aws-node-termination-handler VS helm

Disaster recovery is a critical component of any IT infrastructure. It ensures that your applications and data are protected in the event of an unexpected outage or disaster. In this blog post, we will explore different disaster recovery strategies for Amazon Elastic Compute Cloud (EC2) deployments.

When you are using compute you have a lot of options. One of these options is Amazon EC2. In a world where more and more workloads become serverless. You might still have this use-case that is better off on EC2. But, how do you combine EC2 with compliance and security? In this blog post we will explore how we can build a compliant and secure EC2 stack.

In this article, a WEB application using the latest version of Angular in a built Docker image will be hosted on Amazon EC2 (Elastic Compute Cloud) and deployed by Amazon ECS (Elastic Container Service) using an Amazon ECR (Elastic Container Registry) containers repository.

The single most important development in hosting since the invention of EC2 is defined by its own 3-letter acronym: k8s. Kubernetes has won the “container orchestrator” space, becoming the default way that teams across industries are managing their compute nodes and scheduling their workloads, from data pipelines to web services.

EC2

Then in 2020, I started working with AWS. My first two years with AWS were mostly interacting with the Node.js apps I've deployed in EC2 and reviewing logs since we had a DevOps engineer who managed the cloud infrastructure.

If you want to learn more about EC2 and get detailed information, I suggest you start your journey by visiting https://aws.amazon.com/ec2/. This is the best place to begin learning about EC2.

AWS - Cloud Computing AWS - EC2 Wikipedia - Cloud Computing Guru99 - Cloud Computing Cloudflare - Cloud Computing Cloudzero - Statistics Zippia - Statistics

Say that we have an application running behind a public-facing Application Load Balancer (ALB). The load balancer's target can be any supported target, including ECS containers, EC2 instances or even Lambda functions. Because the application is only available to authenticated users, we want to find a solution to identify them.

Although I'll use Lambda functions in the examples, we can transfer the concepts to other compute resources, like EC2 instances, and ECS or EKS containers.

Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.

helm

Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...

Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.

Helm (Get from here https://helm.sh/)

It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.

Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!

Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.

We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).

Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.

Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.