Editor’s note: The video platform Vimeo leverages managed database services from Google Cloud to serve up billions of views around the world each day. Here’s how they deliver a consistent user experience across all their content.
Vimeo is the world’s leading video software solution, powering hundreds of thousands of new uploads every day and billions of views. At our scale, it’s paramount that we retain a seamless user experience across all of the videos hosted, shared, and viewed on our platform. With managed database services from Google Cloud, we’ve been able to deliver a consistent and reliable user experience no matter where our users and their audiences are.
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Outgrowing the data center and gaining more scale
Our first exposure to Google Cloud was the excellent performance between Google Compute Engine (GCE) and Google Cloud Storage (GCS), which we used to design a really high quality playback and upload environment for our customers’ videos. At first we were simply creating cloud-based packaging and delivery of their content, but the bulk of our application ran on an on-premises MySQL database. Seeing the gains from our initial investment in GCE and GCS, we decided to fully migrate to Google Cloud.
We started by lifting and shifting our workloads from our on-premises deployments to GCE. But we quickly realized we had to redesign our application to deliver higher availability and responsiveness for an exceptional user experience, which led us to Cloud Spanner, a distributed SQL database management and storage service. With Spanner, we found all the benefits of a relational semantics database with global scale, allowing us to add more nodes with the push of a button.
Today we have a multi-region instance with 99.999% uptime, so we’re confident it can handle our video workloads. We use about 16 Spanner nodes to cover approximately 50.8 billion rows and about 4.5 terabytes of storage/disk space. And with the launch of Video Library, we have the scale we need to fundamentally change the way organizations handle content.
Using Spanner as a time machine during migration
During the initial migration, we wanted to ensure an accurate data transfer with as few errors or bugs as possible. When we moved data from MySQL tables into Spanner, we ran spot analyses to check for potential problems. If the data didn’t match, Spanner allowed us to revert to the original in a single click. Through Spanner we could check stale timestamps or past users. It almost functioned like a time machine by offering point-in-time recovery functionality.
Serving up any video at any time
We work with a long tail of content. Depending on how popular a video is, we take a different approach to storing it. We cache the most popular material so it’s immediately accessible and use Cloud Spanner to ensure it’s highly available across multiple regions. On the flip side, we use Cloud SQL for some lower volume satellite services that support other components of the application that don’t require the same guarantees or performance that Cloud Spanner provides.
As our millions of users continue to upload their own videos, Spanner also acts as a video metadata indexing and cataloging service. When we need to play back a particular video, we can quickly and easily find it in a sea of content. It’s crucial that our database is highly available and reliable so the playback experience is seamless for our users.
To learn more about Vimeo, visit our site.
Learn more about how your organization can use Cloud Spanner.
By: Sergio Salvatore (Senior director of Engineering, Vimeo)
Source: Google Cloud Blog
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