backstage VS kubernetes

apiVersion: scaffolder.backstage.io/v1beta3 # https://backstage.io/docs/features/software-catalog/descriptor-format#kind-template kind: Template metadata: name: sample-btpsubaccount-remote-template title: Remote Template for SAP BTP Subaccount Setup description: A remote template that creates a basic SAP BTP Subaccount setup tags: - sap - btp - basic - javascript spec: owner: user:guest type: service

Backstage is an open-source platform developed by Spotify for managing the entire lifecycle of developer infrastructure, including services, APIs, documentation, and more. Backstage streamlines the development process through its centralized and customizable platform, offering a unified dashboard that consolidates information on projects, services, and infrastructure. Acting as a service catalog enhances transparency by allowing teams to document and discover internal services easily. Backstage's extensible architecture supports a robust plugin ecosystem, enabling teams to tailor the platform to their specific workflows and preferences. The platform promotes collaboration, accelerates onboarding through standardized documentation, and integrates seamlessly with various DevOps tools.

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.

We use Confluence and markdown files in GitHub. I think we are moving a lot of our docs to Backstage [0] soon.

One process that ends up being really valuable for documentation purposes is our "Architecture Review Documents". This is a standard document that team leads fill out before starting work on a new Saga/Epic/Feature/whatever. It includes the scope and business value of a new feature or large block of work, high level technical architecture of implementation, the impact on existing database schemas and service APIs, etc. This document is presented in a meeting with technical leadership in our organization who deep dive on the topic and explore potential pitfalls in the plan.

The document and recording of that meeting live on forever, and this information is very useful when getting acquainted with a certain part of our product/codebase. You are able to read and hear clearly the intention of a certain service or module, and you can identify several relevant points of contact to ask questions to.

[0] https://backstage.io/

Check the Backstage repo on GitHub

Backstage - An open platform for building developer portals. [Internal Developer Portal]

So you've just bought a new platform tool? Maybe it's Hashicorp Vault? Snyk? Backstage? You’re excited about all of the developer experience, security and other benefits you're about to unleash on your company—right? But wait…

The idea is to have a central point where people can find standards, documentation, and designs. The team can do this with a specialized tool like Backstage, Confluence, Github, Google Docs, or some internal implementation. The software is not the most important thing here, but having an easy way to find what is needed for the person to be more productive.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

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.

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.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

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.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

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.