The Kafka Metric You're Not Using: Stop Counting Messages, Start Measuring Time

Aratz Manterola Lasa
July 16, 2024
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.
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Multiple Regions, Single Pane of Glass

Emmanuel Pot
June 20, 2024
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.
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Secure by default: How WarpStream’s BYOC deployment model secures the most sensitive workloads

Caleb Grillo
June 10, 2024
WarpStream's Zero Disk / Diskless Architecture enables a BYOC deployment model that is secure by default and does not require any external access to the customer's environment.
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Announcing Bento, the open source fork of the project formerly known as Benthos

Richard Artoul
May 31, 2024
Announcing Bento, the open source fork of the project formerly known as Benthos.
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Zero Disks is Better (for Kafka) - Diskless Kafka

Richard Artoul
May 23, 2024
Follow up to "Tiered Storage Won't Fix Kafka", this post covers all the different advantages that WarpStream's Zero Disk / Diskless Architecture provides over Apache Kafka.
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Tiered Storage Won’t Fix Kafka

Richard Artoul
April 28, 2024
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.
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Cloud Disks are (Really!) Expensive

Richard Artoul
April 20, 2024
Cloud disks are expensive. Really expensive. Most engineers intuitively understand this, but the magnitudes are worth considering.
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The Original Sin of Cloud Infrastructure

Richard Artoul
March 14, 2024
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?
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