Overview

In the past few weeks I have seen a overwhelming amount of people explaing their struggles with Amazon EKS, I have decided to create this repository to do my best to breakdown some of the more mandatory skill aspects of EKS. Amazon EKS is by no means a easy service to use that you can just learn over night, having heavily been involved with EKS for the last few years of my life. I dived straigt into EKS when I was only 15. I have experienced more struggles and obstacles than I can even remember. That being said I want to do my best to help the community in anyway I can considering that were all apart of this together after all.

Section 1: EKS Breakdown

Section 2: EKS Roadmap

Section 1 EKS Breakdown:

Complexity

Amazon EKS is a complex system, and users need to have a good understanding of Kubernetes and its associated concepts to use it effectively. I will be breaking down all of the main concepts that I feel are the most important being Helm, Pods, Kube ctl, Kube-proxy, Kubernetes API, Control plane, Worker nodes, Kubernets objects, Kubernetes controllers, Kubernetes namespace, Kubernetes labels, Kubernetes networking, Kubernetes storage, Kubernetes security. We will do a deep dive into all of them later but for now we are just going to give a summary of each component.

Helm: "Helm is the package manager for Kubernetes. Helm is the best way to find, share, and use software built for Kubernetes. Helm and Kubernetes work like a client/server application. The Helm client pushes resources to the Kubernetes cluster via kubernetes API." you can either use pre-built helm charts or take time to create your own for more specific needs.

Pods: A pod is the smallest deployable unit in the Kubernetes system. A pod represents a single instance of a running process in a cluster, and it encapsulates one or more containers that share the same network namespace and storage volumes. Pods are the basic building blocks of a Kubernetes application, and they provide a convenient way to package, deploy, and manage containerized applications. Pods can be created and managed using the Kubernetes API, and they can be automatically scheduled and scaled by the Kubernetes control plane.

Kube ctl: Kubectl is a command-line tool used for managing Kubernetes clusters, including those running on Amazon Elastic Kubernetes Service (EKS). It is the primary interface for interacting with Kubernetes clusters and allows developers and administrators to deploy, inspect, and manage containerized applications running on a Kubernetes cluster. Think of it like a remote controller for your Kubernetes clusters.

Kube-proxy: Kube-proxy is a network proxy and load balancer that runs on each worker node in a Kubernetes cluster. It is responsible for managing network traffic between Kubernetes services and their associated pods. Kube-proxy uses the Kubernetes API to monitor the state of the cluster, including the creation and deletion of pods and services. It then updates the IP tables on the worker nodes to ensure that traffic is correctly routed to the appropriate pods and services. I find this to be one of the more helpful tools as it pertains to Kubernetes, also one of the tools I use the most.

Kubernetes API: The Kubernetes API is a RESTful API that exposes the functionality of a Kubernetes cluster. It is the primary interface for interacting with a Kubernetes cluster and is used by developers and administrators to manage and deploy containerized applications. The Kubernetes API provides a declarative model for specifying the desired state of a Kubernetes cluster and allows users to manipulate the state of the cluster by creating, updating, and deleting Kubernetes objects such as pods, services, deployments, and replica sets.

Control plane: The control plane is the set of components that manage the Kubernetes cluster. These components include the Kubernetes API server, etcd (a distributed key-value store for storing cluster state), the Kubernetes controller manager, and the Kubernetes scheduler.

Worker nodes: Worker nodes are instances that run your containerized applications and services. These nodes are responsible for running the Kubernetes pod and container tasks that make up your application. When you create an Amazon EKS cluster, you define the desired number of worker nodes, their instance type, and the Amazon Machine Image (AMI) to use for provisioning.

Kubernetes Objects: Kubernetes objects are the fundamental building blocks used to define, configure, and manage applications and services deployed on the Kubernetes cluster. Exmaplas include: Pods, Deployments, Services, ConfigMaps, Secrets, and Statefulsets.

Kubernetes controllers: Kubernetes controllers are components that are responsible for managing the state of Kubernetes objects, ensuring that the desired state is maintained and automatically correcting any deviations from that state. There are many diffrent types of Kubernetes controllers, so you will have to identify your needs before making any rash decisions.

Kubernetes namespace: Kubernetes namespace is a way to create a virtual cluster inside a Kubernetes cluster. A namespace provides a way to logically partition resources and create a virtual cluster, which helps to manage and organize resources within the cluster.

Kubernetes labels: Kubernetes labels are key-value pairs that are used to organize and categorize resources within a Kubernetes cluster. Labels are metadata that can be attached to Kubernetes objects such as pods, services, and deployments, allowing you to easily select and manage related resources.

Kubernets networking: Kubernetes networking refers to the set of mechanisms used to enable communication between the various components of a Kubernetes cluster. Kubernetes networking allows pods to communicate with each other and with other services in the cluster, and enables load balancing and traffic management for those services. Kubernetes networking in Amazon EKS is built on top of the Kubernetes networking model.

Kubernetes storage: Kubernetes storage refers to the mechanisms used to provide persistent storage to containerized applications running in a Kubernetes cluster. Kubernetes storage allows for the persistent storage of data even if a pod or container is restarted, rescheduled, or terminated.

Kubernetes security: Kubernetes security refers to the set of mechanisms used to secure the various components of a Kubernetes cluster, including the control plane, worker nodes, and applications running in the cluster.

Setup

Setting up Amazon EKS can be a difficult and time-consuming process, requiring expertise in infrastructure and networking. Setting up a effective EKS environment involves everal steps, including configuring the cluster, setting up networking and security, and deploying applications there are multiple steps to ensure proper setip of your EKS environment.

Planning the architecture: Before setting up the cluster, it's important to plan the overall architecture of your application, including the number of nodes, the types of workloads, and the required networking and storage configurations. This way you can ensure that everything works cohesively and it makes it alot easier to take the proper steps in launching your EKS deployment.

Creating the cluster/clusters: You can create an Amazon EKS cluster using the AWS Management Console, AWS CLI, or AWS CloudFormation. It's important to configure the cluster with the appropriate settings, including the Kubernetes version, networking, and security policies. Everything does not have to be flawless on this end at first, but it acts as a good base to have a cluster to build around.

Setup Networking: Amazon EKS supports a variety of networking solutions, including the Amazon VPC CNI, Calico, and Weave Net. It's important to choose a networking solution that meets your requirements and configure it appropriately. Typically you should have no trouble finding what suit your needs, I usually just refer to the AWS documentation.

Configure security: Kubernetes security in Amazon EKS involves securing the control plane, worker nodes, and applications running in the cluster. This can involve configuring RBAC, network policies, container security features, logging and monitoring, and compliance and governance frameworks. There will be a separate section for security later on for a deeper dive into it.

Deploy applications: Once the cluster is set up, you can deploy applications using Kubernetes manifests or Helm charts. It's important to configure the appropriate resources, such as pods, services, and persistent volumes, and to test the application thoroughly to ensure it meets your requirements.

Monitor and optimize: It's important to monitor the performance of your Amazon EKS environment and optimize it as needed to ensure optimal resource utilization and cost-effectiveness. This can involve using tools like AWS CloudWatch and Kubernetes Dashboard to track resource usage and identify opportunities for optimization. In a way this category can also fall under the same page as secuity, but it's still important to monitor your application at all times do to things like compute or storage failures or even the fact that AWS could update there services and you can find a better way to optimize performance.

Cost

The cost of using Amazon EKS (Elastic Kubernetes Service) can vary based on a number of factors, such as the size of the cluster, the number of nodes, the storage and networking requirements, and the region where the cluster is deployed.

There are two main components to the cost of using EKS: the cost of the EKS control plane and the cost of the worker nodes. The control plane manages the Kubernetes master nodes and is charged at an hourly rate based on the region. The worker nodes are EC2 instances that run your application workloads and are charged based on the instance type, the number of nodes, and the usage time.

In addition to these costs, you may also incur charges for other services that you use in conjunction with EKS, such as Elastic Load Balancers, Elastic Block Storage volumes, and other AWS services.

Scalability

The scalability on EKS typically comes down to the way you want to scale and how fast and cost effectively you want to do it. I've worked closely with five different types that I use on a weekly basis.

Horizontal Pod Autoscaling: EKS supports Kubernetes' Horizontal Pod Autoscaler (HPA), which automatically scales the number of pods in a deployment based on CPU utilization or other metrics. By setting up an HPA, you can ensure that your application can handle varying levels of traffic.

Cluster Autoscaling: EKS also supports Cluster Autoscaler, which automatically adjusts the number of worker nodes in the cluster based on the demand for resources. This is particularly useful when you have unpredictable traffic patterns, and you don't want to overprovision your cluster.

Manual Scaling: You can also manually scale your cluster by adding or removing worker nodes. This can be done through the EKS console, AWS CLI, or SDKs. Manual scaling is useful when you want more fine-grained control over your cluster's capacity.

Spot Instances: EKS also supports using Spot instances, which are spare EC2 instances that are available at a lower cost than On-Demand instances. You can use Spot instances to scale your cluster and save costs, but you need to be prepared for the possibility of instances being terminated with short notice.

Node Groups: Node Groups are a way to group worker nodes with similar characteristics, such as instance type or storage configuration. By using Node Groups, you can have more control over the scaling of specific subsets of your cluster.

Security

Securing your Amazon EKS environment is essential for protecting sensitive data, ensuring business continuity, meeting compliance requirements, and mitigating cyber threats. By implementing a comprehensive security strategy, you can help ensure the safety and reliability of your EKS environment. Here are some of the best practices that I use for securing my environments.

Secure the EKS Control Plane: The EKS control plane manages the Kubernetes master nodes, and it's critical to secure it to prevent unauthorized access. You can secure the control plane by using AWS Identity and Access Management (IAM) to manage access to EKS resources and by enabling encryption for communication between the control plane and worker nodes.

Secure Worker Nodes: You should secure your worker nodes by ensuring that only authorized users and services can access them. You can use IAM roles to grant access to worker nodes, and you can also use AWS security groups and network ACLs to restrict inbound and outbound traffic to your worker nodes.

Secure Kubernetes API Server: The Kubernetes API server exposes an HTTP API that enables users to interact with the cluster. You should secure the API server by using Transport Layer Security (TLS) encryption and by restricting access to authorized users.

Use Network Security Best Practices: You should implement network security best practices such as using a Virtual Private Cloud (VPC) to isolate your EKS cluster from the public internet, using AWS security groups to control inbound and outbound traffic, and using VPC flow logs to monitor network traffic.

Implement Security Policies: You should implement security policies such as limiting the use of privileged containers, using pod security policies to enforce security requirements for pods, and enabling auditing to monitor activity within the cluster.

Use AWS Security Services: AWS provides a number of security services that can help you secure your EKS cluster, such as AWS Security Hub, AWS CloudTrail, and AWS Config. You should use these services to monitor your cluster for security events, detect and respond to security threats, and maintain compliance with security standards.

Networking

Networking can be a complicated part of Amazon EKS, and users need to have a good understanding of Kubernetes networking concepts to configure it correctly. It is always best to break the concepts down separately.

To start off with the concepts I am sure whoever is reading this is already familiar with the bascic types of networking. Things like VPC's, Subnets, Scurity groups, and Load balancing shouldn't have to be explained, so I will just stick with the core 3 networking type that pertain to EKS.

Kube-proxy: kube-proxy is a Kubernetes networking component that runs on each worker node in the cluster. Its primary function is to provide a network proxy and load balancer for Kubernetes services running on the worker nodes.

kube-proxy works by setting up a set of network rules on the worker node's operating system to forward incoming traffic to the appropriate pod in the cluster. It also manages the virtual IP address (VIP) assigned to the service, which allows clients to connect to the service without needing to know the IP addresses of the individual pods.

kube-proxy operates in three different modes:

User space mode: In this mode, kube-proxy runs as a userspace daemon on the worker node, and it uses iptables rules to forward traffic to the appropriate pod. This mode is less performant than other modes, but it can be used in environments where the kernel does not support the other modes.
IPVS mode: In this mode, kube-proxy uses the Linux kernel's IPVS (IP Virtual Server) module to perform load balancing and service proxying. This mode is highly performant and scalable and is the recommended mode for EKS clusters running on Linux worker nodes.
IPTables mode: In this mode, kube-proxy uses iptables rules to forward traffic to the appropriate pod. This mode is similar to user space mode, but it uses a more efficient implementation of iptables.

Kube-dns service: kube-dns is a Kubernetes add-on service that provides name resolution for Kubernetes services using DNS. It is responsible for mapping Kubernetes service names to their corresponding IP addresses, which enables clients to connect to services using their names rather than their IP addresses.

kube-dns is composed of two components: a DNS server and a DNS agent. The DNS server is responsible for serving DNS requests for the Kubernetes cluster, while the DNS agent runs as a pod on each worker node in the cluster and watches for changes to the Kubernetes service and pod configurations.

When a Kubernetes service is created, kube-dns creates a DNS record for the service name in the cluster's DNS namespace. This record maps the service name to a cluster IP address assigned to the service. When a client sends a DNS query for the service name, the DNS server returns the IP address of one of the pods associated with the service. This enables clients to connect to the service without needing to know the IP addresses of individual pods.

kube-dns is an essential component of the Kubernetes networking stack in EKS and plays a critical role in ensuring that services are accessible and discoverable within the cluster.

Container networking: Container networking refers to the networking model used by Kubernetes to facilitate communication between containers running on different worker nodes within the cluster. Container networking is a crucial aspect of EKS since it enables Kubernetes to schedule and manage containers in a highly distributed and scalable manner. Container networking in EKS is implemented using a Container Network Interface (CNI) plugin. A CNI plugin is responsible for configuring the networking environment for containers running on a worker node. The CNI plugin creates network namespaces and virtual network interfaces for containers and sets up rules in the kernel's networking stack to enable communication between them.

Monitoring

Monitoring and logging are essential parts of operating any Kubernetes cluster, and this can be challenging in Amazon EKS. EKS provides several monitoring capabilities to help you observe the health of your Kubernetes cluster and applications running on it.

Metrics: EKS provides a set of pre-configured metrics that you can use to monitor your cluster, such as CPU and memory utilization, network traffic, and disk usage. These metrics can be viewed using Amazon CloudWatch.

Logging: EKS supports logging of Kubernetes API server events, container logs, and node logs. These logs can be viewed using various tools, such as Amazon CloudWatch Logs and Elasticsearch.

Tracing: EKS integrates with AWS X-Ray to enable tracing of requests through applications running on the cluster. This can help you identify performance issues and troubleshoot errors.

Kubernetes Dashboard: EKS includes a Kubernetes Dashboard that provides a graphical user interface for monitoring and managing your cluster. The dashboard displays real-time information about your cluster, such as resource utilization and the status of Kubernetes objects.

Prometheus: EKS supports Prometheus, a popular open-source monitoring system for Kubernetes. With Prometheus, you can collect custom metrics and perform more advanced monitoring and analysis.

Maintenance

Maintenance can be a time-consuming process, and users need to keep their cluster up-to-date with the latest patches and upgrades. Maintenance in Amazon EKS involves several key concepts, including:

Cluster upgrades: Amazon EKS automatically manages the upgrade process for the Kubernetes control plane and worker nodes, ensuring that the cluster stays up-to-date with the latest security patches and features.

Node maintenance: Amazon EKS provides tools to manage node maintenance, including the ability to drain nodes before performing maintenance tasks, such as patching or updating node software.

Scaling: Amazon EKS makes it easy to scale worker nodes up or down based on demand, using the AWS Auto Scaling feature. Monitoring: Amazon EKS provides built-in monitoring capabilities, including integration with AWS CloudWatch and the ability to view cluster and node-level metrics.

Logging: Amazon EKS provides built-in logging capabilities, including integration with AWS CloudTrail and the ability to view logs for Kubernetes components, applications, and containers.

High availability: Amazon EKS is designed to be highly available, with automatic failover for the Kubernetes control plane and worker nodes.

Security: Amazon EKS provides several security features, including network isolation, encryption in transit and at rest, and integration with AWS Identity and Access Management (IAM) for authentication and authorization.

Integration

Integrating Amazon EKS with other services can be complicated, and users need to have a good understanding of the integration process. There are some that you should definitely focus on more than others though like:

Kubernetes API server: Amazon EKS integrates with the Kubernetes API server, providing a managed control plane for Kubernetes clusters. This allows users to manage their clusters using standard Kubernetes tools and APIs.

AWS Identity and Access Management (IAM): Amazon EKS integrates with IAM to provide authentication and authorization for Kubernetes API calls. This allows users to control access to their Kubernetes clusters using IAM policies.

AWS VPC networking: Amazon EKS integrates with Amazon VPC networking, allowing users to control network traffic to and from their Kubernetes clusters. This provides secure and isolated network access to Kubernetes applications.

AWS Load Balancers: Amazon EKS integrates with AWS Load Balancers, allowing users to easily expose their Kubernetes applications to the internet. This provides scalability and availability for Kubernetes applications.

AWS CloudFormation: Amazon EKS integrates with AWS CloudFormation, allowing users to create and manage their Kubernetes clusters using CloudFormation templates. This provides a way to automate the creation and management of Kubernetes clusters.

AWS CloudTrail: Amazon EKS integrates with AWS CloudTrail, allowing users to log and monitor all API activity for their Kubernetes clusters. This provides visibility into user activity and helps with compliance and auditing.

Support

Although Amazon provides support for EKS, getting help can be challenging, and users need to have a good understanding of the platform to troubleshoot issues effectively.

Node Groups: A node group is a set of Amazon EC2 instances that are used to run Kubernetes nodes. Node groups can be created and managed separately from the rest of the Kubernetes control plane, making it easier to scale your cluster as needed.

Control Plane: The control plane is the set of Kubernetes components that manage the state of your cluster. Amazon EKS provides a managed control plane that automatically scales to meet the needs of your workload.

Worker Nodes: Worker nodes are the Amazon EC2 instances that run your Kubernetes pods. These nodes are managed by the control plane and can be added or removed as needed to meet the demands of your workload.

Cluster: The Kubernetes cluster is the set of nodes and control plane components that work together to manage your workload. Amazon EKS provides a managed Kubernetes control plane, but you are responsible for managing your worker nodes.

Managed Node Groups: Managed node groups provide a simpler way to manage your worker nodes. You can create a managed node group with a few clicks in the AWS Management Console or using the AWS CLI or SDKs, and Amazon EKS takes care of the rest, including automatically updating the AMI and managing the lifecycle of the instances.

Fargate: Amazon EKS also supports running Kubernetes pods on AWS Fargate, a serverless compute engine for containers. With Fargate, you don't need to manage any infrastructure, and you only pay for the resources your pods consume.

Section 2 EKS Roadmap:

In this section I will be explaining the best ways to learn Amazon EKS and the ways to incorporate each service with your Amazon EKS environment.

Deployment:

Deployment in my opinon is the core aspect of Amazon EKS, it's like the cake itself. You need to have a cake in order to add frosting, sprinkles, and what not. So you always want to start with testing or visualizing a deployment first so its always great to have knowledge of deployment services first. The ones I would start with would be Kubernetes manifest, Container images, Kubernetes CLI, EKS console, CI/CD tools.

Kubernetes manifest: Kubernetes manifest is a YAML file that describes the desired state of the resources in a Kubernetes cluster. It can include specifications for a variety of resources such as deployments, services, pods, config maps, and more. Its a great way to setup your resources in EKS. The Kubernetes manifest defines the desired configuration of the Kubernetes objects and their relationships to each other. It is used by Kubernetes to create and manage the resources in the cluster. The manifest also enables developers to define complex deployment scenarios, including scaling and updating applications.

you can create a Kubernetes manifest file locally on your computer and use the kubectl command-line tool to apply it to your cluster. You can also use tools like AWS CloudFormation or AWS CDK to manage your Kubernetes resources using manifests.

Container images:

container images are self-contained, executable packages that include everything needed to run a piece of software, including the code, runtime, system tools, libraries, and settings. Container images are typically built using a Dockerfile, which specifies the dependencies and configuration needed to create the image. Once an image is built, it can be stored in a container registry, such as Amazon Elastic Container Registry (ECR), where it can be easily accessed and distributed to other users or teams. container images are used to deploy applications and services to the cluster. A container image can be specified in a Kubernetes manifest, and Kubernetes will use that image to create containers that run the application. When a container is created from an image, it runs in an isolated environment with its own file system, network, and resources, providing a consistent and reproducible environment for the application.

Container images can also be used to implement a continuous delivery (CD) pipeline, allowing developers to quickly and easily build, test, and deploy code changes to a Kubernetes cluster.

Kubernetes CLI: The kubectl command-line tool, which is a standard command-line interface for interacting with Kubernetes clusters. kubectl is used to deploy and manage applications and resources on a Kubernetes cluster running in Amazon EKS. With kubectl, you can perform a variety of tasks such as:

Creating, modifying, and deleting Kubernetes resources such as pods, services, and deployments.
Scaling and updating applications running on the Kubernetes cluster.
Viewing and troubleshooting logs and events.
Managing Kubernetes configuration and secrets.

To use kubectl with Amazon EKS, you need to first configure the tool with credentials to access your cluster. This can be done by running the aws eks update-kubeconfig command, which downloads the necessary authentication information and configures kubectl to use it. Once kubectl is configured, you can use it to interact with your Amazon EKS cluster as you would any other Kubernetes cluster.

EKS console: The EKS Console in Amazon EKS is a web-based graphical user interface (GUI) for managing Kubernetes clusters running on the Amazon EKS service. It provides an intuitive interface for viewing and managing the resources in your cluster, including nodes, pods, services, and deployments. The EKS Console includes a dashboard that provides an overview of the state of your cluster, as well as details about the nodes and resources running in the cluster. It also provides a visual editor for creating and managing Kubernetes resources such as pods and services.

While the EKS Console can be a useful tool for managing Kubernetes clusters, it is not a replacement for the kubectl CLI or other command-line tools. Some tasks may be easier to perform using the EKS Console, while others may be more efficient using the command-line tools. The EKS Console is intended to provide an additional option for managing your cluster, alongside the existing command-line tools and APIs.

CI/CD tools: There are many Continuous Integration/Continuous Deployment (CI/CD) tools that can be used with Amazon EKS to help automate the build, test, and deployment of applications and services to Kubernetes clusters. Some popular CI/CD tools that work well with EKS include:

AWS CodePipeline: A fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates.
Jenkins: An open-source automation server that can be used to build, test, and deploy applications to Kubernetes clusters using plugins and integrations with other tools.
GitLab CI/CD: An integrated CI/CD solution that provides automated testing, building, and deploying of applications using GitLab's pipeline feature.
CircleCI: A cloud-based CI/CD platform that allows you to build, test, and deploy applications using a simple configuration file. Spinnaker: An open-source multi-cloud continuous delivery platform that can be used to deploy applications to Kubernetes clusters.

These CI/CD tools can be used to create and manage pipelines that automatically build, test, and deploy containerized applications to Kubernetes clusters running on Amazon EKS. By automating the deployment process, teams can accelerate the delivery of new features and updates while ensuring consistency and reliability across different environments.

Networking:

Networking is a key part of Amazon EKS it is essential that everything in the EKS environment has a home and a way to communicate with each other to make sure everything can flow properly. So here are the main key services to master for your EKS environment as it pertains to networking.

VPC: A VPC is a virtual network that allows you to launch AWS resources in a logically isolated and secure environment. Amazon Elastic Kubernetes Service (EKS) is a fully managed Kubernetes service that makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS. When it comes to networking, a VPC can interact with Amazon EKS in several ways:

Network topology: Amazon EKS is deployed inside a VPC. You can specify the subnets where your Kubernetes nodes and other resources will be launched, as well as the security groups that control traffic flow to and from those resources. This allows you to define your network topology and control the flow of traffic in and out of your Kubernetes clusters.
Service discovery: Amazon EKS integrates with AWS Cloud Map to provide service discovery for Kubernetes services. Cloud Map can discover and map services to VPC endpoints or IP addresses, which can be used to access services within the VPC or from external networks.
Load balancing: Amazon EKS integrates with AWS Elastic Load Balancing (ELB) to provide load balancing for Kubernetes services. ELB can be used to distribute traffic across multiple Kubernetes nodes or pods, and can be configured to use a variety of load balancing algorithms.
Network policies: Amazon EKS supports Kubernetes network policies, which allow you to define rules for traffic flow within your VPC. Network policies can be used to control traffic between Kubernetes pods, as well as between pods and other resources in the VPC.

Subnets: A subnet in Amazon Web Services (AWS) is a range of IP addresses in your Virtual Private Cloud (VPC) that can be used to launch resources like Amazon Elastic Kubernetes Service (EKS) nodes or other AWS services. As EKS is deployed inside a VPC, subnets are an important aspect of networking for EKS. Here are some ways subnets interact with EKS:

Node subnet: When you create an EKS cluster, you specify the subnets in which to launch the worker nodes that will run your Kubernetes workloads. EKS will automatically launch the worker nodes in the specified subnets, and the nodes will have IP addresses assigned from the subnet range. This allows your nodes to communicate with other resources in the same subnet, as well as other subnets in the VPC.
Network policies: EKS supports Kubernetes network policies, which are used to control traffic flow between pods and other resources in the VPC. You can apply network policies to specific subnets, allowing you to define rules for traffic flow between pods and other resources in the same subnet or in different subnets.
Load balancing: EKS integrates with AWS Elastic Load Balancing (ELB) to provide load balancing for Kubernetes services. You can configure your load balancer to use specific subnets to distribute traffic to your Kubernetes nodes or pods. By selecting specific subnets for your load balancer, you can control the flow of traffic between nodes or pods and other resources in the VPC.
PrivateLink: AWS PrivateLink allows you to securely access EKS services without using public IP addresses or requiring traffic to traverse the internet. PrivateLink can be configured to use specific subnets, allowing you to control which subnets can access EKS services.

Security groups: Security groups in Amazon Web Services (AWS) are used to control traffic to and from your Amazon Elastic Kubernetes Service (EKS) resources, such as worker nodes and pods. Here are some ways security groups interact with EKS as it pertains to networking:

Worker node security groups: When you create an EKS cluster, you specify the security groups that will be associated with the worker nodes launched in the specified subnets. These security groups control inbound and outbound traffic to the worker nodes, allowing you to define rules for traffic flow between the worker nodes and other resources in the VPC.
Pod security groups: EKS supports Kubernetes Network Policies which can be used to define rules for traffic flow between Kubernetes pods and other resources in the VPC. Pod security groups are a Kubernetes construct that allow you to specify security rules for pods based on their labels. These security rules are applied to the pods' network interfaces and can control inbound and outbound traffic to the pods.
Load balancer security groups: If you use an Elastic Load Balancer (ELB) to distribute traffic to your EKS resources, you can specify security groups that control inbound and outbound traffic to the load balancer. These security groups can control access to the load balancer from the internet or from specific resources in the VPC.
PrivateLink security groups: If you use AWS PrivateLink to securely access EKS services from within your VPC, you can associate security groups with the endpoint network interfaces. These security groups can control inbound and outbound traffic to the endpoint, allowing you to define rules for traffic flow between the endpoint and other resources in the VPC.

ELB (Elastic Load Balancer): An ELB can be used to distribute traffic to resources in your Amazon Elastic Kubernetes Service (EKS) cluster. Here are some ways an ELB can interact with EKS as it pertains to networking:

Ingress controller: EKS supports Kubernetes ingress resources, which allow you to define rules for routing external traffic to your Kubernetes services. The Kubernetes ingress controller can be configured to use an ELB to distribute traffic to your services. This allows you to control traffic flow to your Kubernetes services from the internet or other resources outside your VPC.
Load balancing: When you configure an ELB to distribute traffic to your EKS resources, you can specify the target groups that contain the worker nodes or pods that will receive traffic. The ELB can use various algorithms to distribute traffic across the target group, such as round-robin or least connections. This allows you to scale your Kubernetes services horizontally by adding or removing worker nodes or pods as needed, and the ELB will automatically distribute traffic to the available resources.
Security: ELBs can be used to add an additional layer of security to your EKS resources. By configuring the ELB to use HTTPS or SSL/TLS, you can encrypt traffic between the ELB and your EKS resources. Additionally, you can configure security groups to control inbound and outbound traffic to the ELB, allowing you to define rules for traffic flow between the ELB and other resources in your VPC.
Auto Scaling: If you use Amazon EC2 Auto Scaling to automatically scale your EKS worker nodes based on demand, you can configure the ELB to work with Auto Scaling to distribute traffic to the new worker nodes as they are added. This allows you to scale your Kubernetes services dynamically based on demand, and the ELB will automatically distribute traffic to the available resources.

Kubernetes networking: Kubernetes networking refers to the way in which Kubernetes manages networking between its various components, such as pods, services, and nodes. Kubernetes networking allows pods to communicate with each other, and also provides access to services from within and outside the cluster. There are several Kubernetes networking options that can be used in EKS, including:

Amazon VPC CNI (Container Networking Interface): This is the recommended networking option for EKS. The Amazon VPC CNI uses the AWS VPC networking to provide each pod with its own IP address and allows pods to communicate with each other and with resources in the VPC.
kubenet: This is a simple, basic networking option that can be used in EKS. It uses a bridge network to allow pods to communicate with each other and with services.
Calico: This is a popular networking option that provides advanced network policy and security features, such as network segmentation and policy enforcement.

Security:

Security is one of the most important parts of not just EKS but any AWS environment or service. Without security everything would pretty much go out of order due to malfunctions and malicious hacks. Here are some of the best ways to ensure that your Amazon EKS environment is secure:

VPC: A VPC in AWS can interact with Amazon EKS in several ways as it pertains to security. Here are some ways a VPC can interact with EKS to enhance security:

Network isolation: A VPC provides network isolation for your EKS resources, which can help improve security by limiting access to your EKS resources to only authorized resources. By configuring security groups and network access control lists (ACLs) in your VPC, you can control inbound and outbound traffic to your EKS resources.
Private subnets: You can configure private subnets within your VPC for your EKS worker nodes, which can help improve security by preventing direct access to your worker nodes from the internet. This can be accomplished by using a Network Address Translation (NAT) gateway or a bastion host to access the worker nodes from outside the VPC.
Encryption: You can use various encryption options in your VPC to improve security for your EKS resources. For example, you can encrypt data at rest using Amazon Elastic Block Store (EBS) encryption or Amazon S3 server-side encryption. You can also encrypt data in transit between your EKS resources using Transport Layer Security (TLS) or Secure Sockets Layer (SSL) protocols.
Identity and access management: You can use AWS Identity and Access Management (IAM) to control access to your EKS resources. This can include managing permissions for accessing EKS resources, creating IAM users and groups, and implementing multi-factor authentication (MFA) for added security.
Logging and monitoring: You can use AWS CloudTrail to log API calls to your EKS resources, allowing you to monitor and audit activity in your VPC. Additionally, you can use Amazon CloudWatch to monitor and analyze logs and metrics from your EKS resources, providing real-time insight into the health and security of your infrastructure.

Monitoring and logging: Monitoring and logging are critical components of a secure and reliable infrastructure for Amazon Elastic Kubernetes Service (EKS). Here are some ways monitoring and logging interact with EKS as it pertains to security:

Security monitoring: Monitoring tools can detect suspicious activity or behavior in your EKS cluster, such as attempts to access resources that are not authorized or suspicious network traffic patterns. You can use monitoring tools such as Amazon CloudWatch or third-party solutions like Datadog or Prometheus to monitor your EKS cluster for potential security threats.
Incident response: In the event of a security incident, logs can be crucial for understanding the scope and impact of the incident, as well as for identifying the root cause. By collecting logs from your EKS cluster and other AWS services, you can quickly identify and respond to security incidents and reduce the impact of the incident.
Compliance: Compliance requirements often require logging and monitoring of infrastructure resources. By configuring logging and monitoring for your EKS cluster, you can demonstrate compliance with various security standards, such as the Payment Card Industry Data Security Standard (PCI DSS) or the Health Insurance Portability and Accountability Act (HIPAA).
Alerting: Monitoring tools can be configured to generate alerts when specific security events or anomalies are detected. This can include alerts for failed login attempts, unauthorized access attempts, or other suspicious activity. These alerts can be used to trigger automated incident response workflows or to notify security teams for further investigation.
Auditing: Monitoring and logging tools can provide audit trails of activity in your EKS cluster, allowing you to track changes and troubleshoot issues. By maintaining a comprehensive audit trail, you can identify potential security issues before they become major problems and ensure that your EKS cluster is functioning as expected.

Encryption: Encryption is an important component of security for Amazon Elastic Kubernetes Service (EKS) as it can help protect your data at rest and in transit. Here are some ways encryption interacts with EKS as it pertains to security:

Data at rest encryption: Encryption can be used to protect data at rest in your EKS cluster by using Amazon Elastic Block Store (EBS) encryption or Amazon S3 server-side encryption. EBS encryption encrypts data on the EBS volumes attached to your EKS worker nodes, while S3 server-side encryption encrypts the data stored in S3 buckets used by your EKS applications. By encrypting data at rest, you can help prevent unauthorized access to your sensitive data in case of a data breach or other security incident.
Data in transit encryption: Encryption can also be used to protect data in transit between your EKS resources, such as worker nodes, load balancers, and other services. You can use Transport Layer Security (TLS) or Secure Sockets Layer (SSL) protocols to encrypt data in transit between your EKS resources. By using encryption, you can help prevent eavesdropping and other attacks on your network traffic.
Key management: To effectively use encryption in EKS, it is important to manage the encryption keys used to encrypt and decrypt data. AWS Key Management Service (KMS) provides a scalable key management solution that integrates with EKS and other AWS services. With KMS, you can create and manage encryption keys, configure access controls, and audit key usage. This helps you maintain control over your encryption keys and ensures that your data remains secure.
Compliance: Encryption is often a requirement for compliance with security standards such as HIPAA, PCI DSS, and others. By using encryption in your EKS cluster, you can help ensure compliance with these standards and protect sensitive data.

IAM: AWS Identity and Access Management (IAM) is a key component of security for Amazon Elastic Kubernetes Service (EKS) as it enables you to control access to your EKS resources and manage permissions for users, groups, and applications. Here are some ways IAM interacts with EKS as it pertains to security:

Access control: IAM allows you to create policies that specify the permissions required to access your EKS resources. You can control who can create and manage EKS clusters, who can deploy applications to EKS, and who can access EKS API operations. By using IAM to manage access to your EKS resources, you can help prevent unauthorized access and ensure that users have the appropriate level of access to perform their tasks.
Resource permissions: IAM policies can also be used to control access to other AWS resources used by your EKS cluster, such as Amazon S3 buckets, Amazon RDS databases, and Amazon EC2 instances. By using IAM policies to manage resource permissions, you can help prevent unauthorized access and ensure that only authorized users can access sensitive data.
Service accounts: EKS uses Kubernetes service accounts to control access to Kubernetes resources within your cluster. IAM roles can be associated with these service accounts to control access to AWS resources. This allows you to control access to AWS resources used by your applications running on EKS, such as Amazon S3 or Amazon DynamoDB.
Audit logging: IAM can be used to generate audit logs of user activity within your EKS cluster. This can include actions such as creating or modifying IAM policies, creating or modifying EKS clusters, and accessing EKS resources. By reviewing these logs, you can identify potential security issues and ensure that users are following security best practices.
Multi-factor authentication (MFA): IAM supports MFA, which provides an extra layer of security to help prevent unauthorized access. By requiring MFA for IAM users who access EKS resources, you can help prevent unauthorized access and ensure that only authorized users can access sensitive data.

RBAC: Role-based access control (RBAC) is a key component of security for Amazon Elastic Kubernetes Service (EKS) as it allows you to control access to your EKS resources based on roles and permissions. Here are some ways RBAC interacts with EKS as it pertains to security:

Resource permissions: RBAC allows you to define roles that specify the permissions required to access EKS resources. You can control who can create and manage EKS clusters, who can deploy applications to EKS, and who can access EKS API operations. By using RBAC to manage resource permissions, you can help prevent unauthorized access and ensure that users have the appropriate level of access to perform their tasks.
Cluster-level access: RBAC allows you to define roles that apply to the entire EKS cluster. This includes roles for managing the cluster, such as creating and modifying Kubernetes objects, as well as roles for managing access to AWS resources used by the cluster, such as Amazon S3 or Amazon DynamoDB. By using RBAC to manage cluster-level access, you can ensure that only authorized users can manage the cluster and access sensitive data.
Namespace-level access: RBAC also allows you to define roles that apply to specific namespaces within the EKS cluster. This allows you to control access to resources within namespaces, such as Kubernetes pods or services. By using RBAC to manage namespace-level access, you can help prevent unauthorized access and ensure that users have access only to the resources they need.
Audit logging: RBAC can be used to generate audit logs of user activity within your EKS cluster. This can include actions such as creating or modifying roles, creating or modifying Kubernetes objects, and accessing EKS resources. By reviewing these logs, you can identify potential security issues and ensure that users are following security best practices.

Logging:

Logging is an extremely important aspect across EKS because 9 times out of 10 there is going to be a lot going on in your EKS environment. Logging will ensure that you keep track and maintain important Information or API calls made inside your Amazon EKS environment to ensure that nothing funny goes under your nose as it pertains to your environment. Here are incredibly effective ways to help log changes made in your EKS environment:

Cloudwatch: Amazon CloudWatch is a monitoring and logging service provided by AWS, and it can be used to collect, monitor, and analyze logs from Amazon Elastic Kubernetes Service (EKS). Here are some ways CloudWatch interacts with EKS as it pertains to logging:

Container logs: EKS allows you to collect and stream container logs from your EKS cluster to CloudWatch. This includes logs generated by containers running on Kubernetes pods within your cluster. By using CloudWatch to collect and monitor container logs, you can identify potential issues and troubleshoot problems quickly.
Node logs: EKS also allows you to collect and stream node logs from your EKS cluster to CloudWatch. This includes logs generated by the Kubernetes nodes that run your pods. By using CloudWatch to collect and monitor node logs, you can identify potential issues with your cluster infrastructure, such as node failures or network issues.
Log groups and streams: When you stream logs from EKS to CloudWatch, you can organize your logs into log groups and streams. This allows you to view and analyze logs from different parts of your EKS cluster separately. By using CloudWatch to organize your logs, you can quickly identify issues and troubleshoot problems in specific areas of your cluster.
Metrics: CloudWatch can also be used to monitor metrics from your EKS cluster, such as CPU usage, memory usage, and network traffic. By using CloudWatch to monitor metrics, you can identify potential issues and optimize your cluster performance.
Alarms: CloudWatch can be used to create alarms based on metrics or log data. This allows you to receive notifications when certain thresholds are exceeded or specific events occur within your EKS cluster. By using CloudWatch alarms, you can quickly respond to potential issues and take action to ensure the security and stability of your cluster.

Kubernetes Monitoring and Logging: Kubernetes monitoring and logging are important for maintaining the security and performance of Amazon Elastic Kubernetes Service (EKS) clusters. Here are some ways Kubernetes monitoring and logging interact with EKS as it pertains to logging:

Kubernetes API server logs: EKS provides access to Kubernetes API server logs, which contain information about API requests and responses, authentication, and authorization. These logs can be useful for troubleshooting issues with Kubernetes components, identifying security threats, and auditing activity within your EKS cluster.
Kubernetes application logs: Kubernetes allows you to collect and stream application logs from your EKS cluster using various logging frameworks such as Fluentd, Fluent Bit, and others. By configuring logging agents to collect logs from your Kubernetes application, you can identify and troubleshoot issues within your applications, such as errors or crashes.
Kubernetes events: Kubernetes generates events to record changes to objects in the Kubernetes API. These events can be used to track changes to the state of objects, such as pods or services, and to diagnose problems with your EKS cluster.
Monitoring metrics: Kubernetes provides a rich set of monitoring metrics that can be used to monitor the health and performance of your EKS cluster. These metrics can be collected and analyzed using a variety of monitoring tools, such as Prometheus or Grafana. By monitoring these metrics, you can identify potential issues and optimize your cluster performance.
Log aggregation and analysis: Kubernetes logging and monitoring data can be aggregated and analyzed using various tools, such as the Elastic Stack or AWS Elasticsearch. By aggregating your logs and metrics, you can gain greater visibility into your EKS cluster, identify trends and patterns, and troubleshoot issues more efficiently.

Container insights: Container Insights is an Amazon CloudWatch feature that provides logging and monitoring capabilities for Amazon Elastic Kubernetes Service (EKS) clusters. Here are some ways Container Insights interacts with EKS as it pertains to logging:

Collecting container logs: Container Insights can collect and stream container logs from your EKS cluster to CloudWatch Logs. This includes logs generated by containers running on Kubernetes pods within your cluster. By using Container Insights to collect and monitor container logs, you can identify potential issues and troubleshoot problems quickly.
Collecting EKS control plane logs: Container Insights can also collect and stream logs from the EKS control plane, including API server logs, scheduler logs, and controller manager logs. This can be useful for troubleshooting issues with Kubernetes components, identifying security threats, and auditing activity within your EKS cluster.
Viewing container logs: Container Insights provides a dashboard within the CloudWatch console where you can view logs generated by containers running in your EKS cluster. The dashboard allows you to filter and search logs, view logs for specific containers, and analyze trends over time.
Analyzing container logs: Container Insights can be used to analyze container logs using CloudWatch Logs Insights. This allows you to query and analyze logs using a SQL-like syntax, identifying patterns and trends in your log data.

AWS X-ray: AWS X-Ray is a distributed tracing system that enables you to trace requests across multiple services and identify the root cause of performance issues or errors. When integrated with Amazon EKS, AWS X-Ray can provide valuable insights into the performance and behavior of your microservices running on your EKS cluster. Here are some ways AWS X-Ray interacts with Amazon EKS as it pertains to logging:

Tracing microservices: AWS X-Ray can trace requests as they move through your microservices running on EKS. This allows you to identify the performance of individual services, as well as the entire request flow. Traces can be used to identify performance bottlenecks and troubleshoot issues.
Correlating logs and metrics: AWS X-Ray can correlate logs and metrics with distributed traces, allowing you to identify the root cause of issues more quickly. By correlating logs and metrics with traces, you can identify patterns and trends that may be impacting the performance of your microservices.
Service maps: AWS X-Ray can generate service maps that show the relationships between your microservices. Service maps provide a visual representation of the architecture of your application, making it easier to understand the dependencies between services.
Insights into external services: AWS X-Ray can trace requests to external services, allowing you to gain insights into the performance of third-party services that your application depends on. This can be useful for identifying issues with external services that may be impacting the performance of your application.

3rd party logging tools: There are several third-party logging tools that can be used to collect, analyze, and visualize logs generated by microservices running on Amazon EKS. Some examples include:

Elasticsearch: Elasticsearch is a popular search and analytics engine that can be used to collect, store, and analyze logs from EKS clusters. It provides powerful search capabilities, real-time analytics, and visualization tools that make it easy to identify issues and troubleshoot problems.
Fluentd: Fluentd is an open-source data collector that can be used to collect and forward logs from EKS clusters to a centralized logging platform such as Elasticsearch or Splunk. It supports a wide range of inputs and outputs, making it a flexible and powerful tool for collecting and managing logs.
Splunk: Splunk is a popular log management and analysis platform that can be used to collect, index, and analyze logs from EKS clusters. It provides powerful search capabilities, real-time analytics, and visualization tools that make it easy to identify issues and troubleshoot problems.

These third-party logging tools can interact with Amazon EKS in several ways:

Integration with Kubernetes logging: Many third-party logging tools can be integrated with Kubernetes logging to collect logs generated by pods and containers running on EKS clusters.
Integration with Amazon CloudWatch: Some third-party logging tools can be integrated with Amazon CloudWatch to collect and analyze logs generated by EKS clusters. This allows you to use CloudWatch as a centralized log repository and leverage its powerful analytics and visualization tools.
Direct integration with EKS: Some third-party logging tools provide direct integration with EKS, allowing you to collect and analyze logs from your EKS clusters without the need for additional configuration or setup.

Rimurutempestx/Amazon-EKS-Breakdown