Using Docker to Scale Operational Intelligence at Splunk
With more than 14,000 customers in 110+ countries, Splunk is the market leader in analyzing machine data to deliver operational intelligence for security, IT and the business. Our rapid growth as a company meant that our Infrastructure Engineering Team, responsible for all the common tooling, build and test systems and frameworks utilized by the Splunk engineers, was bogged down with a sprawl of virtual machines and physical servers that were becoming incredibly difficult to manage. And as our customer’s demand for data has grown, testing at the scale of petabytes/day has become our new normal. We needed a reliable and scalable “Test Lab” for functional and performance testing. With Docker Enterprise Edition, our engineers are able to create small test stacks on their laptop just as easily as creating multi-petabyte stacks in our Test Lab. Support for Windows, Role Based Access Control and having support for both the orchestration platform and the container engine were key in deciding to go with Docker over other solutions. In this talk, we will cover the architecture, tooling, and frameworks we built to manage our workloads, which have grown to run on over 600 bare-metal servers, with tens of thousands of containers being created every day. We will share the lessons learned from running at scale. Lastly, we will demonstrate how we use Splunk to monitor and manage Docker Enterprise Edition. Speakers: Mike Dickey - Sr Director, Engineering, Splunk.
Harish Jayakumar - CA, Docker.