Anyscale transfers the Ray distributed computing framework to the PyTorch Foundation, creating a unified, vendor-neutral AI stack with PyTorch and vLLM.
Introducing ClientIsolationHost, a new component for the Isolator framework that enables executing sandboxed code plugins on remote machines over TCP/IP.
A beginner-friendly introduction to using PySpark for big data processing with Apache Spark, covering the fundamentals.
A guide on deploying and running a Dask distributed computing cluster on a Databricks analytics platform alongside Apache Spark.
Using dask-ctl to run Dask workloads on multiple cluster backends (like LocalCluster, KubeCluster) with zero code changes via YAML configuration.
A software engineer outlines his 2024 blog plans, focusing on advanced engineering topics, career insights, visual tutorials, and community growth.
A detailed case study on debugging a scaling issue in a large-scale Apache Beam and Dask workflow involving hundreds of GPU workers.
A guide to setting environment variables on Dask cluster workers to ensure remote tasks have access to necessary keys and configurations.
Announcing the 2021 Ihaka Lectures featuring local experts on distributed computing, machine learning for child welfare, and applied math for COVID-19 response.
A technical guide on setting up and analyzing distributed Dask clusters for parallel computing across multiple machines.
A tutorial on using Daskernetes to create auto-scaling, personal Python clusters on Kubernetes for distributed computing tasks.
A technical guide on integrating Google Guice dependency injection with Hazelcast's distributed ExecutorService for stateful tasks in Java.
An analysis of Butler Lampson's 1999 predictions on computer science, comparing what worked then to the state of technology in 2015.
Explains the eight common but false assumptions developers make when building distributed systems, leading to major issues.
