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Apache Kafka is one of the most commonly used stream-processing applications. Its high performance, low latency and open source license are just some of the reasons 80% of Fortune 100 enterprises use Kafka to power event-driven applications and deliver resilient data pipelines.
But when you start working with massive amounts of high-velocity data, you quickly run into cost, operational and complexity problems. For cloud native businesses, high replication costs when running Kafka across multiple cloud availability zones are a very serious issue.
Recently, Aiven has focused on addressing this problem with Inkless Kafka, its fork of the project. Inkless Kafka is based on a fully open source and open source aligned design that proposes to extend Kafka with Diskless topics. This design “proposes a new class of topics in Apache Kafka that delegates replication to object storage,” wrote Filip Yonov, head of streaming services at Aiven, in a blog post.
“Rather than eliminating disks altogether, Diskless abstracts them away — leveraging object storage (like S3) to keep costs low and flexibility high,” Yonov said.
If running Kafka at scale is giving you headaches, watch Kafka at Scale: Smarter Architectures for Real-Time Business Impact, now available on demand.
During this free webinar, Greg Harris, open source software engineer at Aiven (and lead author of KP-1150), David Esposito, streaming architect at Aiven, and Chris Pirillo, TNS host, discussed how leading companies are adapting their Kafka architecture to manage larger, faster data streams and deliver real business impact today.
In addition to discussing the pitfalls to avoid when scaling Kafka in the cloud, they’ll also share an exclusive sneak peek at Diskless Topics for Apache Kafka, a breakthrough that removes local disks to make Kafka up to 80% leaner, significantly reducing total cost of ownership (TCO) while simplifying operations and unlocking new ways to scale in the cloud.
By watching, you’ll gain best practices, real-world examples and actionable tips, including: