Cross-posted on Google Cloud Platform Blog.
Cloud native
technologies like Kubernetes help you compose scalable services out
of a sea of small logical units. In our last post, we introduced Vitess (an open-source
project that powers YouTube's main database) as a way of turning
MySQL into a scalable Kubernetes application. Our goal was to
make scaling your persistent datastore in Kubernetes as simple as
scaling stateless app servers - just run a single command to
launch more …
Oct
06
2015
Oct
06
2015
Cross-posted on Google Cloud Platform Blog. Cloud native technologies like Kubernetes help you compose scalable services out of a sea of small logical units. In our last post, we introduced Vitess(an open-source project that powers YouTube's main database) as a way of turning MySQL into a scalable Kubernetes application. Our goal was to make scaling your persistent datastore in Kubernetes as simple as scaling stateless app servers - just run a single command to launch more pods.
Mar
20
2015
Cross-posted on Google Cloud Platform Blog.
Your new website is growing exponentially. After a few rounds of
high fives, you start scaling to meet this unexpected demand.
While you can always add more front-end servers, eventually your
database becomes a bottleneck, which leads you to . . .
- Add more replicas for better read throughput and data durability
- Introduce sharding to scale your write throughput and let your data set grow beyond a single machine
- Create separate replica pools for batch jobs and backups, to isolate them from live traffic
- Clone the whole deployment into multiple datacenters worldwide for disaster recovery and lower latency
At YouTube, we went on that …
Mar
20
2015
Cross-posted on Google Cloud Platform Blog. Your new website is growing exponentially. After a few rounds of high fives, you start scaling to meet this unexpected demand. While you can always add more front-end servers, eventually your database becomes a bottleneck, which leads you to... Add more replicas for better read throughput and data durability Introduce sharding to scale your write throughput and let your data set grow beyond a single machine Create separate replica pools for batch jobs and backups, to isolate them from live traffic Clone the whole deployment into multiple datacenters worldwide for disaster recovery and lower latency At YouTube, we went on thatjourney as we scaled our MySQL deployment, which today handles the metadata for billions of daily video views and 300 hours of new video uploads per minute.