Operations | Monitoring | ITSM | DevOps | Cloud

Frequently in support conversations and posts on Playwright forums, a problem has come up that’s a little bit hard to describe, but comes down to synchronous testing: developers writing a series of Playwright tests that operate on the assumption that one of the tests will either run first or run last, and perform the function of a setup and cleanup script.

A faulty engine in a high-performance car; how disappointing can that be? The same is the case of a slow-loading, poorly performing webpage for any digital entity. All that the page can gain will be a group of tired and irritated customers and a loss of trust in the brand. Modern businesses need a fast, reliable, and seamless digital experience. Proactive monitoring of the user experience—understanding how users interact with all digital touchpoints—is vital.

When something goes wrong, the first question is always: what changed? Whether it’s an unexpected change to your on-call schedule, a broken automation, or a modified Runbook that just seems off, understanding the issue starts with knowing who made what change, when it happened, and what exactly changed. But in an organization with many users, keeping track of every action can feel impossible.

AI platforms have experienced several service interruptions over the past few months. We’ve all seen the memes fly when ChatGPT, Gemini or Perplexity go down. They’re funny at first, but then reality hits: if you rely on AI tools for work or business, these outages can grind your day to a halt.

PowerShell is a command-line-based shell and scripting language that automates tasks on the Windows OS. PowerShell lets you automate any task normally done on Windows, like installing programs or updating software, allowing you to complete those tasks faster and on a larger scale. You can even extend its powers with Azure PowerShell to control Azure’s robust functionality, allowing you to use cmdlets to provision VMs, create cloud services, and carry out a number of other complex processes.

B2B eCommerce is finally catching up. While B2C has spent the last decade perfecting oneClick checkouts and AI-powered recommendations, B2B has been stuck in the past—relying on email chains, phone orders, and clunky procurement systems. But that’s changing. Fast. With B2B eCommerce sales already more than double D2C sales (we’re talking $7.7 trillion vs. $3.8 trillion), companies are finally realizing they need to streamline and automate the way they sell.

Shopify is a fantastic tool for organizations who want to sell products, but don’t want to build or maintain an e-commerce platform themselves. Even some of the largest brands that have built their own e-commerce platforms in the past have seen the value of using Shopify to accelerate their business. As your Shopify site scales and grows, however, you may need more insight into the performance of your store.

I first started using AI coding assistants in early 2021, with an invite code from a friend who worked on the original GitHub Copilot team. Back then, the workflow was just single-line tab completion, but you could also guide code generation with comments and it’d try its best to implement what you want. Fast forward to 2025. There’s now a wide range of coding assistants that are packed with features.

Kubernetes has revolutionized how organizations deploy, scale, and manage containerized applications, offering unprecedented efficiency and flexibility. However, the very characteristics that make Kubernetes so powerful—its dynamic, distributed, and ephemeral nature—also create significant challenges for monitoring. Without robust monitoring capabilities, organizations struggle to identify and resolve performance bottlenecks, optimize resource utilization, and maintain security.