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Get Kafka-Nated S2E4: Debugging the Kafka-Iceberg Connector

In this episode of Get Kafka-Nated, host Hugh is joined by Anatolii Popov, Senior Software Engineer at Aiven, to dive into one of the most talked-about integrations in the modern data stack: Kafka to Apache Iceberg. Anatolii was accepted to speak at Iceberg Summit 2026 on debugging the Kafka Connect Iceberg Connector, and in this session we’ll cover the talk he would have given, including common failure modes, debugging locally, catalog complexities, and where the integration is heading next.

The Best SKILL.md Is the One You Never Update - Meet Checkly's CLI

Most agent skills are static — frozen documentation snapshots that go stale the moment APIs change or flags get deprecated. Checkly does it differently. Our SKILL.md is just 100 lines of CLI pointers. No baked-in docs. Your coding agent learns what it needs, when it needs it, straight from the Checkly CLI.

Tech Talk | AI Agents in O11y Cloud

Transform reactive incident response with Splunk’s troubleshooting agents, designed to drastically reduce mean time to identify and resolve issues. This session demonstrates how a multi-agent approach empowers teams of all skill levels to pinpoint root causes, prioritize issues by business impact, and prevent future outages. Tech Talk sessions offer insightful and valuable deep-dives for any technical practitioner.

Unlocking Security Potential for AI: Introducing the Harness WAAP MCP Server | Harness Blog

Security teams face overwhelming amounts of data and complex interfaces, making it hard to access critical insights. AI tools promise solutions, but integration remains difficult as time ticks away and leadership wants the latest data to inform risk decisions. Most security platforms lack seamless integration, slowing access to important data and hindering AI-powered workflows.

The Runbook Problem: How AURA Documents What Teams Don't Have Time to Write

Runbooks are rarely missing because teams don't value them. They're usually missing because incident response, follow-up, and platform work compete for the same limited time. By the time an issue is resolved, the knowledge is fresh, but the window to document it is already closing. That gap creates familiar failure modes: over-reliance on senior engineers, slower handoffs, and less confidence for whoever is on call next.

From One Month to One Day: How CloudZero Builds Cloud Cost Connectors at the Speed of AI Adoption

Not long ago, adding a new cost connector to CloudZero was a serious undertaking. We’d task multiple engineers, build in extended review cycles, run a private preview period. But a single connector could take up to two months from kickoff to customer hands. For the major cloud providers, that timeline was acceptable. The size of the investment matched the scale of the integration. But the tools landscape has changed. Our customers’ teams don’t just run on AWS and Azure.