flux2 VS kubernetes

Given the team had already adopted GitOps and were familiar with deployments powered by Helm Releases and Flux, we wanted to move the provisioning of the infrastructure to be part of the same process of creating the service and its continuous deployment.

Your GitHub action can trigger a helm chart, or series thereof, or other infra tools. Declarative specifications, triggered procedurally with the context of the branch’s latest build. We use this pattern quite extensively for preview app workflows.

As of a year ago this is possible in a fully declarative way with Flux 2, but there’s a lot more moving parts and security footguns - and the idea that the maintenance of this project has lost one of its primary sponsors is worrying at best.

https://github.com/fluxcd/flux2/discussions/831

https://blog.kluctl.io/introducing-the-template-controller-a...

FluxCD - FluxCD is another popular GitOps tool that allows developers to use a Git repository as the sole source of configuration. Flux automatically ensures that the state of the Kubernetes cluster is synchronized with the configuration in the Git repository. It supports automatic updates, meaning Flux can monitor Docker image repositories for new images and push updates to the cluster.

#!/bin/bash aws eks update-kubeconfig --name $CLUSTER_NAME --region $AWS_REGION flux_installed=$(kubectl api-resources | grep flux) if [ -z "$flux_installed" ]; then echo "flux is not installed" curl -s https://fluxcd.io/install.sh | sudo bash flux bootstrap github \ --owner=$GH_USER_NAME \ --repository=$FLUX_REPO_NAME \ --path="clusters/$ENVIRONMENT/$CLUSTER_NAME/bootstrap" \ --branch=main \ --personal else echo "flux is installed" fi

Flux CD enables continuous deployment to Kubernetes through GitOps by syncing Git repositories with Kubernetes clusters. Flux CD enables GitOps for Kubernetes through source control integration. It manages Kubernetes manifests as code and syncs git repo changes to clusters. Flux automates checks, deployments, and updates within clusters.

FluxCD is a GitOps tool developed by Weaveworks that allows you to implement continuous and progressive delivery of your applications on Kubernetes. It is a CNCF graduated project that offers a set of controllers to monitor Git repositories and reconciles the cluster's actual state with the desired state defined by manifests committed in the repo.

From here, we can explore other developments and tutorials on Kubernetes, such as o11y or observability (PLG, ELK, ELF, TICK, Jaeger, Pyroscope), service mesh (Linkerd, Istio, NSM, Consul Connect, Cillium), and progressive delivery (ArgoCD, FluxCD, Spinnaker).

Instead, we will create a single long-lived cluster, and deploy our application in different namespaces. There are a bunch of ways to do that - see ArgoCD, Flux, custom internal tooling, or other solutions (we use our own product). That way, we:

One is to make sure configurations in both clusters is same. And for that there are many tools like fluxcd or projectsveltos

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.

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.

Kubernetes was first released on September 9, 2014. This release timeline is part of what helped it gain a foothold over Docker Swarm. It was an open source version of an internal Google project. Features of container orchestration were presented in a more modular fashion along with scaling functionality. You can chose how your networking stack works, your load balancing, container runtime, and filesystem interfaces. Availability of an API allowed for more programmatic interactions with orchestration, making it tie in very well with CI/CD solutions. However, the big issue it has is complexity of setup. Putting together a Kubernetes cluster with basic functionality is certainly no easy feat.