The separation of the two Silicon Valley tech giants was announced and the critical work relating to the partition needs to be executed and completed within 3 months when the companies became legally different entities.
Databases residing inside the internal OpenStack cloud's DBaaS (Database-as-a-Service) needed to be segregated and migrated to their respective company clouds. Failure in separating of data of the cloud database will create complications that are not just technical, but operational and legal.
Due to the massive size of database accounts and storage, the variety of database types, the sensitivity of the data and the limited time that the task needed to be completed, a manual operation is just not feasible.
The attempt to automate the separation of the data in the cloud database was faced with challenges of bugs, errors, and slowness. Often it is the resource-related in the transfer due to the wrong implementation strategy.
Omar asked to develop an automation framework, strategy, and implementation that allows the separation of DBaaS instance and data as part of an executed job.
Omar wrote a framework with a workflow of replicating the database instance for the separated companies, and a pipeline connecting the cloud databases, allowing for data to be piped, with little resource usage due to little to no memory buffer required to hold the data in transit.
The framework developed by Omar was able to accommodate all database types of the DBaaS (MySQL, Cassandra, MongoDB, Redis, ...)
The framework that Omar developed was ready by the scheduled date for data migration. Migration was successful and seamless with no issues. The execution was completed on schedule, saving the companies many financial and legal complications, maintaining the productivity of DBaaS tenants.
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