WarpStream

pprof is an amazing tool for debugging memory leaks, but what about when it's not enough? Read about how we used gcore and viewcore to hunt a particularly nasty memory leak in a large distributed system. https://lnkd.in/ezUdVMB2

S3 Express One Zone (S3EOZ) prices are 85% cheaper than they used to be. When you pair S3EOZ with WarpStream, latency is 3x lower at only a 15% higher TCO 👉 https://lnkd.in/ea4gRPhR

🌑 Entire cloud region goes dark? Your streams shouldn't. WarpStream's Multi‑Region Clusters replicate every write across 3 regions, delivering true RPO=0 and a 99.999% uptime SLA. Never lose a record, even during region‑wide outages 👉 https://lnkd.in/g8xxEbKW

Did you know Cursor's Kafka-compatible data streaming infrastructure is powered by WarpStream? Learn about: 🙌 Why they picked WarpStream over OSK ⏲️ Latency 🔒 Data privacy 📊 Scaling and zero ops 🚀 And more https://lnkd.in/eYeafaHW

Learn how WarpStream leverages Antithesis to do deterministic simulation testing for our entire SaaS — from sign up to creating a virtual cluster to producing and consuming data, and why we chose it over Jepsen 👉 https://lnkd.in/eWVxVZsA

It's a bold claim we're making: that we can reduce Apache Kafka cloud costs by as much as 10x (by removing interzone networking fees and using object storage). See how our benchmarks show how we do that 👉 https://lnkd.in/eABQNtw5

WarpStream now exposes an MCP server. Ask your AI assistant to check Diagnostics, query ACL denials, inspect consumer group lag, or search Agent logs — across every cluster, without leaving your IDE 👉 https://lnkd.in/gXe6kkTV

WarpStream Tableflow is the easiest, cheapest, and most flexible way to convert Kafka topic data into Iceberg tables with low latency, and keep them compacted 🧊 https://lnkd.in/g-RY_df4

WarpStream Diagnostics continuously analyzes your clusters to identify potential problems, cost inefficiencies, and ways to improve things: https://lnkd.in/e9JiiFNm

Distributed systems built on object storage share a common problem: removing files that have been logically deleted, either due to data expiry or compaction. What's the solution? We'll give a hint: it's not bucket policies or synchronous deletion 👉 https://lnkd.in/e-5vNTPe