The Netflix data platform is a massive-scale, cloud-only suite of tools and technologies. It includes big data tech (Spark and Flink), enabling services (federated metadata management), and machine learning support. But with power comes complexity. Kurt Brown explains how Netflix is working toward an easier, "self-service" data platform without sacrificing any enabling capabilities.

User-based real-time recommendation systems have become an important topic in ecommerce. Lu Wang, Nicole Kong, Guoqiong Song, and Maneesha Bhalla demonstrate how to build deep learning algorithms using Analytics Zoo with BigDL on Apache Spark and create an end-to-end system to serve real-time product recommendations.

As the popularity and utilization of Apache Impala deployments increases, clusters often become victims of their own success when demand for resources exceeds the supply. Tim Armstrong dives into the latest resource management features in Impala to maintain high cluster availability and optimal performance and provides examples of how to configure them in your Impala deployment.

Uber relies on Big Data and ML to make business critical decisions such as pricing, trip ETA, etc. Today, those workloads such as Hive and Spark are running on YARN. To save millions of dollars by eff …

Many existing applications like the Big Data stack is in a community debate over moving to K8s. They see it as the future, but there are lots of unknowns and complex problems to solve. This is a dialo …

Kubernetes support schedule workloads based on CPU and memory resource with node affinity, pod affinity and anti-affinity. This works very well for stateless workloads. For stateful workloads, especia …

Kubernetes not only becomes predominant in public cloud area these days, but also becomes a new trend in on-premises big data cluster environment, as an alternative of Hadoop YARN, a resource schedule …