aws-node-termination-handler VS helm-charts

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.

Prometheus can be deployed using the Prometheus Helm Chart. This helm chart contains a lot of features such as the already mentioned Push Gateway, Alert Manager and so on. For simplicity reasons of this tutorial I will not show all the Helm chart configuration but you can see a real example used by me here.

Building upon Bartłomiej Płotka's insightful blog on Prometheus and its passthrough agent mode, this post dives into implementing multi-cluster Prometheus support. Notably, the official inclusion of support in the widely-used kube-prometheus-stack came with the release in July 2023, making it easier to extend Prometheus monitoring across clusters.

The first thing you'll need, of course, is at least one backend to store metrics. So install Prometheus now:

For the request following, something like jeager https://www.jaegertracing.io/, because you are talking more about tracing than necessarily logging. For just monitoring, https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack would be the starting point, then it depends. Nginx gives metrics out of the box, then you can pull in the dashboard like https://grafana.com/grafana/dashboards/14314-kubernetes-nginx-ingress-controller-nextgen-devops-nirvana/ , or full metal with something like service mesh monitoring which would provably fulfil most of the requirements

kube-prometheus-stack is a Helm chart that contains several components to monitor the Kubernetes cluster, along with Grafana dashboards Grafana Dashboards to visualize the data. This option will be used in this article.

This one I highly recommend: https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack

We use kube-prometheus-stack for metrics and have added the K8s views dashboards from grafana-dashboards-kubernetes. You should check out the k8s-views-global dashboard. I believe it's just what you are looking for.

You should take a look at "kube-prometheus-stack". It not only includes prometheus, node-exporter and Grafana but also a ton of preconfigured alerts and dashboards. Will save you a lot of work!

Since their are different ways to install what exactly did you install? Vanilla charts , stack, operator? https://github.com/prometheus-community/helm-charts/tree/main/charts