Systems | Development | Analytics | API | Testing

Enterprise Kafka DR Without Vendor Lock-In.

Join Tun Shwe and Jeremy Frenay as they stream live from the floor of the Databricks Data + AI Summit! They’ll break down the biggest announcements, key takeaways, and cutting-edge trends shaping the intersection of AI and data streaming. Register to get an insider look at the future of data AI streaming.

Most AI agents are generalists that struggle with the nuances of streaming data and Kafka infrastructure, often leading you down a rabbit hole with many tokens spent. In this session, live from Current London, we’ll show you how to close the context gap with Skills for Kafka: structured files that are playbooks and level-ups for agents to handle complex multi-step tasks like reviewing schema changes, critiquing DLQ policies and auditing topics for best practice. We will walk through how these skills work, demonstrate the different ways to use them (including with MCP servers) in Cursor and Claude.

Discover the powerful new IDE-like Studio in Lenses 6.2. Learn how to manage your Kafka clusters, discover topics across multiple environments, and perform side-by-side comparisons of dev and staging data. We also dive into the new ways to interact with streaming data, including the CLI, VS Code plugin, and the new MCP server for AI agents and chatbots. Whether you're a developer troubleshooting schema mismatches or a data engineer managing complex Kafka estates, the new Lenses Studio provides the tools you need to stay in context and work efficiently.

Is your AI agent one misconfigured server away from a production data leak? In this deep dive, Jeremy from Lenses explores the critical security architecture of the Model Context Protocol (MCP) and how it’s evolving to protect the future of Agentic Engineering.

Discover how the new Lenses 6.2 VS Code plugin revolutionizes the way developers interact with Kafka and streaming data infrastructure. In this deep-dive tutorial, we explore how to manage your entire streaming ecosystem directly from your IDE, eliminating context switching and boosting productivity.

Every engineering team is onboarding AI agents. Most are doing it without a governance model - static API keys, no audit trail, no way to revoke access if something goes wrong. Join us on April 15th as we go live on the topic everyone is talking about but few are solving: how to govern AI agent access to streaming data.

AI agents need access to your systems. But are you sure they're accessing them securely? In this video, Tun @DataSurfer breaks down the way most teams give AI agents access today: static API keys, shared credentials, no audit trail. It's a disaster waiting to happen, but what exactly can teams do about it?

Agents need real access to do real work - but when MCP connects your AI to production systems like Kafka, who controls what it can touch? OAuth 2.1 is emerging as the answer.

2025 was vibe coding. 2026 is Agentic Engineering - and the security rules haven't caught up. AI agents now have direct access to your databases, your APIs, your Kafka clusters. The protocol giving them that access is MCP. And most teams have no idea how exposed they are. We are fixing this problem with OAuth 2.1.