Until now, traditional databases have been difficult to deploy on Kubernetes because they weren’t designed to work in containerized environments. Enterprises were forced to create their own solutions or, more often, rely on the cloud providers’ own cloud database offerings, which locked them into that particular cloud platform.
That’s been changing over the past few months, with increased support for both SQL and noSQL databases on Kubernetes from the open source community and from vendors offering additional support and management tools.
For the past few years, enterprises have been making dramatic moves cloud infrastructure. With the COVID-19 pandemic, in the past year that flow turned into a tsunami.
According to a March survey by Flexera, 99% of companies now have a cloud adoption strategy, with 92% opting for a multicloud option with combinations of different public clouds or public and on-premises clouds.
And the percentage of companies spending at least $1 million a month on cloud services is now at 31%, nearly double the 16% in last year’s survey. Half of all workloads are now in the cloud, and enterprises plan to increase that to 57%.
Container adoption, too, has risen with the flood to the cloud. According to a 2020 survey by the Cloud Native Computing Foundation, 92% of the global cloud user community is using containers in production, up from 84% in 2019, and up 300% from the organization’s first survey in 2016.
Kubernetes accounts for much of that container usage, with 83% using Kubernetes as their preferred container platform, up from 78% in 2019.
Data services are right behind. According to the Flexera survey, 87% of companies are either using, experimenting with or planning to use data warehouses or relational databases as a service.
In fact, 46% of organizations’ data is already in public clouds, and will grow to 54% in the next 12 months.
Gartner predicts that by 2022, more than 75% of organizations will be running containerized applications in production.
According to the Flexera survey, Docker and Kubernetes account for the bulk of the container tools used. Companies are adopting containers to shorten development cycles, simplify cloud migrations and lower cloud costs.
“Containers are all about horizontal scalability,” said Sam Ramji, chief strategy officer at DataStax. “If we could vertically scale everything, we would still be on mainframes or running giant Java virtual machines.”
In those older approaches, organizations would see months between software updates, if not longer.
“Continuous delivery companies can iterate multiple times a day,” he said. “That’s the first driver for Kubernetes — lean flow, the ability to reduce the cycle time between coming up with an idea and implementing it in production.”
This changes the kind of products you can offer to your customers, said Ramji.
“We were able to generate multiple billion-dollar ideas at Google,” said Ramji, who was once vice president of product management there. “We could try out lots of ideas to see if they worked.”
With this approach to development, he said, “you can satisfy your customers, fight for market share and benefit from unit economics. You can take a million lines of code, break it up into a hundred different microservices with different topologies, and each piece can scale independently.”
But as organizations make the move to the cloud, containers and Kubernetes, data has been a challenge.
Containers favor a “stateless” approach to application development. Individual containers can spin up and down on-demand, so the applications can’t be designed to run continuously and remember what they’re working on. If a containerized application has a built-in database, that database disappears when the container shuts down and is recreated from scratch when it boots back up again.
“Single-instance databases are kind of going to die in this environment,” Ramji said.
