Presented by: Santosh Bardwaj, Senior Director of Technology, CapitalOne
Capital One’s Data analysts have traditionally used leading analytic tools to prototype new insights and build stat models. To improve analyst productivity and innovation, Cap1 has embarked on a re-invention of the Data technology stack by deploying a Big Data Hub consisting of a central Hadoop Data Lake and a large suite of Open source tools and SW packages.
The platform & engineering team had to come up with a solution to enable fast prototyping of tools, isolate the workload in a contained environment and integrate it into a self-service portal . After evaluating different options, we chose Docker to build an ‘Analytic garage’ for the enterprise .
We’ll walk through some of the challenges we faced and techniques we used to integrate a wide variety of technologies into a single Docker container, access management, security & audit. As we expand the user base within the organization, we'll share future plans to progress innovations from the garage to a production ready Docker Analytic platform .
Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere.
Docker containers can encapsulate any payload, and will run consistently on and between virtually any server. The same container that a developer builds and tests on a laptop will run at scale, in production*, on VMs, bare-metal servers, OpenStack clusters, public instances, or combinations of the above.