Operations | Monitoring | ITSM | DevOps | Cloud

The Scout MCP server connects your AI assistant directly to your Scout Monitoring data. Instead of switching between your editor, Scout, and a chat window, your assistant can pull traces, errors, N+1 insights, and endpoint metrics on its own and use that context to suggest or make fixes right in your codebase. This covers how to connect it, what to ask it, how other teams are using it, and what we shipped recently.

The impact vision for PagerDuty.org is to enable mission-driven teams to build a resilient world and a sustainable future for all. As a leader in modern, AI-first operations, we know that operational excellence supercharges social impact. As artificial intelligence rapidly reshapes the social sector, this commitment to resilience and efficiency has never been more vital.

The shift to autonomous and AI-assisted security operations is well underway. But there is a quiet infrastructure decision that will determine whether your AI agents are sharp or sluggish: how your security data is structured before it ever reaches them.

The race to better AI-assisted observability has been a race for bigger and better models. But intelligence was never the real bottleneck. Structure and context were.

For a decade, one idea has guided everything we’ve built at Tigera: How do you secure a dynamic system with a lot of moving parts that is changing rapidly, with a programmatic approach? Calico has applied that idea for Global 2000 companies running the largest Kubernetes platforms in the world, securing tens of millions of mission-critical transactions every day. Today I’m excited to announce the next chapter of that work: Lynx, a unified control plane for Kubernetes-native AI agents.