stargate VS kubernetes

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®.

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

Securing access to your Kubernetes clusters is crucial as inadequate security measures can lead to unauthorized access and potential data breaches. However, navigating the complexities of Kubernetes access security, especially when setting up strong authentication, authorization, and network policies, can be challenging.

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.