WarpStream now has the capability to connect to external schema registries, and verify that records actually conform to the provided schema.

Traditional offset-based monitoring can be misleading due to varying message sizes and consumption rates. To address this, you can introduce a time-based metric for a more accurate assessment of consumer group lag.

How we built support for running WarpStream's control plane and Metadata Store in multiple regions, while still presenting our platform as a single pane of glass.

WarpStream's Zero Disk Architecture enables a BYOC deployment model that is secure by default and does not require any external access to the customer's environment.

Announcing Bento, the open source fork of the project formerly known as Benthos.

Follow up to "Tiered Storage Won't Fix Kafka", this post covers all the different advantages that WarpStream's Zero Disk Architecture provides over Apache Kafka.

Tiered storage is a hot topic in the world of data streaming systems, and for good reason. Cloud disks are (really) expensive, object storage is cheap, and in most cases, live consumers are just reading the most recently written data. Paying for expensive cloud disks to store historical data isn’t cost-effective, so historical data should be moved (tiered) to object storage. On paper, it makes all the sense in the world.

Cloud disks are expensive. Really expensive. Most engineers intuitively understand this, but the magnitudes are worth considering.

Many of today's most highly adopted open source “big data” infrastructure projects – like Cassandra, Kafka, Hadoop, etc. – follow a common story. A large company, startup or otherwise, faces a unique, high scale infrastructure challenge that's poorly supported by existing tools. They create an internal solution for their specific needs, and then later (kindly) open source it for the greater community to use. Now, even smaller startups can benefit from the work and expertise of these seasoned engineering teams. Great, right?

How we leverage Antithesis to deterministically simulate our entire SaaS platform and verify its correctness, all the way from signup to running entire Kafka workloads.

A huge part of building a drop-in replacement for Apache Kafka® was implementing support for compacted topics. The primary difference between a “regular” topic in Kafka and a “compacted” topic is that Kafka will asynchronously delete records from compacted topics that are not the latest record for a specific key within a given partition.

Serverless products and usage based billing models go hand in hand, almost by definition. A product that is truly serverless effectively has to have usage based pricing, otherwise it’s not really serverless!

The future of modern data infrastructure is object storage.

How we separated data from metadata to build support for idempotent producers in our Apache Kafka protocol layer.

We first introduced WarpStream in our blog post: "Kafka is Dead, Long Live Kafka", but to summarize: WarpStream is a Kafka protocol compatible data streaming system built directly on top of object storage.

How we built stateless load balancing into a protocol that was never designed for it.

Chances are you probably had a strong reaction to the title of this post. In our experience, Kafka is one of the most polarizing technologies in the data space. Some people hate it, some people swear by it, but almost every technology company uses it.