In this blog post we'll explain how transactions work in Kafka by comparing and contrasting the implementations of transactions in two different Kafka implementations: the official Apache Kafka project, and WarpStream.
In this post, we’ll look at what noisy neighbors are, the current ways to handle them (cluster quotas and mirroring clusters), and how WarpStream’s solution compares in terms of elasticity, operational simplicity, and cost efficiency.
WarpStream BYOC reimplements the Kafka protocol with a stateless, zero-disk cloud-native architecture, replacing Kafka brokers with WarpStream Agents to simplify operations. But data streaming extends beyond Kafka clusters alone.
In this post, I’ll start off with a brief overview of “shared nothing” vs. “shared storage” architectures in general. This discussion will be a bit abstract and high-level, but the goal is to share with you some of the guiding philosophy that ultimately led to WarpStream’s architecture.
Orbit is a tool which creates identical, inexpensive, scaleable, and secure continuous replicas of Kafka clusters. It is built into WarpStream and works without any user intervention to create WarpStream replicas of any Apache Kafka-compatible source cluster.
WarpStream now supports AWS Glue Schema Registries, in addition to the Kafka-compatible schema registries. The WarpStream Agent can use schemas stored in the user’s AWS Glue Schema Registries to validate records.
Backpressure is a really simple concept. When the system is nearing overload, it should start “saying no” by slowing down or rejecting requests. Of course, the big question is: How do we know when we should reject a request?