stargate VS kind

They suggested https://stargate.io

- https://github.com/stargate/stargate

Datastax Astra is built on Apache Cassandra. In addition to great documentation, Astra offers a robust free tier that can run small production workloads, pet projects, or just let you play—all for free, no credit card required. Cassandra can be tricky for hardcore SQL developers, because it uses a different slightly different query language (CQL), but when you get Astra, Stargate is there to let you interact with your data through APIs. Our open source Stargate product provides REST, GraphQL, and schemaless document APIs in addition to native language drivers. If you like them but don’t want to use our products, that’s fine! It’s completely open source and you can implement it on your own system.

DataStax built Stargate into Astra to give us, app developers, a natural data API stack which meshes with the Jamstack (or serverless stack of your choice). Stargate in Astra is built on the rock solid NoSQL data engine (Apache Cassandra) which powers Netflix, Instagram, Yelp, iCloud and other apps we all use everyday.

To make it easy for your app to interact with the database, we created Stargate.io. It’s an open-source data gateway with three APIs that work with Astra DB right out of the box. Instead of having to read up on different APIs and databases, all you have to do is pick one of the three Stargate APIs and get to work on your application.

Twelve-plus years after its invention, Cassandra is now used by approximately 90 percent of the Fortune 100, and it’s appeal is broadening quickly, driven by a rush to harness today’s “data deluge” with apps that are globally distributed and always-on. Add to this recent advances in the Cassandra ecosystem such as Stargate, K8ssandra, and cloud services like Astra DB, and the cost and complexity barriers to using Cassandra are fading into the past. So while it’s fair to say that while Cassandra might have been ahead of its time in 2007, it’s primed and ready for the data demands of the 2020s and beyond.

Until now, aggregate functions were only available using cqlsh (the CQL Shell). However, with the Stargate 1.0.25 release, they are now also available using the GraphQL API. In this blog entry, I’ll walk you through the process to get early access to this exciting new functionality in Stargate, and how to set up everything you need to test your own aggregate queries.

Stargate is an open-source data gateway that makes it simple to query any Cassandra database using GraphQL types, queries, and mutations. When you add the Stargate GraphQL API to a Cassandra deployment, it scans the database and automatically creates HTTP endpoints with GraphQL queries and mutations for the objects it finds.

BattleStax is implemented as a JAMStack app that uses Stargate, Netlify, DataStax Astra DB, and GitHub to demonstrate how to build and deploy an application using modern, scalable architectures. In this post, we’ll break down the video to help you quickly create your own BattleStax game using React and Redux — implemented with a CI/CD pipeline, global content delivery network (CDN), and Apache Cassandra®.

Have you tried https://kind.sigs.k8s.io/? If so, how does it compare to k3s for testing?

To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:

Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.

Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Features compared to https://kind.sigs.k8s.io/

Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.

Check out KinD

If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.

You can also use k3s; it's hella easy to get started with and it works great.

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.