kubernetes VS consul

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.

The JHipster scaffolded sample application has a gateway application and two microservices. It uses Consul for service discovery and centralized configuration.

Service Discovery: Microservices need to discover and communicate with each other dynamically. Service discovery tools like etcd, Consul, or Kubernetes built-in service discovery mechanisms help locate and connect to microservices running on different nodes within the infrastructure.

After some research and testing, I landed on using Consul and Fabio as the demo infrastructure. Of course, there is a myriad of other options to accomplish this task, but because of the low configuration and ease of use, I was impressed with this pairing. Both projects are mature and well-supported, and very flexible--just because you can run them with low configuration, doesn't mean you have to. I wanted to keep this demo constrained, but the exercise did get me excited about exploring things further: circuit breakers, traffic splitting, and more complex service meshes.

The goal is to be able to use Consul SD configurations to allow for retrieving scrape targets from consul. Is this possible? Can anyone provide an example? Thank you!!

https://github.com/hashicorp/consul/pull/12080 - this should be the Consul issue that brought down Roblox

The Consul collector is production ready! Consul by HashiCorp is a powerful and complex identity-based networking solution, which is not trivial to monitor. We were lucky to have the assistance of HashiCorp itself in this endeavor, which resulted in a monitoring solution of exceptional quality. Look for common blog posts and announcements in the coming weeks!

Changed the service discovery to Consul, since this is the default in JHipster 8.

In another effort to standardize development and operations, Lob has just wrapped up our container orchestration migration from Convox to HashiCorp’s Nomad, led by Senior Platform Engineer Elijah Voigt. In this new ecosystem, one feature available to us is Consul Service Mesh (a feature of Consul, which is part of our Lob Nomad stack).

Service registry and discovery etcd, consul, nacos