Hadoop and Spark on Docker: Container Orchestration for Big Data

Presented by

Anant Chintamaneni, Vice President, Products, BlueData; Tom Phelan, Chief Architect, BlueData

About this talk

Watch this on-demand webinar to learn the key considerations and options for container orchestration with Big Data workloads. Container orchestration tools such as Kubernetes, Marathon, and Swarm were designed for a microservice architecture with a single, stateless service running in each container. But this design is not well suited for Big Data clusters constructed from a collection of interdependent, stateful services. So what are your options? In this webinar, we discussed: - Requirements for deploying Hadoop and Spark clusters using Docker containers - Container orchestration options and considerations for Big Data environments - Key issues such as management, security, networking, and petabyte-scale storage - Best practices for a scalable, secure, and multi-tenant Big Data architecture Don’t miss watching this webinar on container orchestration for Hadoop, Spark, and other Big Data workloads.

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Hewlett Packard Enterprise (HPE) is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.