Operations | Monitoring | ITSM | DevOps | Cloud

Observability has evolved dramatically in the past decade. The industry has moved from basic uptime checks to full-stack observability (FSO), including metrics, logs, traces, and real user monitoring. Observability tools like ManageEngine FSO can detect anomalies in little time. And yet, outages still last longer than they should. Observability has matured. Response hasn’t. Most IT teams today have the tools to know when something breaks. But knowing is not the same as resolving.

Most founders have a build problem. Very few have solved the distribution problem. That gap is where startups die. When someone comes to me with a startup idea (and this happens more than you’d think), I always ask the same question first.

Dozens of SaaS services you depend on, starting from Google Workspace and Slack to Shopify, may experience downtime, partial outages, or degraded performance. And most have their own status pages, APIs, or RSS feeds. Juggling all these sources is exhausting, and many teams suffer from alert fatigue, missed early warnings, and fragmented visibility.

Endpoint visibility has always been foundational to IT and security. You can’t secure, patch or support what you can’t see. But as environments have become more distributed and complex, what visibility means has evolved. It’s no longer enough to know that a device exists — IT teams and organizations as a whole need to understand its health, its risk posture and its impact on both security and user experience.

Honeycomb was excited to attend KubeCon + CloudNativeCon Europe, where one theme stood out across sessions: as AI reshapes how software is built and run, teams are being pushed to rethink how they understand their systems. Without strong observability and feedback loops, AI can accelerate confusion, misalignment, and operational risk.

Let’s suppose you’re building an even smarter fishtank. You’re adding temperature and salinity sensors, logging timestamped readings to flash. The struct is your binary record format – every field at a fixed byte offset, so you can read it back on any system that knows the layout. You use fixed-width types from stdint.h and pack(1) to strip out compiler-inserted padding. This is the advice I had always received and given, and it’s correct – as far as it goes.

To safeguard IT operations during regional disruptions.

Following the incredible success of Ubuntu Summit 25.10, we are thrilled to announce that Ubuntu Summit 26.04 is officially on the horizon. If you are new to the Ubuntu community, every new release of Ubuntu comes with an Ubuntu Summit – an event that takes place twice a year and serves as a showcase of the absolute best in open source innovation from around the world. Our hub in London hosts the talks, which are then streamed live, across the world.

Modern network operations generate an extraordinary amount of telemetry. Metrics, logs, events, topology data, cloud signals, and service context all contribute to a richer picture of system behavior. As environments expand across cloud, data center, edge, and SaaS, the opportunity for operations teams is clear: when that telemetry is unified and understood in context, it becomes a powerful source of resilience, efficiency, and business insight.