36 min listen
Etsy's Big Data Cloud Migration
FromThe Cloudcast
ratings:
Length:
32 minutes
Released:
Aug 14, 2019
Format:
Podcast episode
Description
SHOW: 410DESCRIPTION: Aaron and Brian talk with Kevin McHale (Senior Staff Engineer at Etsy) about the migration of their Big Data / Data Science platform from on-premises to Google Cloud, the business drivers for the migration, and the lessons the team has learned throughout the multi-year process.SHOW SPONSOR LINKS:Digital Ocean HomepageGet Started Now and Get a free $50 Credit on Digital OceanDatadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirt[FREE] Try an IT Pro ChallengeGet 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:GitHub Actions now includes CI/CDSHOW INTERVIEW LINKS:Etsy HomepageEtsy’s Engineering Blog (“Code as Craft”)Migrating Etsy to Google CloudSHOW NOTES:Topic 1 - Welcome to the show. Before we dive into your work at Etsy, tell us a little bit about your background prior to Etsy - you’re pretty good at math. Topic 2 - You’ve been working on two very interesting projects at Etsy - both building/evolving the data platform, and helping to manage the migration to Google Cloud Platform (GCP). Let’s start by talking about the Etsy data platform.Topic 3 - What have been some of the business drivers that are pushing the data platform to collect more information, to become more cloud-native, and to better enable data pipelines? Topic 4 - At some point in 2017-18, Etsy decided to migrate some of the platforms to Google Cloud. Tell us about that decision-process, and how the migration has been going. What have been some of the lessons learned? Topic 5 - How does working with Google Cloud (or just being in the public cloud) help accelerate the work that you’re doing on evolving the Etsy data platform? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast
Released:
Aug 14, 2019
Format:
Podcast episode
Titles in the series (100)
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