Operations | Monitoring | ITSM | DevOps | Cloud

AI incident assistant from BigPanda gives L2, L3, and SRE teams instant answers to resolve incidents faster without manual triage or tool-switching. IT teams lose critical minutes during incidents because context is scattered across Slack threads, bridge calls, monitoring tools, and historical tickets. The BigPanda AI Incident Assistant fixes that by surfacing relevant knowledge exactly when and where responders need it. It gives responders evidence-based resolution paths drawn from historical incidents and live system data, without leaving your workflows.

Agents are pretty good at fixing your apps. We can make them even better. ​In this workshop we’re going to show you how to give your agents superpowers using Seer, the Sentry MCP server, and CLI tool. Join to learn how to: ​- Teach agents how to best implement and work with Sentry through agent skills and the CLI tool. ​- Set up Seer’s agent handoff feature for Claude, Cursor, or GitHub Copilot and have agents start automatically generating pull requests for fixes.

Most enterprises have observability tools. What they often lack is a shared view between application and infrastructure teams. When application performance degrades, finding the root cause can be slow because the data lives in separate silos. Virtana brings application observability and infrastructure intelligence together in a single platform, helping teams identify issues faster, collaborate more effectively, and shift from reactive troubleshooting to proactive operations.

Highly classified environment. Strict compliance requirements. Data that can't leave the network. But still a real need for the competitive advantage AI delivers. Civo Director of Enterprise Cloud Solutions John Dietz addresses exactly that challenge and how Konstruct makes it possible to run Kubernetes, deploy your own models, and point Claude Code at your own internal private servers instead of public APIs.

This video demonstrates how to use the ProxyMock web tool to record API traffic from a remote Kubernetes cluster and automatically scan it for hidden PII to ensure the data is safe for developers to use.

We demonstrate how to stream realistic test data directly from a production environment to developers and AI models without exposing any personally identifiable information (PII).