Alexander Gallego

Alex and Noah talk with Alexey Fyodorov about Co-designing Raft + thread-per-core execution model for the Kafka-API

Eliminating the data ping-pong

Alex joins Eric from Contributor Podcast to talk about Redpanda and the future of streaming

Alex joins Rob and Jason from CppCast to talk about event streaming in C++

A benchmark of Redpanda and Apache Kafka

How to turn data streams into data products.

Hello world! with Tensorflow and Redpanda

A new storage engine built from the ground up for Kafka-API compatibility with Kernel bypass technologies for 10x lower tail latencies

Big news! Today we are announcing that Redpanda is now free and source available!

See our fireside chat with LinkedIn's Kafka and Samza teams as we dive deep into the technical architecture of redpanda

The dataengineering podcast interview - Speed Up And Simplify Your Streaming Data Workloads With Redpanda, Episode 152

Superscalar CPUs with wide GB/s memory, NVMe access times in the order of 10-100’s of microseconds, necessitates a new buffer management for low latency storage systems.

Autotuning, or increasing the vertical scalability via performance engineering, is focused on the time, energy and ultimately, the cost to run a system.

Hardware is fast, but most do not architect software to take advantage of these hardware advances. At worse, running software on significantly better hardware crashes your app because of latent bugs.