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How T-Mobile Is Leveraging Kubernetes to Handle iPhone-Launch Scale

Were you ready for the launch of the new iPhone? Thanks to Kubernetes, T-Mobile was.

In 2015, it took T-Mobile seven months to get new code to production. That certainly wasn’t the speed of delivery that the third-largest wireless carrier in the U.S. needed to keep up with its business goals, so the following year, the company adopted Pivotal’s Platform as a Service offering, Pivotal Cloud Foundry. The migration yielded great results: The time to production shrank to less than a day. 

But not all applications, particularly vendor-delivered ones that were shipped to T-Mobile in Docker containers, ran smoothly on PaaS during updates. The company needed an orchestrator, and the main requirements were high availability at every level, persistent storage, and the ability to patch and upgrade the infrastructure seamlessly without any impact to customers.

“Kubernetes checked a lot of those boxes,” says James Webb, Member of Technical Staff, and by that point, “it had become the dominant force.” The team spent six months working with an outside company to build a completely open source Kubernetes platform for T-Mobile, but when Pivotal rolled out PKS, they decided to switch over. “We deploy Cloud Foundry in a very specific way, and if we could do the same thing with Kubernetes, that gives us a lot of efficiencies in terms of how we operate, the automation we build, the monitoring we do,” says Brendan Aye, Director, Platform Architecture. “It was win-win-win.” 

During the new iPhone launch last September—the beginning of the peak retail season for T-Mobile—a small amount of production traffic was running on Kubernetes. Soon the company was able to do 95% of deployments in daytime with zero impact, and for development teams, getting a new database went from 5 days to 5 seconds.

This September, Aye says, “we’ll have a huge portion of apps, especially in the sales path for iPhone, running on Kubernetes.”

Read more about T-Mobile’s adoption of Kubernetes for iPhone-launch scale in the full case study.