Operations | Monitoring | ITSM | DevOps | Cloud

Have you ever been in the middle of an important video call, only for it to glitch or freeze out of nowhere? Or did an application suddenly slow down right when you needed it most? These frustrating moments can often be caused by something hidden in the background: packet bursts. But what exactly are packet bursts, and why do these sudden surges in data traffic catch you off guard when your network seems steady? Are they just random spikes in the data flow, or is there something deeper causing them?

The gap between security operations and IT operations poses significant risk. It’s increasingly clear that DevOps leaders, IT managers, and enterprise teams face an uphill battle to manage growing threat complexity, endless patches, and compliance requirements while operating in silos. Bridging this gap is essential to effectively manage risks and enhance operational efficiency.

If, like me, you’re continuously striving to keep pace with the ever-evolving world of artificial intelligence, you’re probably hearing a lot about how Ambient AI is poised to dominate discussions and developments throughout the second half of 2025. Ambient AI refers to artificial intelligence systems that operate unobtrusively in the background of our daily environments, constantly sensing, analyzing, and responding to various inputs without explicit human interaction.

Imagine you’re working on a hospital floor when suddenly a patient’s condition starts to deteriorate. What happens next can mean the difference between life and death. That’s where a Rapid Response Team (RRT) steps in: a specially trained group of healthcare professionals who respond quickly to patients showing early signs of crisis to prevent emergencies like cardiac arrest or respiratory failure. But how common are these teams? What do they really do day-to-day?

Librato (a SolarWinds product) is being sunsetted summer of 2025, and that directly affects Heroku teams who’ve relied on the Librato add-on for “good enough” visibility into dynos, routers, and Postgres. If you’re in that group, you’ll need a replacement monitoring add-on that keeps you covered on Heroku and lets you grow beyond it without re-architecting how you ship metrics.

Good logging isn’t optional when building Java applications—it’s critical. Logs are often the first place we turn to when something breaks and are essential for performance tuning, security audits, and long-term maintainability. Two names come up in the Java logging conversation: Simple Logging Facade for Java (SLF4J) and Log for Java (Log4j). They sound similar and often work together, but they serve distinct roles.

Your Jaeger setup is running. Traces are coming in, and the UI is helping you spot slow services or debug broken flows. But just like any part of your observability stack, Jaeger needs some basic monitoring to stay reliable. If the collector starts queueing spans or the agent runs out of buffer, it can lead to dropped traces, sometimes without any obvious sign in the UI. This blog focuses on the operational side of Jaeger.

‍ On August 2, 2025, a key part of the EU AI Act comes into force. It has serious implications for how you manage incidents related to artificial intelligence. ‍ While the full regulation will not apply until 2026, new obligations for providers of general-purpose AI (GPAI) models begin this summer. If you are building or deploying AI-powered services in Europe, the clock is ticking.

In the first two parts of this series, we explored why modern network operations demand intelligent automation and how AI agents can reason, act, and collaborate to solve complex problems. We examined the frameworks – such as ReACT, LangGraph, and Pydantic – that power these agents, and how the Model Context Protocol (MCP) facilitates seamless integration with tools and services. But theory alone doesn’t improve network uptime or reduce manual toil.

Organizations migrating from Opsgenie and other legacy incident management platforms are discovering that basic connectivity monitoring isn’t enough for modern operations. While Opsgenie Heartbeats and similar traditional heartbeat features offer simple binary status checks of system availability, PagerDuty’s AIOps-powered approach transforms system health monitoring from reactive alerting into intelligent, automated operational intelligence.