What is Kubernetes??

What does Kubernetes actually do and why use it?

Kubernetes is a vendor-agnostic cluster and container management tool, open-sourced by Google in 2014. It provides a “platform for automating deployment, scaling, and operations of application containers across clusters of hosts”. Above all, this lowers the cost of cloud computing expenses and simplifies operations and architecture.

This article will explain Kubernetes from a high-level and answer the questions:

• What is Kubernetes and what does it do? Why should people use it?
• What does orchestration mean?
• Why do people use containers?
• Why should IT people care about this, meaning what would they do if they do not use Kubernetes and containers?

Kubernetes and the Need for Containers

Before we explain what Kubernetes does, we need to explain what containers are and why people are using those.

A container is a mini-virtual machine. It is small, as it does not have device drivers and all the other components of a regular virtual machine. Docker is by far the most popular container and it is written in Linux. Microsoft also has added containers to Windows as well, because they have become so popular.

The best way to illustrate why this is useful and important is to give an example.

Suppose you want to install the nginx web server on a Linux server. You have several ways to do that. First, you could install it directly on the physical server’s OS. But most people use virtual machines now, so you would probably install it there.

But setting up a virtual machine requires some administrative effort and cost as well. And machines will be underutilized if you just dedicate it for just one task, which is how people typically use VMs. It would be better to load that one machine up with nginx, messaging software, a DNS server, etc.

The people who invented containers thought through these issues and reasoned that since nginx or any other application just needs some bare minimum operating system to run, then why not make a stripped down version of an OS, put nginx inside, and run that. Then you have a self-contained, machine-agnostic unit that can be installed anywhere.

Now containers are so popular than they threaten to make VMs obsolete, is what some people say.

On the Need for Orchestration

Now, there is an inherent problem with containers, just like there is with virtual machines. That is the need to keep track of them. When public cloud companies bill you for CPU time or storage then you need to make sure you do not have any orphaned machines spinning out there doing nothing. Plus there is the need to automatically spin up more when a machine needs more memory, CPU, or storage, as well as shut them down when the load lightens.

Orchestration tackles these problems. This is where Kubernetes comes in.

Kubernetes

Google built Kubernetes and has been using it for 10 years. That it has been used to run Google’s massive systems for that long is one of its key selling points. Two years ago Google pushed Kubernetes into open source.

Kubernetes is a cluster and container management tool. It lets you deploy containers to clusters, meaning a network of virtual machines. It works with different containers, not just Docker.

Kubernetes Basics

The basic idea of Kubernetes is to further abstract machines, storage, and networks away from their physical implementation. So it is a single interface to deploy containers to all kinds of clouds, virtual machines, and physical machines.

Here are a few of Kubernetes concepts to help understand what it does.

Node

A node is a physical or virtual machine. It is not created by Kubernetes. You create those with a cloud operating system, like OpenStack or Amazon EC2, or manually install them. So you need to lay down your basic infrastructure before you use Kubernetes to deploy your apps. But from that point it can define virtual networks, storage, etc. For example, you could use OpenStack Neutron or Romana to define networks and push those out from Kubernetes.

Pods

A pod is a one or more containers that logically go together. Pods run on nodes. Pods run together as a logical unit. So they have the same shared content. They all share the share IP address but can reach other other via localhost. And they can share storage. But they do not need to all run on the same machine as containers can span more than one machine. One node can run multiple pods.

Pods are cloud-aware. For example you could spin up two Nginx instances and assign them a public IP address on the Google Compute Engine (GCE). To do that you would start the Kubernetes cluster, configure the connection to GCE, and then type something like:

kubectl expose deployment my-nginx –port=80 –type=LoadBalancer

Deployment

A set of pods is a deployment. A deployment ensures that a sufficient number of pods are running at one time to service the app and shuts down those pods that are not needed. It can do this by looking at, for example, CPU utilization.

Use Cases

So why would you use Kubernetes on, for example, Amazon EC2, when it has its own tool for orchestration (CloudFormation)? Because with Kubernetes you can use the same orchestration tool and command-line interfaces for all your different systems. Amazon CloudFormation only works with EC2. So with Kubernetes you could push containers to the Amazon cloud, your in-house virtual and physical machines as well, and other clouds.

OK, so what specifically can Kubernetes do for me?

Here are five fundamental business capabilities that Kubernetes can drive in the enterprise–be it large or small. And to add teeth to these use cases, we have identified some real world examples to validate the value that enterprises are getting from their Kubernetes deployments

1. Faster time to market
2. IT cost optimization
3. Improved scalability and availability
4. Multi-cloud (and hybrid cloud) flexibility
5. Effective migration to the cloud

Let's look at the values in greater detail next.

1. Faster time to market (aka improved app development/deployment efficiencies)

Kubernetes enables a “microservices” approach to building apps. Now you can break up your development team into smaller teams that focus on a single, smaller microservice. These teams are smaller and more agile because each team has a focused function. APIs between these microservices minimize the amount of cross-team communication required to build and deploy. So, ultimately, you can scale multiple small teams of specialized experts who each help support a fleet of thousands of machines.

Kubernetes also allows your IT teams to manage large applications across many containers more efficiently by handling many of the nitty-gritty details of maintaining container-based apps. For example, Kubernetes handles service discovery, helps containers talk to each other, and arranges access to storage from various providers such as AWS and Microsoft Azure.

Real World Case Study

Airbnb’s transition from a monolithic to a microservices architecture is pretty amazing. They needed to scale continuous delivery horizontally, and the goal was to make continuous delivery available to the company’s 1,000 or so engineers so they could add new services. Airbnb adopted Kubernetes to support over 1,000 engineers concurrently configuring and deploying over 250 critical services to Kubernetes. The net result is that AirBnb can now do over 500 deploys per day on average.

Tinder: One of the best examples of accelerating time to market comes from Tinder. This blog post describes Tinder’s K8 journey well. And here’s the cliff notes version of the story: Due to high traffic volume, Tinder’s engineering team faced challenges of scale and stability. And they realized that the answer to their struggle is Kubernetes. Tinder’s engineering team migrated 200 services and ran a Kubernetes cluster of 1,000 nodes, 15,000 pods, and 48,000 running containers. While the migration process wasn't easy, the Kubernetes solution was critical to ensure smooth business operations going further.

2. IT cost optimization

Kubernetes can help your business cut infrastructure costs quite drastically if you’re operating at massive scale. Kubernetes makes a container-based architecture feasible by packing together apps optimally using your cloud and hardware investments. Before Kubernetes, administrators often over-provisioned their infrastructure to conservatively handle unexpected spikes, or simply because it was difficult and time consuming to manually scale containerized applications. Kubenetes intelligently schedules and tightly packs containers, taking into account the available resources. It also automatically scales your application to meet business needs, thus freeing up human resources to focus on other productive tasks.

There are many examples of customers who have seen dramatic improvements in cost optimization using K8s.

Real World Case Study

Spotify is an early K8s adopter and has significant cost saving values by adopting K8s. Leveraging K8s, Spotify has seen 2-3x CPU utilization using the orchestration capabilities of K8s, resulting in better IT spend optimization.

Pinterest is another early K8s customer. Leveraging K8s, the Pinterest IT team reclaimed over 80 percent of capacity during non-peak hours. They now use30 percent less instance-hours per day compared to the static cluster.

3. Improved scalability and availability

The success of today’s applications does not depend only on features, but also on the scalability of the application. After all, if an application cannot scale well, it will be highly non-performant at best scale, and totally unavailable, at the worst case.

As an orchestration system, Kubernetes is a critical management system to “auto-magically” scale and improve app performance. Suppose we have a service which is CPU-intensive and with dynamic user load that changes based on business conditions (for example, an event ticketing app that will see dramatic users and loads prior to the event and low usage at other times). What we need here is a solution that can scale up the app and its infrastructure so that new machines are automatically spawned up as the load increases (more users are buying tickets) and scale it down when the load subsides. Kubernetes offers just that capability by scaling up the application as the CPU usage goes above a defined threshold - for example, 90 percent on the current machine. And when the load reduces, Kubernetes can scale back the application, thus optimizing the infrastructure utilization. The Kubernetes auto-scaling is not limited to just infrastructure metrics; any type of metric--resource utilization metrics - even custom metrics can be used to trigger the scaling process.

Real World Case Study

LendingTree: Here’s a great article from LendingTree. LendingTree has many microservices that make up its business apps. LendingTree uses Kubernetes and its horizontal scaling capability to deploy and run these services, and to ensure that their customers have access to service even during peak load. And to get visibility into these containerized and virtual services and monitor its Kubernetes deployment, LendingTree uses Sumo Logic

4. Multi-cloud flexibility

One of the biggest benefits of Kubernetes and containers is that it helps you realize the promise of hybrid and multi-cloud. Enterprises today are already running multi-cloud environments and will continue to do so in the future. Kubernetes makes it much easier is to run any app on any public cloud service or any combination of public and private clouds. This allows you to put the right workloads on the right cloud and to help you avoid vendor lock-in. And getting the best fit, using the right features, and having the leverage to migrate when it makes sense all help you realize more ROI (short and longer term) from your IT investments.

Need more data to validate the multi-cloud and Kubernetes made-in-heaven story? This finding from the Sumo Logic Continuous Intelligence Report identifies a very interesting upward trend on K8 adoption based on the number of cloud platforms organizations use, with 86 percent of customers on all three using managed or native Kubernetes solutions. Should AWS be worried? Probably not. But, it may be an early sign of a level playing field for Azure and GCP--because apps deployed on K8s can be easily ported across environments (on-premise to cloud or across clouds).

Thank You!!!

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