Significance of Kubernetes and some of its implication in today’s IT Industry….

History

Google introduced the Borg System around 2003–2004. It started off as a small-scale project, with about 3–4 people initially in collaboration with a new version of Google’s new search engine. Borg was a large-scale internal cluster management system, which ran hundreds of thousands of jobs, from many thousands of different applications, across many clusters, each with up to tens of thousands of machines.

Borg was an undisputed competitive advantage of Google because it utilized the machines much better than purely virtualized operations. Google strengthened its market position by being able to provide huge infrastructure landscapes at a much lower cost

In 2013 , following Borg, Google introduced the Omega cluster management system, a flexible, scalable scheduler for large compute clusters.

The big hit for the general public was the idea of making Borg available as an open-source solution. Kubernetes (Greek for helmsman; short: K8 or K8s) was born.In mid 2014 Google introduced Kubernetes as an open source version of Borg.

What is Kubernetes(K8s)?

Kubernetes (also known as k8s or “kube”) is an open source container orchestration platform that automates many of the manual processes involved in deploying, managing, and scaling containerized applications.

The open-source platform Kubernetes orchestrates and automates the setup, operation and scaling of container applications. The architecture allows the containers to be orchestrated across multiple machines, whether they are virtualized hardware or bare metal.

Google generates more than 2 billion container deployments a week, all powered by its internal platform, Borg. Borg was the predecessor to Kubernetes, and the lessons learned from developing Borg over the years became the primary influence behind much of Kubernetes technology.

Kubernetes continuously monitors the state of the applications and ensures that it corresponds to the specified descriptions: For example, if the descriptions specify that three instances should always be executed as web servers, Kubernetes keeps exactly three instances running. If an instance fails or a process crashes, Kubernetes restarts this instance. Even if an entire work process fails or cannot be reached, Kubernetes restarts it from a new node.

Kubernetes is structured according to the so-called master-slave architecture. The master component controls the nodes on which the containers run.

What can you do with Kubernetes?

Kubernetes helps you fully implement and rely on a container-based infrastructure in production environments. And because Kubernetes is all about automation of operational tasks, you can do many of the same things other application platforms or management systems let you do — but for your containers.

With Kubernetes you can:

  • Orchestrate containers across multiple hosts.
  • Make better use of hardware to maximize resources needed to run your enterprise apps.
  • Control and automate application deployments and updates.
  • Mount and add storage to run stateful apps.
  • Scale containerized applications and their resources on the fly.
  • Declaratively manage services, which guarantees the deployed applications are always running the way you intended them to run.
  • Health-check and self-heal your apps with autoplacement, autorestart, autoreplication, and autoscaling.

Some Features of Kubernetes.

The main aim of Kubernetes, as the other orchestration systems, is to simplify the work of technical teams, by automating many processes of applications and services deployment that before were carried out manually. In particular, now we’ll show you Kubernetes features that improve IT field’s work and the benefits for companies who decide to use it.

  • Automates various manual processes: for instance, Kubernetes will control for you which server will host the container, how it will be launched etc.
  • Interacts with several groups of containers: Kubernetes is able to manage more cluster at the same time
  • Provides additional services: as well as the management of containers, Kubernetes offers security, networking and storage services
  • Self-monitoring: Kubernetes checks constantly the health of nodes and containers
  • Horizontal scaling: Kubernetes allows you scaling resources not only vertically but also horizontally, easily and quickly
  • Storage orchestration: Kubernetes mounts and add storage system of your choice to run apps
  • Automates rollouts and rollbacks: if after a change to your application something goes wrong, Kubernetes will rollback for you
  • Container balancing: Kubernetes always knows where to place containers, by calculating the “best location” for them
  • Run everywhere: Kubernetes is an open source tool and gives you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you move workloads to anywhere you want

Why do you need Kubernetes?

Kubernetes can help you deliver and manage containerized, legacy, and cloud-native apps, as well as those being refactored into microservices.

In order to meet changing business needs, your development team needs to be able to rapidly build new applications and services. Cloud-native development starts with microservices in containers, which enables faster development and makes it easier to transform and optimize existing applications.

Kubernetes orchestration allows you to build application services that span multiple containers, schedule those containers across a cluster, scale those containers, and manage the health of those containers over time. With Kubernetes you can take effective steps toward better IT security.

Linux containers give your microservice-based apps an ideal application deployment unit and self-contained execution environment. And microservices in containers make it easier to orchestrate services, including storage, networking, and security.

This significantly multiplies the number of containers in your environment, and as those containers accumulate, the complexity also grows.

Kubernetes fixes a lot of common problems with container proliferation by sorting containers together into “pods.” Pods add a layer of abstraction to grouped containers, which helps you schedule workloads and provide necessary services — like networking and storage — to those containers.

Other parts of Kubernetes help you balance loads across these pods and ensure you have the right number of containers running to support your workloads.

With the right implementation of Kubernetes — and with the help of other open source projects like Open vSwitch, OAuth, and SELinux — you can orchestrate all parts of your container infrastructure.

You should use Kubernetes-

1. If you want to manage your containered applications easily, quickly and efficiently.
2. If you need a HA solution and you can’t suffer downtime in any case.
3. if you have a complex infrastructured, composed by several containers.

Some of the Industrial use cases of Kubernetes

1. Adidas

Challenge is

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 the challenge

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.

After implementing Kubernetes

Just six months after the project began, 100% of the Adidas e-commerce site was running on Kubernetes. Load time for the e-commerce site was reduced by half. Releases went from every 4–6 weeks to 3–4 times a day. With 4,000 pods, 200 nodes, and 80,000 builds per month, Adidas is now running 40% of its most critical, impactful systems on its cloud native platform.

2. Huawei

Challenge is

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 to the challenge

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.

After implementing Kubernetes

“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. “The global deployment cycles decreased from a week to minutes, and the efficiency of application delivery has been improved 10 fold.” For the bottom line, he says, “We also see significant operating expense spending cut, in some circumstances 20–30 percent, which we think is very helpful for our business.” Given the results Huawei has had internally — and the demand it is seeing externally — the company has also built the technologies into FusionStage™, the PaaS solution it offers its customers.

3.ING

Challenge is

After undergoing an agile transformation, ING realized it needed a standardized platform to support the work their developers were doing. “Our DevOps teams got empowered to be autonomous,” says Infrastructure Architect Thijs Ebbers. “It has benefits; you get all kinds of ideas. But a lot of teams are going to devise the same wheel. Teams started tinkering with Docker, Docker Swarm, Kubernetes, Mesos. Well, it’s not really useful for a company to have one hundred wheels, instead of one good wheel.

Solution to the challenge

Using Kubernetes for container orchestration and Docker for containerization, the ING team began building an internal public cloud for its CI/CD pipeline and green-field applications. The pipeline, which has been built on Mesos Marathon, will be migrated onto Kubernetes. The bank-account management app Yolt in the U.K. (and soon France and Italy) market already is live hosted on a Kubernetes framework. At least two greenfield projects currently on the Kubernetes framework will be going into production later this year. By the end of 2018, the company plans to have converted a number of APIs used in the banking customer experience to cloud native APIs and host these on the Kubernetes-based platform.

After implementing Kubernetes

“Cloud native technologies are helping our speed, from getting an application to test to acceptance to production,” says Infrastructure Architect Onno Van der Voort. “If you walk around ING now, you see all these DevOps teams, doing stand-ups, demoing. They try to get new functionality out there really fast. We held a hackathon for one of our existing components and basically converted it to cloud native within 2.5 days, though of course the tail takes more time before code is fully production ready.”

4.NOKIA

Challenge is

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 to the challenge

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.”

After implementing Kubernetes

Kubernetes has enabled Nokia’s foray into 5G. “When you develop something that is part of the operator’s infrastructure, you have to develop it for the future, and Kubernetes and containers are the forward-looking technologies,” says Csatari. The teams using Kubernetes are already seeing clear benefits. “By separating the infrastructure and the application layer, we have less dependencies in the system, which means that it’s easier to implement features in the application layer,” says Csatari. And because teams can test the exact same binary artifact independently of the target execution environment, “we find more errors in early phases of the testing, and we do not need to run the same tests on different target environments, like VMware, OpenStack, or bare metal,” he adds. As a result, “we save several hundred hours in every release.”

5.Bose

Challenge is

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 to the challenge

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. Bose has since adopted a number of other CNCF technologies, including Fluentd, CoreDNS, Jaeger, and OpenTracing.

After implementing Kubernetes

With about 100 engineers onboarded, the platform is now enabling 30,000 non-production deployments across dozens of microservices per year. In 2018, there were 1250+ production deployments. Just one production cluster holds 1,800 namespaces and 340 worker nodes. “We had a brand new service taken from concept through coding and deployment all the way to production, including hardening, security testing and so forth, in less than two and a half weeks,” says O’Mahony.

6.Booking.com

Challenge is

In 2016, Booking.com migrated to an OpenShift platform, which gave product developers faster access to infrastructure. But because Kubernetes was abstracted away from the developers, the infrastructure team became a “knowledge bottleneck” when challenges arose. Trying to scale that support wasn’t sustainable.

Solution to the challenge

After a year operating OpenShift, the platform team decided to build its own vanilla Kubernetes platform — and ask developers to learn some Kubernetes in order to use it. “This is not a magical platform,” says Ben Tyler, Principal Developer, B Platform Track. “We’re not claiming that you can just use it with your eyes closed. Developers need to do some learning, and we’re going to do everything we can to make sure they have access to that knowledge.”

After implementing Kubernetes

Despite the learning curve, there’s been a great uptick in adoption of the new Kubernetes platform. Before containers, creating a new service could take a couple of days if the developers understood Puppet, or weeks if they didn’t. On the new platform, it can take as few as 10 minutes. About 500 new services were built on the platform in the first 8 months.

7. Pinterest

Challenge is

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 to the challenge

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.

After implementing 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. “We not only saw reduced build times but also huge efficiency wins. For instance, the team reclaimed over 80 percent of capacity during non-peak hours. As a result, the Jenkins Kubernetes cluster now uses 30 percent less instance-hours per-day when compared to the previous static cluster.”

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