reduce the maximum validity period of TLS certificates to just 47 days by March 15, 2029. This move aims to enhance digital security and trust across the web. But as these changes approach, it'll become increasingly crucial for organizations to understand their implications and prepare accordingly. Automation will likely become mandatory.

When major tech companies maintain high availability while others struggle with frequent outages, the difference often comes down to one thing: effective metrics monitoring. This guide will walk you through everything you need to know about metrics monitoring, from fundamental concepts to advanced strategies.

In modern software architecture, applications aren't just getting bigger—they're getting more distributed. With microservices, serverless functions, and containers running across multiple environments, understanding what's happening inside your systems can feel like trying to track a single raindrop in a storm. That's where traces and spans come in. These observability tools aren't just buzzwords—they're your secret weapon for making sense of complex distributed systems.

In the world of business, AI is like a superhero - but even superheroes need the right tools to do their job. To make AI truly effective, it’s important to pair it with automated data capture across your operations. Just like us, AI needs a complete picture to make smart decisions and avoid mistakes. Without all the details, it can’t spot patterns, catch defects, or find hidden inefficiencies.

Real-time collaboration and virtual meetings have become part of the basic fabric of how work gets done. Because different collaboration platforms do different things really well, most organizations tend to mix and match them to fit their requirements. Teams and Zoom are two of the most common pairings. A study commissioned by Zoom and conducted by the research firm, Metrigy found that 62% of companies use both.

If your clients are like most, they use multiple collaboration platforms to drive business and get work done. A common combo is Microsoft Teams and Zoom: over 60% of organizations use both, and together the two have a more than 80% share of the videoconferencing market. More platforms mean more complexity for you to manage — more parameters to watch, more tools to bounce between to keep an eye on things.

I recently wrote an update to my old piece on the cost of observability, on how much you should spend on observability tooling. The answer, of course, is “it’s complicated.” Really, really complicated. Some observability platforms are approaching AWS levels of pricing complexity these days.

Every day development teams around the world release new software. But what happens to prior releases that are no longer in production? Most organizations save them, typically due to internal policies, external regulations, or simply the fear of losing data. Organizations typically take varied approaches to retaining their prior releases.

Modern applications are often built using microservices: Small, independent components that work together. This makes systems more flexible and scalable, but also harder to monitor. In this guide, we’ll explain what microservice monitoring is, why it’s different from traditional approaches, and how to do it effectively. Whether you’re starting from scratch or improving an existing setup, this article will help you monitor microservices with confidence.