Operations | Monitoring | ITSM | DevOps | Cloud

MCP vs CLI: which one should your AI agent actually use? We get into it with Grafana's cloud and OSS MCP servers and gcx.

Context Offloading is a pipeline solution for managing Observability with AI Agents. If you are building AI Agents that work with real data, the context window can very easily get filled with bloated context that the Agent does not really need. Sven demonstrates "Context Offloading", a solution that stores the JSON result and sends only the summary of the JSON blob, making the LLM loop performance much quicker and keeping your context window small.

Grafana AI Observability is our new database and platform for observing AI Agents. Over the past year at Grafana Labs, we built Agents and we needed a way to understand how they are performing, what are the costs associated with them, what's the error rate or time to the first token as well as how they are behaving. Grafana Staff Engineer, Ivana Hučková provides a deep dive demo on how Grafana AI Observability connects our experience building Agents with our experience building observability systems.

Learn how to create and customize dashboards on Uptime.com, including setting up the General and Display Settings tabs, configuring check cards, filtering by state, setting sort orders, displaying metrics, managing alerts, and creating multiple dashboards.

Say hello to AI Chat Detection! And learn how to receive alerts about potentially risky conversations in your child's ChatGPT, Gemini, and Character.AI.

AI coding agents write code faster than your pipeline can catch mistakes. What if the agent could validate against CI before you ever push? In this 5-minute demo, we set up CircleCI's Chunk CLI and run a microbuild using Chunk sidecars, secure Linux microVMs that spin up in ~1 second in your CircleCI account, mirror your working directory (no git push required), and give your agent CI-grade feedback while it's still in context.

If 90% of code is now AI-generated, what happens to the engineers who never had to write it themselves? The ability to review code well, to catch what the LLM missed, depends on mental models that only come from practice. That tension sits at the center of this conversation.

Your schema changed. Did your masking rules keep up? Here’s how Flyway and Test Data Manager can catch gaps and prevent PII exposure in dev and test. Tony and Tonie discuss how Flyway and Redgate Test Data Manager can work together in a CI pipeline to detect schema changes that introduce unmasked sensitive columns, helping teams keep production-derived test data protected as the database evolves.

Your AI is only as good as the data it sits on — and fragmented IT data isn't just inefficient; it's dangerous. Watch Ivanti's Sterling Parker, SVP of Global Solutions and Services at Ivanti, explain why a unified IT platform and a clean system of record are the true foundation of secure, scalable AI.

AI governance isn't optional — it's the difference between scaling AI confidently and exposing your organization to serious risk. Watch Brooke Johnson, Ivanti's Chief Legal Counsel, SVP HR and Security, break down why AI policy alone isn't enough and what it actually takes to close the governance gap.