The following teaser is from an article posted January 14, 2020 at ciodive.com.
Ancestry spent two years executing its shift to the cloud. In that time, the genealogy company migrated a database of over 20 million members away from data centers and into Amazon Web Services.
After the move the company turned attention to optimizing its presence in the cloud, manually adjusting workload settings to improve efficiency and reduce costs.
“Due to the fact that it’s a manual process, we iterated very slowly,” said Darek Gajewski, principal infrastructure analyst at Ancestry, in an interview with CIO Dive. “It takes time for us to do performance testing and then being able to get it out into our production environment safely so that we’re not affecting our customers at the end of the day.”
But there was still room for improvement. An initial proof of concept from Opsani — an AIOps company that relies on machine learning and artificial intelligence — pointed the way to areas to optimize cloud use without hampering user experience.
“We let the system run its course, give us feedback, and then we implemented the recommendations that Opsani’s tool gives us without having to spend a copious amount of time trying to come up with the most efficient path for that application,” said Gajewski.
Driven by the threat of cloud cost overrun, cloud-based companies such as Ancestry are turning to AI to increase infrastructure efficiency and reduce the length of cloud receipts.
