As mentioned in chapter “Design for Scale”, the automation of data services is not restricted to the creation of data service instances such as provisioning database clusters on-demand. In order to work at platform scale, delivering a number of data services to a large number of platform environments across multiple infrastructures requires the automation of the entire data service lifecycle beyond the lifecycle of resulting service instances. (more…)
The necessity to create backups needs no justification. Everybody knows that backups are mandatory.
An exception to this rule may be systems that are inherently designed for high-availability and use a high-number of data replicas. Especially, when dealing with vast volumes of data, this might be a valid strategy. (more…)
Rebuild Instead of Fixing It
Full lifecycle management for a range of data services is hard; as every data service is different and comes with different edge cases. The automation needs to cover basic developer needs from the beginning and then may mature over time. (more…)