USE-CASES OF INDUSTRIES SOLVED BY KUBERNETES

Kubernetes has now become the de facto standard for deploying containerized applications at scale in private, public and hybrid cloud environments. The largest public cloud platforms AWS, Google Cloud, Azure, IBM Cloud and Oracle Cloud now provide managed services for Kubernetes. A few years back RedHat completely replaced their OpenShift implementation with Kubernetes and collaborated with the Kubernetes community for implementing the next generation container platform. Mesosphere incorporated key features of Kubernetes such as container grouping, overlay networking, layer 4 routing, secrets, etc into their container platform DC/OS soon after Kubernetes got popular. DC/OS also integrated Kubernetes as a container orchestrator alongside Marathon. Pivotal recently introduced Pivotal Container Service (PKS) based on Kubernetes for deploying third-party services on Pivotal Cloud Foundry and as of today there are many other organizations and technology providers adapting it at a rapid phase.

Kubernetes:

it is orchestration engine platform and is a system for running and coordinating containerized applications across a cluster of machines. It is a platform designed to completely manage the life cycle of containerized applications and services using methods that provide predictability, scalability, and high availability.

Benefits of Kubernetes for the companies:

• Using Kubernetes and its huge ecosystem can improve productivity.
• Using Kubernetes along with good native cloud technology attracts talent. For example, many software engineers want to work in companies that use modern and interesting technologies.
• Kubernetes is a feasible solution for many years to come.
• Kubernetes helps an application run more stably.
• Kubernetes can be cheaper than other alternatives, especially if you have large computing resources.

OPENAI and Kubernetes:

Challenge

An artificial intelligence research lab, OpenAI needed infrastructure for deep learning that would allow experiments to be run either in the cloud or in its own data center, and to easily scale. Portability, speed, and cost were the main drivers.

Solution

OpenAI began running Kubernetes on top of AWS in 2016, and in early 2017 migrated to Azure. OpenAI runs key experiments in fields including robotics and gaming both in Azure and in its own data centers, depending on which cluster has free capacity. “We use Kubernetes mainly as a batch scheduling system and rely on our autoscaler to dynamically scale up and down our cluster,” says Christopher Berner, Head of Infrastructure. “This lets us significantly reduce costs for idle nodes, while still providing low latency and rapid iteration.”

Impact

The company has benefited from greater portability: “Because Kubernetes provides a consistent API, we can move our research experiments very easily between clusters,” says Berner. Being able to use its own data centers when appropriate is “lowering costs and providing us access to hardware that we wouldn’t necessarily have access to in the cloud,” he adds. “As long as the utilization is high, the costs are much lower there.” Launching experiments also takes far less time: “One of our researchers who is working on a new distributed training system has been able to get his experiment running in two or three days. In a week or two he scaled it out to hundreds of GPUs. Previously, that would have easily been a couple of months of work.”

SPOTIFY and Kubernetes:

Challenge

Launched in 2008, the audio-streaming platform has grown to over 200 million monthly active users across the world. “Our goal is to empower creators and enable a really immersive listening experience for all of the consumers that we have today — and hopefully the consumers we’ll have in the future,” says Jai Chakrabarti, Director of Engineering, Infrastructure and Operations. An early adopter of microservices and Docker, Spotify had containerized microservices running across its fleet of VMs with a homegrown container orchestration system called Helios.

Solution

“We saw the amazing community that had grown up around Kubernetes, and we wanted to be part of that,” says Chakrabarti. Kubernetes was more feature-rich than Helios. Plus, “we wanted to benefit from added velocity and reduced cost, and also align with the rest of the industry on best practices and tools.” At the same time, the team wanted to contribute its expertise and influence in the flourishing Kubernetes community. The migration, which would happen in parallel with Helios running, could go smoothly because “Kubernetes fit very nicely as a complement and now as a replacement to Helios,” says Chakrabarti.

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