Operations | Monitoring | ITSM | DevOps | Cloud

Grant is joined by SQL Server veteran and long-time Microsoft MVP, Hugo Kornelis, to talk all things SQL Server query tuning, execution plans, and more. You’ll hear about some of the problems Hugo’s encountered during his consultancy career, what SQL Server has in common with a highway, and Hugo’s thoughts on AI – plus much more.

Asking developers to take extra steps to pull securely is a policy that won't hold. The only approach that scales is making the private registry the default – a buffer between the developer and public registries that applies policy automatically at the global level. No extra steps, no security theater, no cognitive overhead at the point of pull. Automation and global policy configuration are what turn good intentions into a default secure posture.

Learn how to user agents to turn Slack alerts into autonomous RCA sessions, build incident memory, and help on-call engineers move from signal to fix faster. ​Join us for the live stream demo of Incident Response. We will break things on stream and let agents fix them. We will watch Droid run a real incident from alert to fix, and we show exactly what it read to get there.

See how the new Dynamic MCP Server in Resolve Actions Pro 8.1 lets AI assistants like Claude discover and execute approved Resolve runbooks through the Model Context Protocol (MCP). Watch enterprise automation happen in real time with secure, auditable execution.

The "Patch Apocalypse" is here. With the rise of advanced AI models like Mythos and Project Glasswing, the window for exploiting software vulnerabilities has shrunk from weeks to just days. Are your IT operations and security protocols ready for this new normal?

Code review has always been a time sink. AI just makes the dysfunction undeniable. Luca Rossi, founder of Refactoring.fm and builder of the open source tool Tolaria, has been running one of engineering's most-read newsletters for five years, with over 170,000 subscribers. He's also been doing what a lot of engineering leaders talk about but rarely do: building a real product with AI agents to pressure-test what's actually possible today.