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.

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).

When AI could only answer questions, a bad prompt just meant a bad answer. But now AI agents read your documents, browse websites, and actually do things on your behalf. So when someone sneaks a malicious instruction into a file or a webpage, the agent doesn't just say something wrong. It does something wrong!

Watch the full episode: MCP vs CLI: Does it even make a difference? Live Laugh Logs ep. 3.

Wolt operates in 30+ countries. Every order, every restaurant, every courier runs on the same infrastructure. When it breaks, it doesn't slow things down, it stops everything. Wolt's VP of Engineering shares why Apache Kafka sits at the heart of their platform, what seven years of partnership with Aiven looks like in practice, and how they're building the data foundation needed to get AI working at scale.

Let’s be honest: traditional automation breaks the second it hits a scanned PDF, a messy email thread, or an architectural drawing. Rules-based RPA simply lacks the cognition required to decode unstructured data. In this episode of, Project Manager Swetha K J breaks down exactly how we conquered this massive roadblock on our automation journey. By embedding advanced AI models directly into automation workflows, we’ve built a context-aware architecture that transitions systems from static execution to dynamic intelligence.