Systems | Development | Analytics | API | Testing

New research with 150 Kafka practitioners reveals they have a love-and-hate relationship with the replication tools. Most use MirrorMaker2 until it lacks enterprise compliance and complexity pinches. Confluent Cluster Linking is powerful, but organisations hate being locked in. 70% of respondents would make the switch to a different tool if they were assured the migration was easy. Join Guillaume Aymé, the CEO of Lenses.io, who will be discussing the state of Kafka replication with the author of the research, Dinesh Chandrasekhar, the Founder of Stratola Research.

The standard approach for Kafka in enterprise environments is to lock it down and have engineers file tickets. Platform teams do that because traditional engineering tools (CLIs, UIs and native ACLs) have no enterprise governance, so you cannot grant access you can scope, revoke or prove later. That’s the Kafka ticket desk: the week is access requests instead of platform work, engineers wait days to ship and Kafka adoption scales only as fast as the ticket queue moves.

Most Kafka war rooms don't start at 2am in production. They start weeks earlier, when an engineer couldn’t explore a topic, see partition distribution, a quota or a config and shipped hoping for the best. That's the Platform Engineering waiting room: developers building apps waiting in a queue of tickets, with no self-service visibility into Kafka. That release triggers a P1 later.

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.

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 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.

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.