I'm a bit of an AI skeptic. And even though GitHub Copilot is my daily auto-completion on steroids, I always double-check the code generated by LLMs. If you're using AI for coding, you probably know that the results are sometimes surprisingly good and other times shockingly terrible. Lately, I have seen more and more articles and even docs recommending ChatGPT to generate Playwright tests. Could this be true? Are ChatGPT and friends really that good at generating test code?

Data sovereignty has become increasingly critical for UK enterprises, particularly in regulated sectors like finance, healthcare, and the public sector. This is due in part to growing concerns over data security and the need for compliance with increasingly stringent regulations.

Businesses, like pretty much all of us, continue to grow ever more reliant upon network connectivity. When that connectivity falters, it can be extremely disruptive—and very costly. According to a report in PCMag, an internet shutdown of one minute can cost a business like Amazon almost $978,000 in revenue losses. For Alphabet, the number is $538,000.

Managing assets remotely has become increasingly important in today’s dynamic and distributed work environment. Remote asset management allows organizations to track and manage their assets from any location, ensuring efficiency, security, and productivity. This guide explores the concept of remote asset management, its key features, implementation strategies, and the benefits it offers to businesses.

Let’s face it: managing IT operations today feels a bit like spinning plates in a hurricane. Alerts are pinging, systems are stalling, users are shouting (as if that’ll help), and all the while, you’re drowning in a sea of repetitive, manual tasks. Sound familiar? Welcome to the wonderfully chaotic world of IT. But it doesn’t have to be this way.

During critical incidents, teams often scramble to pull data from multiple sources, wasting precious time and delaying issue resolution. Manual processes hamper response and create blind spots that can lead to costly oversights. Data integration addresses this head-on. Data integration collects incident management information from various sources, such as monitoring tools, logs, and user reports, into a unified system.

Maximize your observability with tracing tools to track requests, identify bottlenecks, and optimize system performance across services.

Proactive monitoring helps IT teams spot issues early, ensuring smooth operations, minimal disruptions, and a better user experience.

Demystifying Docker logs: From basic tail commands to advanced log management, learn how to debug and monitor containers in production.

Recently, I have seen a trend of enterprises moving toward OpenTelemetry (OTel) for application tracing. Tail sampling, in particular, has emerged as a preferred approach to gain actionable insights while balancing data volume and cost. OpenTelemetry offers developers and practitioners the ability to instrument their code with open-source tools, moving away from vendor-provided tools for application instrumentation.