Ansible VS kubernetes

Ansible is an open-source IT automation tool that simplifies application deployment, cloud provisioning, and configuration management across diverse environments. It uses a declarative language to describe the desired state of the system, and then takes the necessary actions to achieve that state. Ansible has become incredibly popular due to its simplicity, agentless architecture, and extensive community support. Document: ansible.com, ansible basics

Ansible v2.16

Ansible is a tool used to help manage software automation processes, configuration management across machines, deployment as well as remote execution of commands and scripts. In sports, Ansible operates as the coach of your team by providing strategies (playbooks), and actions, and ensuring the smooth execution of tasks across your infrastructure, just like a coach guides and directs players (Servers)during a game.

They support for-if from python, too: https://jinja.palletsprojects.com/en/3.1.x/templates/#loop-f... but I haven't tried the "recursive" keyword to know if ansible supports that. I say "ansible supports that" because they don't just drop jinja2 into ansible and call it a draw, they have a bunch of custom execution integrations: https://github.com/ansible/ansible/blob/v2.16.3/lib/ansible/...

To manage a VM, you can use something as simple as just manual actions over SSH, or can use tools like Ansible, Hashicorp's Packer and Terraform or other automations. For an app where there is minimal load and security/reliability concern, VMs are still a great option that provide a lot of value for the buck

In this article's context, it is simply a tool that provides a declarative way to automate your machine/OS to configure the development machine as you want (install package, modify the configuration, etc). Examples of these tools are Ansible, Puppet, etc.

Now we're getting more tangential, but for years, Ansible releases were named for Van Halen songs (see old Changelog here: https://github.com/ansible/ansible/blob/v1.8.4/CHANGELOG.md)

In the lab to follow, we'll quickly provision a 3-node kubeadm cluster (1 master, 2 workers) on the cloud provider of your choice using an automation stack comprised of OpenTofu and Ansible, then deploy Rook Ceph using the official Helm charts and confirm that we are now able to successfully create CSI volume snapshots from PVCs by reusing the MinIO example from our last article.

I’m joking of course. I’m not really sure about what a faded keyboard says about its owner. What I do know for sure is how important kubectl is to anybody who wants to be a proficient Kubernetes administrator.

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.