Airflow Evolution at Snap. Yuri Desyatnik, Zhengyi Liu, Han Gan… | by Yuri Desyatnik | Apache Airflow | Medium
Yuri Desyatnik, Zhengyi Liu, Han Gan, Nanxi Chen, Jun Gao| Medium
Yuri Desyatnik, Zhengyi Liu, Han Gan, Nanxi Chen, Jun Gao| Medium
At Snap, we have a strong focus on user experience and have built many ML applications to surface the right content to our users. We present Robusta: our in-house feature platform, built to streamline and accelerate ML iteration.| eng.snap.com
Building ML at scale: Discover how Snap's Bento ML Platform powers personalized user experiences through cutting-edge ML Ops| eng.snap.com
Google Cloud training and certification, and business support services to enable Snap to scale global business strategy.| Google Cloud Blog
Snap was born in the cloud — launching its flagship app, Snapchat, in 2011 on a cloud-native, monolithic architecture. As the app grew in popularity, Snap migrated to a microservices architecture on Amazon Web Services (AWS) to improve scalability, optimize availability, minimize latency, and reduce costs. On AWS, Snap now supports more than 306 million Snapchat users sending over 5.4 billion Snaps daily with 20 percent less latency than its prior architecture. Freed from managing infrastru...| Amazon Web Services, Inc.
As we offload more to AI, we risk losing the subtle instincts that make great developers great.| architecturenotes.co
Learn about the Data Tech Stack used by Netflix to process trillions of events every day.| www.junaideffendi.com
Learn about the Data Tech Stack used by DoorDash to process hundreds of Terabytes of data every day.| www.junaideffendi.com
