StreamNative

How much is "managing Kafka" actually costing your team? 💸 Between manual rebalancing, hardware provisioning, and the constant fear of a cluster outage, the "free" open-source version of Kafka often comes with a massive hidden price tag in engineering hours. On May 28, we’re showing you how to reclaim that time.💡 StreamNative (Kundan Vyas) and Lenses.io (Patrick Polster) are teaming up to demonstrate a proven, low-risk path to move your workloads to a fully managed, cloud-native Kafka service. What we’ll dive into: ✨ Proven Migration Patterns: Why Lenses K2K is the "easy button" for moving data between clusters. ✨ Architecture Matters: How StreamNative Ursa separates compute and storage to make scaling instant and painless. ✨ Business Continuity: A step-by-step look at performing cutovers without impacting your downstream consumers. 📅 Register here: https://hubs.ly/Q04gDLmp0 #Kafka #DataEngineering #CloudNative

🔔 We’re excited to announce the launch of Maintenance Notifications for StreamNative Cloud! Ensuring the stability and security of your Pulsar clusters requires regular maintenance, but we know that visibility into these changes is critical for your operations. Our new feature gives you a clear, centralized way to track and manage planned updates directly from the StreamNative Cloud Console. 🌟 What’s new: 🔹 Maintenance Dashboard: Access all planned and ongoing notices under Organization Settings > Observability. 🔹 Detailed Execution Info: See exactly what is changing, which resources are affected, and the scheduled windows. 🔹Actionable Controls: Users on Enterprise or Production support plans can now Approve, Reject, or Reschedule maintenance events directly within the console. 🔹 End-to-End Email Alerts: Stay informed with updates sent before, during, and after any maintenance execution. 
 💡 Pro-Tip: Make sure your "Technical Contact" in the Organization Profile is up to date to ensure your team receives these critical email alerts. Ready to take control of your maintenance lifecycle? Log in to your console and explore the new dashboard today. Learn more in the first comment below.👇

Huge thanks to our co-hosts at RisingWave and Aiven for an incredible event in San Francisco! We were thrilled to see such a high-energy turnout from the streaming and AI communities. It was a privilege to have our CEO, Sijie Guo, join Yingjun Wu, Filip Yonov, and Dmitry Kan to discuss the "Future of Kafka + AI." The session made it clear: the intersection of real-time data and agentic workflows is the next frontier for intelligent systems. Looking forward to the next one! 🚀

StreamNative Ursa is Expanding: Kafka Queues, Azure Support, and Private Cloud 🚀 Since launching our StreamNative Kafka Service (UFK) on Lakestream, we’ve been working to redefine what a cloud-native Kafka experience looks like. Today, we’re announcing several major enhancements that bring more flexibility, power, and cost efficiency to your streaming infrastructure. 💥 🌟 What’s new: 🔹 Ursa for Private Cloud (Private Review): We are bringing our lakehouse-native storage engine to self-managed and highly regulated environments. Separate compute and storage, and leverage zero-ETL integration to turn Pulsar topics into queryable Iceberg or Delta Lake tables natively. 🔹 Kafka Service on Microsoft Azure: Deployment is now available across all three major clouds (AWS, GCP, and Azure) for both Dedicated and BYOC clusters. 🔹 Kafka Queues Support: Combine event streaming and queue-based processing on a single platform. Scale consumers beyond partition counts and simplify AI agent task orchestration using the new Share Groups model. 🔹 Flexible Storage Pricing: New pricing for Dedicated Cost-Optimized clusters, designed to slash infrastructure costs for high-volume analytics and long-term retention workloads. 🔗 Read the full announcement: https://hubs.ly/Q04gpt6l0

Final Call: Streaming into Unity Catalog Managed Tables 🧊 Join us tomorrow, Thursday, May 14, at 9:00 AM PT, as we team up with Databricks to solve the governance gap in real-time data pipelines. 💡 What you'll learn: 🔹 Direct writes into managed Delta tables via Unity Catalog Commits. 🔹 Simplified pipelines that write Kafka and Pulsar data directly to your lakehouse. 🔹 Best practices for building unified, AI-ready architectures. 🎙️ Speakers: Kundan Vyas, StreamNative Benjamin Mathew, Databricks 👉 Save your spot: https://hubs.ly/Q04gpfKy0 #DataStreaming #Databricks #UnityCatalog #Lakehouse #Kafka #Pulsar #DataGovernance

We are excited to announce Organization-Level Remote MCP Server support in StreamNative Cloud.🚀 Previously scoped to individual clusters, MCP access can now be configured at the organization level. This isn't just a feature update—it is a foundational shift in how enterprises build, secure, and scale real-time AI applications.💥 Why this is a game-changer for AI developers: ✅ Unified Access: Agents can now interact with data across multiple clusters through a single endpoint—no more managing fragmented interfaces. ✅ Enterprise Governance: Standardize access control with organization-scoped credentials and API keys (Auth v2) that align with your security model. ✅ Seamless Scalability: Developers get a consistent interface for building and deploying agents, regardless of how many clusters are running in the background. ✅ Foundation for Agentic Workspaces: This is a key step toward our vision of a unified environment where agents, functions, and AI services operate within a governed organizational boundary. This is a foundational step toward Agentic Workspaces—where real-time data, functions, and AI agents operate within a single, secure organizational boundary. 🔗 Read the full announcement here: https://hubs.ly/Q04gcT_X0

If you’re a platform engineer or infrastructure lead, you know the drill: every Kafka vendor has a calculator that "confidently" shows you a low number by using straw-man competitors and hidden assumptions. We decided to do something different. We’ve released a comprehensive Kafka on #AWS TCO Report that strips away the sales fluff. We used published rate cards, applied every cost-saving lever available (like KIP-392 and VPC peering), and ran the same workload assumptions across every major player. The massive takeaway? Pick the wrong latency tier and you could overpay by 4-10x per byte. What’s inside the report: 🔹Latency-Optimized Rankings: A side-by-side cost comparison of leading streaming platforms for sub-10ms workloads. 🔹Cost-Optimized (Analytics) Rankings: How leaderless agents and S3 storage backends are redefining the lakehouse cost structure. 🔹The "Pluggable Storage" Advantage: Why running a single cluster with per-topic backend routing can be 3.5x cheaper than a multi-vendor sprawl. 🔹The "AWS Surface": A breakdown of how much you can actually save by applying cloud-side discounts directly to your infrastructure bill. 🇬🇧 Attending #Current London? Stop by the #StreamNative booth to grab a physical copy of our Kafka on AWS Field Guide. Our team will be there to whiteboard your architecture and help you find your actual cost floor. Not in London? We’ve put the link to the full report in the first comment below so you can re-run these rankings against your own real-world assumptions. 👇 #Current26 #ApacheKafka #DataStreaming #CloudInfrastructure #AWS #TCO #UFK

Heading to Budapest virtually next week 🇭🇺 I'll be at the Budapest Data + AI Forum (May 18–20) presenting "Cataloging Streaming Data in the Iceberg Ecosystem." Here's the thing nobody warns you about when you start landing Kafka topics in Iceberg: the table format is the easy part. The hard part is the catalog — how streaming data actually shows up, gets discovered, and stays consistent as it lands. Get this layer wrong and your lakehouse turns into a swamp of orphaned tables and confused analysts. Iceberg has done a remarkable job standardizing the table layer of the lakehouse. But streaming data introduces a set of problems the catalog spec wasn't originally designed for — high-frequency commits, schema evolution at write time, and the question of how a Kafka topic should even be represented as a queryable table in the first place. I'll share how we're approaching this at StreamNative, what's working, and where the rough edges still are. Plenty of time for questions and arguments afterward, which is honestly the part I look forward to most. Hybrid format — join in person if you're in Budapest, or tune in virtually from anywhere. #ApacheIceberg #ApacheKafka #Lakehouse #DataEngineering #StreamingData #DataCatalog #StreamNative #BudapestDataAIForum #DataAndAI

The storage layer for #ApacheKafka is undergoing a massive shift. Two forces are leading the charge: Diskless architectures and Apache Iceberg. Most solutions make you choose between the two. At #Current London, we’re showing you how to unify them. 💡 Join Sijie Guo and Kundan Vyas for our exclusive session to see how #Lakestream and Ursa for Kafka (#UFK) allow native Kafka to run directly on a diskless, Iceberg-native foundation—eliminating the need for complex ETL pipelines entirely. 🎙️ The Session: Diskless Kafka Meets Iceberg - When: Tuesday, May 19 & Wednesday, May 20 | 1:30 PM - The Goal: Learn how to write Kafka topics as queryable Iceberg tables natively, separating compute and storage for ultimate flexibility and cost control. 📍 The Hub: Visit the StreamNative Booth After the session, head over to the #StreamNative booth to see the theory put into practice. Our experts will be on-site to walk you through: - Live Demos: See "Zero-ETL" ingestion into Iceberg in real-time. - Migration Deep-Dives: How to move from self-managed Kafka with zero application changes. - Expert Q&A: Meet our CEO Sijie Guo, CTO Matteo Merli, and technical experts to talk shop. We’re also giving away exclusive StreamNative swag you won’t want to miss! 👕 Let’s build the future of the streaming lakehouse together. See you in London! 🇬🇧

Excited to join the conversation on how streaming systems and AI agents are converging. Our CEO, Sijie Guo, will share insights on why streaming is becoming the backbone of autonomous AI agents — and how real-time data infrastructure is shaping the next generation of AI applications. Looking forward to great discussions with RisingWave, Aiven, and the broader Kafka + AI community in San Francisco. See you there! 🚀 🔗 https://luma.com/ub9sq0u5