Operations | Monitoring | ITSM | DevOps | Cloud

For decades, PHP has powered the web using a simple model: process a request, send a response, then shut down. This model, especially in the form of CGI and PHP-FPM, is easy to understand but increasingly inefficient for modern web demands.

Today, we’re announcing the general availability of Lumigo Copilot, the most intelligent AI-powered observability assistant on the market, built for the complexities of modern microservices. Copilot emerged from a simple realization: Distributed systems produce too much fragmented data across too many layers, making troubleshooting slow, reactive, and deeply manual. Copilot changes that.

Your organization has a bold modernization roadmap. Cloud migration. Application updates. Enhanced customer experiences. New revenue streams. The business case is compelling, the stakeholders are aligned, and the budget is approved. Yet six months in, progress feels sluggish. The cloud migration is behind schedule due to performance issues no one anticipated. Application modernization stalled when the team discovered integration complexities that weren’t apparent during planning.

Grafana Tempo 2.8 is officially here, delivering new TraceQL features, performance improvements, and bug fixes, as well as some breaking changes. Watch the video below to learn more about the TraceQL features, or continue reading to get a quick overview of these and other updates. If you’re looking for something more in-depth for all of the changes that happened in this release, head over to the Grafana Tempo 2.8 release notes or the changelog.

It’s one thing to debug your game during development, but once your game is in production, visibility into errors and failures in real gameplay is harder to achieve. And when something does go wrong, players are more likely to ragequit than submit a bug ticket.

Data isn’t just a record of what happened—it shapes what happens next. Across industries, connected devices continuously stream time-stamped data that reflects the current state of machines, environments, and systems. This steady flow gives businesses a live view of their operations and the opportunity to catch issues early, adjust quickly, and operate more efficiently.

Collecting logs in Kubernetes often starts as a simple goal, and quickly turns into a game of “where did that log line go?” Between sidecars, DaemonSets, and countless config options, it’s easy to get lost. Fluent Bit helps cut through the noise. It's fast, lightweight, and plays well with Kubernetes. And when you deploy it using Helm charts? The setup becomes way more manageable. This guide covers the how and the why, without overcomplicating the what.

In recent months, my conversations with fellow technology leaders have consistently revolved around two key themes: how we leverage AI to drive innovation and efficiency, and how we mitigate the inherent risks associated with AI. However, I’ve noticed a concerning gap – while enterprises are busy strategizing the adoption of AI to enhance productivity, reduce costs, and outpace competitors, very few are addressing how AI is being actively used today by their own teams.

Nextjs is a production-ready React framework for building single-page web applications. It enables you to build fast and user-friendly static websites, as well as web applications using Reactjs. Using OpenTelemetry Nextjs libraries, you can set up end-to-end tracing for your Nextjs applications. Nextjs has its own monitoring feature, but it is only limited to measuring the metrics like core web vitals and real-time analytics of the application.

As part of a customer project, we developed a custom Confluence Management Pack for Microsoft System Center Operations Manager (SCOM). This tailored solution enables IT operations teams to monitor key performance and health metrics of Confluence environments, ensuring knowledge-sharing platforms remain available and performant.