Operations | Monitoring | ITSM | DevOps | Cloud

When a critical system goes down at 3 AM, the difference between a quick resolution and hours of costly downtime often comes down to one role: the incident commander. This person serves as the central coordinator during IT incidents, making crucial decisions that can save thousands of dollars per minute.

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.

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.

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.

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.

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.

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?

If you’ve ever found yourself staring at a cloud bill that could buy a small island or at least a very nice car, you're not alone. Believe me, at Cribl, we've had our share of those "molotov cocktail" bills that make our CFO, Zach, look like he's about to spontaneously combust. And yeah, a few F-bombs might have dropped from various senior leaders (myself included, I won't lie).

Google Workspace went down again in July 2025—but if you had asked AI tools like Google’s own AI Overviews, ChatGPT, or Claude, you would have been told everything was fine. Every one of these tools incorrectly claimed that services were up and running while users across the globe were unable to connect, send messages, or even log in.