Put open source to work
July 16–17, 2018: Training & Tutorials
July 18–19, 2018: Conference
Portland, OR

Pinterest's journey from VMs to containers in the public cloud

Micheal Benedict (Pinterest)
2:35pm–3:15pm Wednesday, July 18, 2018
Business Summit and Case Studies
 Location: D139/140
Level: Advanced
Average rating: ****.
(4.33, 3 ratings)

Who is this presentation for?

  • Software engineers, DevOps engineers, CIOs, and architects

Prerequisite knowledge

  • A basic understanding of containers and public cloud concepts (IAM, security groups, networking, etc.)

What you'll learn

  • Explore Pinterest's evaluation framework
  • Learn the steps involved in moving from VMs to containers in a public cloud environment
  • Explore specific design decisions Pinterest made to accommodate use cases such as long-running stateless services, batch, and stateful services

Description

Pinterest helps you discover and do what you love. Pinterest’s infrastructure is built to cater to its scale—over 150M MAUs across the globe contributing and combing through a billion pins—which has very unique requirements. Micheal Benedict explains how Pinterest, a company operating on VMs in the public cloud since its inception, made a move to containers.

Topics include:

  • Pinterest’s infrastructure (offline compute, online serving)
  • VMs versus containers, with regard to developer velocity, service reliability, infrastructure governance, and efficiency
  • Moving to containers, using Docker
  • Pinterest’s compute platform
Photo of Micheal Benedict

Micheal Benedict

Pinterest

Micheal Benedict leads product management for Pinterest’s cloud and data processing infrastructure, where he and his team are building a multitenant compute infrastructure to support Pinterest’s growing set of diverse workloads. He also manages the cloud capacity planning and the infrastructure governance teams. Previously, Micheal led products for Twitter Cloud Platform, building next-generation compute services that span internal and public clouds, and built the systems that powered Twitter’s observability and monitoring stack. Micheal holds a master’s degree in computer science from the State University of New York at Buffalo.