Learn more
Do you need Kubernetes in AWS?

Do you need Kubernetes in AWS?

In the past 10 years, there have been significant advances in cloud computing. Distributed computing is now the preferred computing model, while the client-server model is slowly being phased out. Kubernetes is an open-source platform that enables easy deployment and scaling of containerized applications in the cloud. It has become a very popular solution for businesses around the world. Many reputable companies use Amazon EKS for their apps. These include Amazon.com (obviously), HSBC, GoDaddy, Fidelity Investments, and Snap Inc, among myriad others. This container orchestration technology enables businesses to undertake maintenance and updates of their apps without service interruption. 

What is Kubernetes?

Kubernetes on AWS provides a powerful option for running containerized applications. Kubernetes, usually abbreviated as K8s, is a container orchestration system for the deployment and management of containerized applications. A container is a small virtual machine without device drivers and the standard components of a regular virtual machine. The popularity of containers now threatens to make virtual machines obsolete. 

Imagine you want to install an Nginx web server on a Linux server. You could install it directly on the physical server’s operating system. Another alternative is to use virtual machines. However, setting up a virtual machine is labor-intensive and costly. The virtual machine will be underutilized because it will be dedicated to only one task.

The inventors of containers realized that most applications need minimal resources to run. In the example, you could make a stripped-down version of an operating system and install Nginx inside it to run it. You will therefore have a self-contained unit that can be installed anywhere.

Kubernetes Architecture

A collection of containers is known as a pod. A pod is the smallest unit of execution in Kubernetes and runs on worker nodes. Let's briefly look at the architecture of Kubernetes to understand how Kubernetes operate.

  • Cluster: This is a set of hosts (servers) that helps pull together available resources like CPU, RAM, and disk storage into a usable pool.
  • Master: This is the most vital component of Kubernetes. It manages K8s clusters. The master is made up of components that constitute the control layer of Kubernetes. The components are API Server, Scheduler, Controller Manager, and ETCD. The API server handles all the REST commands that control the cluster. The scheduler, as the name suggests, is responsible for scheduling tasks for the nodes. It stores resource usage information for all nodes and distributes the workload. The controller manager is the single binary that is made from all the controller functions. Lastly, the ETCD is a key-value store for all K8s cluster data.
  • Node: This is a worker machine capable of running containerized applications. The worker nodes are responsible for hosting pods which are the components of the application workload. Nodes can run on either physical or virtual machines. A node is made up of three components: the Kubelet, Kube-proxy, and container runtime. The Kubelet is an agent that ensures that the required containers are running in a K8s pod. The Kube proxy is a network proxy that allows communication and maintains network rules. Container runtime is the program that runs the containers.

Main Kubernetes Features

  1. Automatic Resource Bin Packing: This is a resource management feature of Kubernetes. Kubernetes automatically places containers in bins depending on the required resources with the aim of ensuring uninterrupted availability.
  2. Service discovery: Pods have the same set of functions clustered together and are known as a service. Every pod is assigned an IP address and DNS name, allowing Kubernetes to communicate between pods.
  3. Horizontal scaling: Kubernetes automatically increases or decreases the number of pod replicas serving a job depending on the workload. A controller monitors metrics such as CPU utilization and memory utilization and adjusts the number of pod copies accordingly.
  4. Storage orchestration: Users can mount storage systems of their choice. The storage could be local or public.
  5. Rollout and rollback: No business ever wants to have downtime. However, developers must continue updating the code of their applications. The rollout is the process of updating an application. Through rolling upgrades, Kubernetes incrementally replaces pod instances with new ones with zero downtime. Through rollback, the system can be deployed back to an earlier version. This prevents downtime in case of unexpected failures.
  6. Health check and self-repair: If a containerized app or component goes down, Kubernetes automatically reloads them. Failed containers are automatically restarted while failed nodes are redistributed. Users can also perform health checks. In the case that containers do not respond to user-health checks, Kubernetes will stop the containers.
  7. DevSecOps support: This advanced security approach automates container operations across the cloud. It ensures developers can deliver secure and high-quality apps within shorter time frames.

Why Run Kubernetes in AWS?

Setting up and running Kubernetes in AWS is not a trivial task. However, the benefits of running Kubernetes on AWS far outweigh the challenges. The following are the advantages of running Kubernetes over ECS for example:

  1. Control over servers: Kubernetes in AWS will give you complete control over all your occurrences. 
  2. Portability: Kubernetes can run anywhere, be it public cloud, private cloud, or bare metal servers.
  3. Personal workload protection: If you have portions of a workload that are sensitive, you can run the portion in a private cloud on-premises, while any other work can be run on a public cloud.
  4. Cost efficiency: Through automated scaling, Kubernetes ensures optimum resource optimization. 
  5. Open-source software: Kubernetes is open-source software. Thanks to its large and well-supported community, developers have access to many compatible tools.

Amazon Elastic Kubernetes Service (EKS) is a service that developers can use to run Kubernetes in AWS. This service takes away the heavy lifting of manually configuring EKS to run on AWS. Through this service, developers won't have to operate or maintain the Kubernetes control plane or nodes. Amazon EKS ensures high availability by running and scaling the Kubernetes control plane across a variety of AWS Availability Zones. It automatically spots and replaces unhealthy control plane instances and automatically provides automated version updates. Using the open-source tool eksctl, you can have Kubernetes running in EKS in a matter of minutes.

Here at Finout, we help our customers track the cost of these components, from pods to namespaces. We know that it can get messy out there in a multi-cloud landscape: because Kubernetes can run on any public cloud provider or on-premises system or apply a hybrid approach, it is possible to have different bills from different service providers for your clusters. This is why Finout provides state-of-the-art Kubernetes cost monitoring & observability tools. Want to learn more? Contact Us.

Learn More

7 Ways to Improve Your Cloud ROI

AWS Recommendations for EC2 Cost Reduction

How FinOps can help cyber security vendors rein in cloud costs

Cloud Economics: Cost of Cloud Services Explained

What is FinOps

How to Choose a Payment Option for EC2 Reserved Instances (RIs)

How FinOps takes cloud cost management to the next level

4 Cloud Cost Management Questions that FinOps Answers

Finout's guide to understanding multiple cloud bills complexity

How to Use AWS Cost and Usage (CUR) Report

What is AWS Cost Usage Report (CUR)?

How Unit Economics help SaaS companies optimize their cloud spend

How FinOps helps make sense of cloud spending complexity

Discovering Finout's brand identity

5 Best Practices for Cloud Cost Management on Google Kubernetes Engine

The complete guide for Google Cloud pricing

DynamoDB Pricing: How to Optimize Usage and Reduce Costs

Introduction to Cost Management in Google Cloud

How to Manage Cloud Costs on GCP and GKE

AWS tagging: Why tagging is not enough

AWS tagging: Top 5 Cost Management Challenges

AWS tagging: Why you need it and how to do it

How FinOps Has Changed the Way Businesses Approach Cloud Computing

How Kubernetes Works and Why It’s So Complicated

Why Use Data warehouses in general and Snowflake specifically

We are announcing our $18.5M funding!

A Guide for APM Data Warehouses Tools

How to manage Snowflake costs

Managing DynamoDB Costs with Capacity Modes

Finout's Complete Guide to Kubernetes Cost Spot-Readiness

Join the FinOps Revolution

"Whether you’re a part of a team with an established FinOps practice, or are building up the discipline, everyone can relate to the challenges of mapping cloud utilization cost to their drivers one-to-one." – FinOps Foundation