cloudinit VS Ansible

This comes from the `ssh_pwauth` setting in cloud-init. Docs: https://cloudinit.readthedocs.io/en/latest/reference/modules...

The PR https://github.com/canonical/cloud-init/pull/1618 implemented using a "sshd_config.d" file.

In my previous article I went over how to set up VMs in Proxmox VE using Terraform to deploy the VMs and Cloud-Init to provision them. In this article I'll discuss using Ansible playbooks to do further provisioning of VMs.

In my last article I talked about getting Terraform set up on Proxmox VE. In this article I want to talk about how I got Cloud-Init set up to use with my Terraform templates.

Multipass is a mini-cloud on your workstation using native hypervisors of all the supported plaforms (Windows, macOS and Linux). Multipass can launch and run virtual machines and configure them with cloud-init like a public cloud.

And there you have it! In my next article I'll show you how to provision your VMs using Cloud-Init

[1] Cloud-Init: https://github.com/canonical/Cloud-Init [2] AutoMQ: https://github.com/AutoMQ/automq [3] Introduction to Cloud-Init: https://cloudinit.readthedocs.io/en/latest/explanation/introduction.html#how-does-Cloud-Init-work

Newer versions of OS use cloud init -> https://cloud-init.io/

Overall, I think in an article that focuses on cloud computing (specifically AWS) there's too much time being spent in the local command line of a server.

It's an especially revealing sentence when the authors says that "Most attacks won’t be against what we’ve covered in this guide, but against the applications you install next. Properly done, containers can limit the impact."

If we are running containerized applications and we are already in the cloud, why are we futzing around on the command line of a Linux box? Why are we not using a cload orchestrator that abstracts the OS from the equation entirely?

If we do have a need to be on a bare Linux box, all of this OS configuration is better handled with cloud init [1], a configuration management tool like Ansible, and/or by building an image with Packer.

I know that seems like overkill for a small hobby reluctant sysadmin project type of deal but it's very little extra effort once you get used to the workflow. I would even recommend putting this infrastructure in Terraform even though, again, it seems like overkill at first.

Someone else in the comments mentioned that it's easier to just start with a hardened image from the AWS Marketplace, and I also agree with that idea. Find a free hardened image and make that the base for your system.

[1] https://cloud-init.io

​​Ansible provides streamlined automation for IT orchestration and configuration management through its declarative language. Teams can efficiently define and execute automation tasks, ensuring consistent environment management. This tool provides simplicity and effectiveness making it a valuable tool for managing complex IT infrastructures at scale.

A key aspect of this starter kit is its comprehensive automation using Ansible. The polaris-forge-setup directory houses Ansible playbooks that:

Hi, in this post, we will use Libvirt with Terraform to provision 2 KVM locally and after that, we will Deploy Flask App & PostgreSQL using Ansible.

Ansible GitHub Repository

Ansible is an open-source tool that excels in infrastructure configuration. With an agentless architecture (no services need to be installed on the managed machines), it communicates with machines over SSH.

Visit the repository for code and examples.

I do believe that using containers makes a ton of sense in writing data pipelines. You can use the same image to develop and run the pipeline, preventing "it works on my machine" issues. You can test different variations of the image without having to stand up additional infrastructure or potentially breaking the workflows of others who're using the same infrastructure. Finally, knowledge of containerization is increasingly expected of all engineers, while knowledge of other tools that solve similar issues (like Vagrant or Ansible) is less common.

Bearing in mind that YAML is still used widely in build and testing production-level environments, it proves to be an essential tool for managing configurations and data interchange. Its readability and flexibility make it a popular choice for defining automation scripts in Ansible , where it streamlines IT task automation. Similarly, YAML's role in Github Workflows facilitates the configuration of CI/CD pipelines, making testing and deployments more efficient. The continued evolution and integration of YAML in these critical areas underscore its ongoing relevance and effectiveness in simplifying complex workflows and configurations. For me, if it works, the it is not a failure.

2. Ansible with AI-Powered Automation