Editor’s notice: Renault, the French automaker, launched into a wholesale migration of its knowledge techniques—shifting 70 packages to Google Cloud. Right here’s how they migrated from Oracle databases to Cloud SQL for PostgreSQL.
The Renault Workforce, recognized for its iconic French vehicles has grown to incorporate 4 complementary manufacturers, and bought just about 3 million automobiles in 2020. Following our company-wide strategic plan, “Renaulution,” we’ve shifted our focal point during the last 12 months from a automotive corporation integrating tech, to a tech corporation integrating vehicles that can expand tool for our industry. For the ideas techniques team, that supposed modernizing our complete portfolio and migrating 70 in-house packages (our high quality and buyer knowledge techniques) to Google Cloud. It used to be an bold undertaking, but it surely’s paid off. In two years we migrated our High quality and Buyer Pleasure knowledge techniques packages, optimized our code, and minimize prices due to controlled database services and products. In comparison to our on-premises infrastructure, the use of Google Cloud services and products and open-source applied sciences involves more or less one greenback consistent with consumer consistent with 12 months, which is considerably inexpensive.
An bold adventure to Google Cloud
We started our cloud adventure in 2016 with virtual tasks integrating a brand new manner of running and new applied sciences. Those new applied sciences incorporated the ones for agility at scale, knowledge features and CI/CD toolchain. Google Cloud stood out because the transparent selection for its knowledge features. No longer best are we the use of BigQuery and Dataflow to support scaling and prices, however we also are now the use of totally controlled database services and products like Cloud SQL for PostgreSQL. Knowledge is a key asset for a contemporary automotive maker as it connects the auto maker to the consumer, lets in automotive makers to raised perceive utilization and higher informs what selections we must make about our services. Once we migrated our knowledge lake to Google Cloud, it used to be a herbal subsequent step to transport our front-end packages to Google Cloud so they’d be more uncomplicated to care for and lets have the benefit of sooner reaction instances. This undertaking used to be no small enterprise. For the ones 70 in-house packages (e.g. automobile high quality analysis, statistical procedure regulate in vegetation, product factor control, survey research), for our knowledge techniques panorama, we had a spread of applied sciences—together with Oracle, MySQL, Java, IBM MQ, and CFT—with some packages created two decades in the past.
Champions spearhead every migration
Prior to we began the migration, we did a world research of the panorama to know every software and its complexity. Then we deliberate a revolutionary method, that specialize in the smallest packages first similar to the ones with a restricted selection of displays or with easy SQL queries, and saving the most important for remaining. To begin with we used some automated gear for the migration, however we realized in no time not anything can exchange the advance workforce’s institutional wisdom. They served as our migration champions.
