Use cases solved by Kubernetes in Industries
ARTH - Task 16
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.
Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Wouldn’t it be easier if this behavior was handled by a system?
That’s how Kubernetes comes to the rescue! Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of scaling and failover for your application, provides deployment patterns, and more. For example, Kubernetes can easily manage a canary deployment for your system.
Source: What is Kubernetes? | Kubernetes
Market Share?
Companies — Challenge faced — Solution Provided by Kubernetes
Challenge :
Launched in 2008, the audio-streaming platform has grown to over 200 million monthly active users across the world. 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. By late 2017, it became clear that “having a small team working on the features was just not as efficient as adopting something that was supported by a much bigger community,” says Jai Chakrabarti, Director of Engineering, Infrastructure and Operations.
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.” “Kubernetes fit very nicely as a complement and now as a replacement to Helios,” says Chakrabarti.
Challenge :
After eight years in existence, Pinterest had grown into 1,000 microservices and multiple layers of infrastructure and diverse set-up tools and platforms. In 2016 the company launched a roadmap towards a new compute platform, led by the vision of creating the fastest path from an idea to production, without making engineers worry about the underlying infrastructure.
Solution :
The first phase involved moving services to Docker containers. Once these services went into production in early 2017, the team began looking at orchestration to help create efficiencies and manage them in a decentralized way. After an evaluation of various solutions, Pinterest went with Kubernetes.”By moving to Kubernetes the team was able to build on-demand scaling and new failover policies, in addition to simplifying the overall deployment and management of a complicated piece of infrastructure such as Jenkins,” says Micheal Benedict, Product Manager for the Cloud and the Data Infrastructure Group at Pinterest.
Challenge :
A global education company serving 75 million learners, Pearson set a goal to more than double that number, to 200 million, by 2025. A key part of this growth is in digital learning experiences, and Pearson was having difficulty in scaling and adapting to its growing online audience. They needed an infrastructure platform that would be able to scale quickly and deliver products to market faster.
Solution :
“To transform our infrastructure, we had to think beyond simply enabling automated provisioning,” says Chris Jackson, Director for Cloud Platforms & SRE at Pearson. “We realized we had to build a platform that would allow Pearson developers to build, manage and deploy applications in a completely different way.” The team chose Docker container technology and Kubernetes orchestration “because of its flexibility, ease of management and the way it would improve our engineers’ productivity.”
Challenge :
IBM cloud offers public, private, and hybrid cloud functionality across a diverse set of runtimes from its OpenWhisk-based function as a service (FaaS) offering, managed Kubernetes and containers, to Cloud Foundry platform as a service (PaaS). These runtimes are combined with the power of the company’s enterprise technologies, such as MQ and DB2, its modern artificial intelligence (AI) Watson, and data analytics services. Users of IBM Cloud can exploit capabilities from more than 170 different cloud native services in its catalog, including capabilities such as IBM’s Weather Company API and data services. In the later part of 2017, the IBM Cloud Container Registry team wanted to build out an image trust service.
Solution :
IBM’s intention in offering a managed Kubernetes container service and image registry is to provide a fully secure end-to-end platform for its enterprise customers. The work on this new service culminated with its public availability in the IBM Cloud in February 2018.Users can create image security policies for each Kubernetes namespace, or at the cluster level, and enforce different levels of trust for different images. Portieris is a key part of IBM’s trust story, since it makes it possible for users to consume the company’s Notary offering from within their IKS clusters. The offering is that Notary server runs in IBM’s cloud, and then Portieris runs inside the IKS cluster. This enables users to be able to have their IKS cluster verify that the image they’re loading containers from contains exactly what they expect it to, and Portieris is what allows an IKS cluster to apply that verification.
Challenge :
Nokia’s core business is building telecom networks end-to-end; its main products are related to the infrastructure, such as antennas, switching equipment, and routing equipment. “As telecom vendors, we have to deliver our software to several telecom operators and put the software into their infrastructure, and each of the operators have a bit different infrastructure,” says Gergely Csatari, Senior Open Source Engineer. “There are operators who are running on bare metal. There are operators who are running on virtual machines. There are operators who are running on VMWare Cloud and OpenStack Cloud. We want to run the same product on all of these different infrastructures without changing the product itself.”
Solution :
The company decided that moving to cloud native technologies would allow teams to have infrastructure-agnostic behavior in their products. Teams at Nokia began experimenting with Kubernetes in pre-1.0 versions. “The simplicity of the label-based scheduling of Kubernetes was a sign that showed us this architecture will scale, will be stable, and will be good for our purposes,” says Csatari. The first Kubernetes-based product, the Nokia Telephony Application Server, went live in early 2018. “Now, all the products are doing some kind of re-architecture work, and they’re moving to Kubernetes.”
Challenge :
A multinational company that’s the largest telecommunications equipment manufacturer in the world, Huawei has more than 180,000 employees. In order to support its fast business development around the globe, Huawei has eight data centers for its internal I.T. department, which have been running 800+ applications in 100K+ VMs to serve these 180,000 users. With the rapid increase of new applications, the cost and efficiency of management and deployment of VM-based apps all became critical challenges for business agility. “It’s very much a distributed system so we found that managing all of the tasks in a more consistent way is always a challenge,” says Peixin Hou, the company’s Chief Software Architect and Community Director for Open Source. “We wanted to move into a more agile and decent practice.”
Solution :
After deciding to use container technology, Huawei began moving the internal I.T. department’s applications to run on Kubernetes. So far, about 30 percent of these applications have been transferred to cloud native. “By the end of 2016, Huawei’s internal I.T. department managed more than 4,000 nodes with tens of thousands containers using a Kubernetes-based Platform as a Service (PaaS) solution,” says Hou.
Challenge :
In recent years, the adidas team was happy with its software choices from a technology perspective — but accessing all of the tools was a problem. For instance, “just to get a developer VM, you had to send a request form, give the purpose, give the title of the project, who’s responsible, give the internal cost center a call so that they can do recharges,” says Daniel Eichten, Senior Director of Platform Engineering. “The best case is you got your machine in half an hour. Worst case is half a week or sometimes even a week.”
Solution :
To improve the process, “we started from the developer point of view,” and looked for ways to shorten the time it took to get a project up and running and into the adidas infrastructure, says Senior Director of Platform Engineering Fernando Cornago. They found the solution with containerization, agile development, continuous delivery, and a cloud native platform that includes Kubernetes and Prometheus.
Challenge :
A household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it. “We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast,” says Lead Cloud Engineer Josh West. In 2016, the company decided to start building a platform from scratch. The primary goal: “To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony.
Solution :
From the beginning, the team knew it wanted a microservices architecture. After evaluating and prototyping a couple of orchestration solutions, the team decided to adopt Kubernetes for its scaled IoT Platform-as-a-Service running on AWS. The platform, which also incorporated Prometheus monitoring, launched in production in 2017, serving over 3 million connected products from the get-go. With about 100 engineers onboarded, the platform is now enabling 30,000 non-production deployments across dozens of microservices per year.
Source: Case Studies | Kubernetes
