How Kubernetes is used in Industries and what all use cases are solved by Kubernetes?
What is Kubernetes?
Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
The name Kubernetes originates from Greek, meaning helmsman or pilot. Google open-sourced the Kubernetes project in 2014. Kubernetes combines over 15 years of Google’s experience running production workloads at scale with best-of-breed ideas and practices from the community.
Why Kubernetes?
The Docker adoption is still growing exponentially as more and more companies have started using it in production. It is important to use an orchestration platform to scale and manage your containers.
Imagine a situation where you have been using Docker for a little while, and have deployed on a few different servers. Your application starts getting massive traffic, and you need to scale up fast; how will you go from 3 servers to 40 servers that you may require? And how will you decide which container should go where? How would you monitor all these containers and make sure they are restarted if they die? This is where Kubernetes comes in.
Case Study: Babylon (AI, Healthcare) - Scheduling and Scalability
Challenge :
A large number of Babylon’s products leverage machine learning and artificial intelligence, and in 2019, there wasn’t enough computing power in-house to run a particular experiment. The company was also growing (from 100 to 1,600 in three years) and planning expansion into other countries.
Solution :
Babylon had migrated its user-facing applications to a Kubernetes platform in 2018, so the infrastructure team turned to Kubeflow, a toolkit for machine learning on Kubernetes. “We tried to create a Kubernetes core server, we deployed Kubeflow, and we orchestrated the whole experiment, which ended up being a really good success,” says AI Infrastructure Lead Jérémie Vallée. The team began building a self-service AI training platform on top of Kubernetes.
Impact :
Instead of waiting hours or days to be able to compute, teams can get access instantaneously. Clinical validations used to take 10 hours; now they are done in under 20 minutes. The portability of the cloud native platform has also enabled Babylon to expand into other countries.
“ Kubernetes is a great platform for machine learning because it comes with all the scheduling and scalability that you need. ”
CASE STUDY: Booz Allen (Government) - Regulatory Change
The White House launched an IT modernization effort in 2017, and in addition to improving cybersecurity and shifting to the public cloud and a consolidated IT model, “the federal government is looking to provide a better experience to citizens in every way that we interact with the government through every channel,” says Booz Allen Hamilton Senior Lead Technologist Martin Folkoff.
Challenge
In 2017, Booz Allen Hamilton’s Strategic Innovation Group worked with the federal government to relaunch the decade-old recreation.gov website, which provides information and real-time booking for more than 100,000 campsites and facilities on federal lands across the country. The infrastructure needed to be agile, reliable, and scalable — as well as repeatable for the other federal agencies that are among Booz Allen Hamilton’s customers.
Solution
The only way that we thought we could be successful with this problem across all the different agencies is to create a microservice architecture and containers, so that we could be very dynamic and very agile to any given agency for whatever requirements that they may have,” says Booz Allen Hamilton Senior Lead Technologist Martin Folkoff. To meet those requirements, Folkoff’s team looked to Kubernetes for orchestration.
Impact
With the recreation.gov Kubernetes platform, changes can be implemented in about 30 minutes, compared to the multiple hours or even days legacy government applications require to review the code, get approval, and deploy the fix. Recreation.gov deploys to production on average 10 times a day. With monitoring, security, and logging built in, developers can create and publish new services to production within a week. Additionally, Folkoff says, supporting the large, existing monoliths in the government is extremely expensive,” and migrating into a more modern platform has resulted in perhaps 50% cost savings.
