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By Jonas Best
Jonas Best & Patrick Polster Kafka migrations are one of the riskiest infrastructure projects a platform team can take on. Miss a dependency and a downstream app starts reprocessing events it already handled leading to breaking SLAs and eroding trust with application teams. Migrate without visibility and you risk a major production issue. The instinct is to reach for a replication tool and call it done. But replication is only one piece of the puzzle.
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By Andrew Stevenson
At Lenses, our goal has always been to help organizations get the most out of their streaming data. We started with visibility into the Apache Kafka, moving up to the part that drives value, the application layer and now the Agentic layer. Lenses 6 moved us into a multi-Kafka world, as increasing, our clients aren’t just running on one type of Kafka anymore, and as sovereign cloud becomes increasingly topical (no pun intended) this is only increasing.
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By Tun Shwe
In 2025, Model Context Protocol (MCP) captured the imagination of the AI engineering community. 2026 will be the year that everyone realises their prototypes need to run in production.
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By Guillaume Aymé
What’s remarkable is how long Confluent competed at the highest level. Creating a category and type of application is hard; transitioning to cloud and surviving against hyper scalers is even harder. That alone is a huge achievement. Some see this as a pressured exit. But another way to look at it is as a strategic purchase by IBM to strengthen its position in enterprise data movement and integration.
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By Andrew Stevenson
When we talk about JSON schema in the world of Kafka and streaming, you may assume the schema for the events/messages. But how many times have you fumbled in the configuration about trying to get an application deployed? Schemas that describe how to configure and deploy Applications or applications-as-code, are also important, allowing us to automate application landscapes. Especially as we will soon be a wash with catalogs for AI Agents, MCP servers etc.
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By Ivan Majnarić
Picture this: It's 3 AM. You’re on-duty in case there is an outage. A team in the other part of the world merged PR and released a new version of K2K Replicator and it crashed. Consumer group lag is spiking to the universe. You’re paged & woken up, went to your laptop, the team already reverted PR, things are stabilising, but what really happened, you have to investigate now as postmortem has to be done.
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By Andrew Stevenson
If you’ve been running Kafka for a while, with any luck you have quite a few engineering teams onboarded, potentially with hundreds or even thousands of applications. Hopefully the Lenses.io Developer Experience platform helped in this adoption. But finding the right balance between governance and openness can be tricky.
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By Stefan Bocutiu
Here at Lenses we’re as always laser-focused on making engineering streaming apps and managing Kafka, not just less stressful, but delightful. 6.1 is another big step forward. It starts with the Lenses MCP Server. It connects your AI assistant such as Cursor and Claude, bringing the knowledge of the internet with the context of your Kafka environment. It has the power to transform the work of engineers building and managing streaming apps.
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By Tun Shwe
If 2024 was the year enterprises adopted Generative AI, 2025 is the year Agentic AI became a reality. In the last six months, the conversations I’m having with engineering leaders have quickly shifted from simple chatbots to AI-enabled IDEs, copilots and autonomous systems that take action. This has to a large part been helped thanks to MCP. To date there have been 10,000+ MCP integrations built by the community, so to say it is a success is an understatement.
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By Andrew Stevenson
Imagine an airline system monitoring traffic around an airport. If it detects a major delay, countless systems may need to react instantly: Ground operations to adjust flows. Some of these systems will still connect via API, traditional MQ or iPaaS technologies, but the data’s volume and urgency and the ease of decoupling apps make architecting with Kafka the better fit. The natural question is: should all these applications & systems connect to the same Kafka cluster?
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By LensesIO
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.
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By LensesIO
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?
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By LensesIO
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.
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By LensesIO
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.
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By LensesIO
Migrating Kafka clusters doesn't have to be a complex or high-risk operation. In this technical walkthrough, we demonstrate how Lenses K2K managed through Lenses 6 simplifies the migration of mission-critical banking applications from Strimzi to AWS Express Brokers with minimal downtime and zero data loss.
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By LensesIO
In this episode, Drew Oetzel sits down with Ryan Anguiano, Staff Architect at @WhatIfMediaGroup to discuss their massive migration of from legacy EC2 instances to using the @Strimzi operator. Ryan shares deep technical insights into how they optimized their data streaming architecture, including their use of EKS, EBS storage striping, and why the 12-Factor App methodology was the key to migrating over 100 services in just a few months.
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By LensesIO
AI agents are only as good as the data they can access. In this video, we explore the Model Context Protocol (MCP) and how it creates a bridge between AI models and Apache Kafka. Learn how MCP allows AI agents to securely produce, consume, and manage Kafka topics in real-time—transforming your event streams into actionable context for LLMs.
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By Lenses
DataOps is the art of progressing from data to value in seconds. For us, its all about making data operations as easy and fast as using the email.
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By Lenses
Apache Kafka is a popular and powerful component of modern data platforms. But it's complicated. Complicated to run, complex to manage and crucially - it's near impossible to drive Kafka adoption from the command line across your organization. So here's your how-to for seeing it through to production (... and possibly fame and fortune). We cover key principles for Kafka observability and monitoring.
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By Lenses
Lenses, a DataOps platform, accelerates time to value, opening up data streams to a wide audience. Lenses enables rapid construction and deployment of data pipelines at scale, for enterprises, with governance and security.
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By Lenses
Lenses, a DataOps platform, accelerates time to value, opening up data streams to a wide audience. Lenses enables rapid construction and deployment of data pipelines at scale, for enterprises, with governance and security.
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Lenses ® is a DataOps platform that provides cutting edge visibility into data streams, integrations, processing, operations and enables ethical and secure data usage for the modern data-driven enterprise.
Accelerate time to value, open up data in motion to a wide audience, enable rapid construction and deployment of data pipelines at scale, for enterprises, with governance and security.
Why Lenses?
- Confidence in production: Everyone’s scared of the dark. Lenses gives you visibility into your streams and data platform that you’ve never had. That means you don’t need to worry running in production.
- Keeping things simple: Life’s hard enough without having to learn new languages and manage code deployments. Build data flows in minutes with just SQL. Reduce the skills needed to develop, package and deploy applications.
- Being more productive: Build, debug and deploy new flows in minutes not days/weeks. In fact, many of our customers build and deploy apps to production 95% faster.
25,000+ Developers Trust Lenses for data operations over Kafka.