Managing Data At Scale with Kasten’s Georgi Matev
For microservices environments, data can be tricky. In a system where everything is designed to be highly ephemeral, scalable, and temporary, data storage doesn’t fit into any of those categories. Stateful applications require stable data platforms that don’t vanish when traffic goes down, or get overwhelmed when a site is overloaded. Because of this square-peg-round-hole problem, a lot of DevOps practitioners can find themselves caught behind the weight of the data. It can drag down an agile process, creating large gaps in release cycles as teams wait for DBAs to adjust the store by hand, or to update the schema to accommodate an application change.