Kubernetes on AWS proposes one of the most effective distributed computing platforms. Nowadays, the internet has reached everyone in the world. On the Internet, you can access websites. Then, these websites show their content to you. This content is stored on the central server or a vendor server. The internet browser sends a request to the server, and that server responds by displaying the data.
But these requests have limited processing capacity. Above the capacity line, the server can not process those requests simultaneously. It starts the subsequent requests after that one running request. Server processing power, accessing memory, and storage resources determine the demand-receiving capacity of the server. Web developers use Kubernetes to scale servers, especially for big servers like AWS, Google, Netflix, etc.
In this article, we will learn about Kubernetes on AWS, and how Kubernetes is contributing to AWS. So, let’s get the ball rolling.
What is AWS?
Amazon Web Service, referred to as AWS, is a broadly adopted cloud platform to the world. It is made of different servers and cloud computing. It provides remote computing, online storage, networking, servers, etc. It is a large company,y and it has three main offerings. S3, Glacier, and EC2.
EC2 provides Amazon virtual machine service, S3 is an Amazon storage system, and Glacier provides cloud storage services. It offers more than 200 featured service centers globally. Large enterprises, governments, website organizations, and millions of web customers are using AWS. AWS is popular because of its fast innovation, cost-effectiveness, and agility. It also offers flexible and secure cloud computing with security compliance.
What is Kubernetes
We all know that web apps are built on a little group of containers that contain all kinds of information and code to run those apps. Kubernetes work as a platform to manage these containers for their proper function. Google was the first one to use Kubernetes. It is also known as Kube or K8.
Simply, the symbol of Kubernetes explains everything. The symbol of Kubernetes is the steering of a ship. The steering drives the ship on the right path to avoid any kind of collision. The Kubernetes also steer the containers. Kubernetes autoscaling steers the containers to maintain their scalability and flexibility.
Why should we use Kubernetes on AWS?
AWS provides more services and features than a few other cloud providers. That is why most high-profile websites are eager to set their data on AWS. High-profile websites will have many users. For example, Netflix is using the AWS server as a cloud vendor. We all know that Netflix has massive users of its popularity.
When Netflix releases a new web series that fans are waiting for so long. And so,
- The log-in number of users will drastically increase at the release moment.
- Huge access will create a sudden load on the cloud servers.
To tackle this kind of situation, Kubernetes is necessary for AWS. There are also more reasons to use Kubernetes on AWS such as
- Kubernetes scale the resources to low when the access number is low. When the number is high, Kubernetes scale the resource to high. This saves resource power costs.
- Kubernetes makes the development and releasing point easier. It optimizes resource management and put them in automation for short time frames.
- Kubernetes accelerate the process of migrating apps from one environment to another. You can also use the re-platforming method.
- Kubernetes allows the IT sector to enjoy Hybrid and multi-cloud platforms. This allows an organization to boost performance and prepare for potential and unexpected challenges.
Situation Before Kubernetes
In the past days before Kubernetes, developers simply build and deploy. There were two ways to do so. One is the traditional way where developers push the codes to the physical server of a data center. Another one is deploying code in the virtual machine. Let’s look at these two types of deployments.
Conventional System
When you are going to run the application on multiple resources, the setup and configuration of that server may not provide consistency. Here the codes are directly going into the physical server. So
- The codes will not work properly in the up and downtime of a server and will show errors in the infrastructure.
- These errors can be about resource allocation, load balancing, request loading, etc.
- As you are putting one app into a server, you are not able to fully utilize the hardware consistently.
- This increases the overall cost for that organization.
Virtual System
The virtual system overcomes the problems of the conventional system. It allows multiple virtual machines or VMs to run on a single piece of hardware. It was providing flexibility and scalability at a lower cost. But this virtual machine is not perfect either.
- You have to use another machine to run and manage the VMs.
- This increases implementation costs.
- There were security risks with VMs. Not every server and app can run in a virtual environment.
- Setting up a virtualized environment is time-consuming.
- It is uncertain that your app will get the available resources free on hardware.
After Kubernetes
After the invention of Kubernetes, conventional and virtual machine systems were facing more issues. And Kubernetes is built for managing only containerized apps. It allows you to deploy codes into the data center and then deploy solutions like a virtual machine, the container and Kubernetes is the next level evolution. Also, Kubernetes is portable and it takes less time to set up.
Final Verdict
AWS as an Amazon web service is a cloud-based platform. And a cloud-based platform will definitely have uptime and downtime. But this actually hampers the user’s experience. It is also harmful to cloud marketing.
Kubernetes scale the resources in such a way that, it scales the space high in server downtime and scales the space down in server uptime. If the space always remains the same, the space remains unutilized and you are paying extra money. So, Kubernetes always opens an option for the server. So, It is important to use Kubernetes on AWS.
