Operations | Monitoring | ITSM | DevOps | Cloud

DORA's data shows that as AI adoption goes up, individual effectiveness rises, and so does software delivery instability: more rollbacks and more unplanned rework. Nathen Harvey of Google's DORA team explains why AI acts as an amplifier of whatever system you already have. He walks through the seven capabilities that separate teams getting real gains from teams drowning in downstream chaos. He also argues that the risks stopping you from shipping AI-built work should become your platform roadmap.

AI can write 1,100 lines of code for a loading spinner in five minutes. Your change board still meets once a week. Karthik Jayaraman, VP of Information Technology at Fiserv, explains what happens when code generation speeds up and everything downstream stays the same. He covers why "human in the loop" doesn't scale, why handing all review to AI backfires, and why an agent told not to touch production needs a boundary it can't cross, not just an instruction.

Turns out telling coding agents what to do over and over again doesn't actually make them better at fixing CI failures.

Onboarding a new client shouldn't mean rebuilding the same dashboards by hand. Live demos show how our MCP server (in preview) hands that work to AI, built for MSPs, but relevant to any team automating dashboards and reporting.

How close are IT teams to total observability? See how SquaredUp uses AI to build plugins and dashboards, spot anomalies, connect data across tools, and set up monitoring from a single prompt.

In this Pyroscope community call, we look at what eBPF is, where it came from, and how the OpenTelemetry eBPF profiler uses it to profile supported workloads without application code changes.

Is an app holding your camera hostage? NinjaOne Remote connects fast, gives you full visibility, and lets you fix it securely. Nothing squats on your computer rent-free. Big shout-out to Marcus Hinojoz (TheITGamer on Instagram) for teaming up with us on this one. Learn more at ninjaone.com.

This video walks through what it looks like to treat Sentry's Seer agent the way you already treat a chatbot, asking it plain language questions about your own production application. From Slack or inside your Sentry account, Seer Agent can answer questions with real context: the affected spans, the recent release, the likely cause. Seer doesn't stop at answering questions. Ask it to act on what it just told you and it completes that work inside Sentry, serving as an assistant to your projects, team workflows, and your future self.

There are times when you have a panel which does not show any data because there is none and it might be a good idea to hide it until it start showing. Learn how to do this in Grafana.

Problem-driven development and handling ambiguity help determine when to use code automation vs. AI.