Optimized Scheduling for Big Data Workloads - The Why, What... Rahul Sharma & Wilfred Spiegelenburg скачать в хорошем качестве

Optimized Scheduling for Big Data Workloads - The Why, What... Rahul Sharma & Wilfred Spiegelenburg

Don't miss out! Join us at our next Flagship Conference: KubeCon + CloudNativeCon events in Amsterdam, The Netherlands (23-26 March, 2026). Connect with our current graduated, incubating, and sandbox projects as the community gathers to further the education and advancement of cloud native computing. Learn more at https://kubecon.io Optimized Scheduling for Big Data Workloads - The Why, What and How of K8s Schedulers - Rahul Sharma & Wilfred Spiegelenburg, Cloudera Stateful workloads like databases, caching systems, and message brokers are the backbone of many modern applications, yet they pose distinct challenges within Kubernetes. Unlike their stateless counterparts, these workloads demand persistent storage, stable network identities, and precise resource allocations. The default Kubernetes scheduler, while robust, often struggles to meet these specialized needs, potentially resulting in performance degradation, resource inefficiencies, or operational instability. In this session, we’ll take a deep dive into the art of scheduling stateful workloads, breaking it down into three essential components - why, what and how of the most popular Kubernetes schedulers out there. By the end of this talk, attendees will walk away with a clear understanding of how to adapt Kubernetes scheduling to the unique demands of big data workloads.