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. Kubernetes was originally developed and designed by engineers at Google.
Kubernetes clusters can span hosts across on-premise, public, private, or hybrid clouds. For this reason, Kubernetes is an ideal platform for hosting cloud-native applications that require rapid scaling.
Red Hat was one of the first companies to work with Google on Kubernetes.
Going back in time(Evolution of Deployment)
Let’s take a look at why Kubernetes is so useful by going back in time.
Traditional deployment era: Early on, organizations ran applications on physical servers.
Problem of Traditional deployment :If multiple applications run on a physical server, there can be instances where one application would take up most of the resources, and as a result, the other applications would underperform. There was no way to define resource boundaries for applications in a physical server, and this caused resource allocation issues.
Solution for the above issue but not feasible: A solution for this would be to run each application on a different physical server. But this did not scale as resources were underutilized, and it was expensive for organizations to maintain many physical servers.
As a solution, Virtualized deployment came into picture.
Virtualized deployment era: It allows you to run multiple Virtual Machines (VMs) on a single physical server’s CPU. Virtualization allows applications to be isolated between VMs and provides a level of security as the information of one application cannot be freely accessed by another application.
Virtualization allows better utilization of resources in a physical server and allows better scalability because an application can be added or updated easily, reduces hardware costs, and much more. With virtualization you can present a set of physical resources as a cluster of disposable virtual machines.
Each VM is a full machine running all the components, including its own operating system, on top of the virtualized hardware.
Container deployment era: Containers are similar to VMs but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, share of CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions.
Why Container become popular?
Containers have become popular because they provide extra benefits, such as:
- Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
- Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and easy rollbacks (due to image immutability).
- Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
- Observability not only surfaces OS-level information and metrics, but also application health and other signals.
- Environmental consistency across development, testing, and production: Runs the same on a laptop as it does in the cloud.
- Cloud and OS distribution portability: Runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and anywhere else.
- Application-centric management: Raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources.
- Loosely coupled, distributed, elastic, liberated micro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically
- Resource isolation: predictable application performance.
- Resource utilization: high efficiency and density.
Why you need Kubernetes and what it can do?
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. It takes care of scaling and failover for your application, provides deployment patterns, and more.
###What Kubernetes provides us?
- Service discovery and load balancing Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable.
- Storage orchestration Kubernetes allows you to automatically mount a storage system of your choice, such as local storages, public cloud providers, and more.
- Automated rollouts and rollbacks You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate.
- Automatic bin packing :You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to make the best use of your resources.
- Self-healing Kubernetes restarts containers that fail, replaces containers, kills containers that don’t respond .
- Secret and configuration management :You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration.
How big companies are using Kubernetes?
Kubernetes’ increased adoption is showcased by a number of influential companies which have integrated the technology into their services.
Let’s take an case studies of one of the company named Babylon Health.
Babylon Health is a health service provider that provides remote consultations with doctors and health care professionals via text and video messaging through its mobile application.
This service also allows users to receive referrals to health specialists, have drug prescriptions mailed to the user or sent to a pharmacy or to consult with therapists to discuss topics such as depression and anxiety.
In addition to the direct healthcare services, users can access various health monitoring tools such as an activity tracker, ordering home blood-test kits and reviewing general lifestyle and fitness questions.
Why Babylon Health need Kubernetes?
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. 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.”
— JÉRÉMIE VALLÉE, AI INFRASTRUCTURE LEAD AT BABYLON
Kubernetes was an enabler on every count. “Kubernetes is a great platform for machine learning because it comes with all the scheduling and scalability that you need,” says Vallée. The need to keep data in every country in which Babylon operates requires a multi-region, multi-cloud strategy, and some countries might not even have a public cloud provider at all.
“We wanted to make this platform portable so that we can run training jobs anywhere,” he says. “Kubernetes offered a base layer that allows you to deploy the platform outside of the cloud provider, and then deploy whatever tooling you need. That was a very good selling point for us.”
“Giving a Kubernetes-based platform to our data scientists has meant increased security, increased innovation through empowerment, and a more affordable health service as our cloud engineers are building an experience that is used by hundreds on a daily basis, rather than supporting specific bespoke use cases.”
— JEAN MARIE FERDEGUE, DIRECTOR OF PLATFORM OPERATIONS AT BABYLON
Thank You