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οΈπŸš€ πŸš€ Top 3 GitOps Tools for Infrastructure Automation in 2024 πŸ”¨

In 2024, developers should primarily focus on their core tasks of feature development, fixing bugs and making improvements to the application.

That means less time spent on adding feature flags, managing infrastructure, monitoring deployments, etc.
Also, as per Puppet State of DevOps Report 2023, lack of automation has been one of the biggest pain points of platform teams.

So in this article, let’s unpack why your project needs infrastructure automation and share tools to help you get started.

Shall we?


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Table of Contents


How Can Your Project Benefit From Infrastructure Automation?

Let’s go over some of the basic benefits of automating your infrastructure:

  1. Ensure repeatable results every time. So that you can provide predictable and reliable experience to users and development teams.
  2. Remove the need for (#clickops), engineers clicking around in a cloud provider UI. Automation improves process efficiency and agility by reducing manual effort. As a result, freeing up DevOps engineers from the tedious tasks.
  3. Built in auditing. Keep a log of every operation done in your infrastructure. Comprehensive audit trails provide visibility into history of operations which is of great help at the time of debugging and troubleshooting.

Tool #1: Digger

If you want to simplify your infrastructure management and improve visibility and auditability of its changes, Digger might be worth exploring. It’s an open-source IaC automation and collaboration software for Terraform and OpenTofu.

Digger tool


Digger tool showing proposed infrastructure changes.

You can version control your infrastructure through defining it in code and storing it in the git repository. With automated infra provisioning and updates, Digger ensures consistency and significantly reduces manual effort of DevOps teams.

At the time of writing this article, Digger has ~2.5k stars on GitHub and is used by companies like Grab, McKinsey & Company, Duolingo with several others.

They also have a highly responsive community that will help you with roadblocks along the way.


Tool #2: Argo Project

Argo Project has become one of the top projects to manage Kubernetes clusters and workflows. Along with being able to run CI/CD pipelines natively, you can easily run compute intensive jobs like data processing in fraction of time.

With it’s rollouts tool, it provides advanced deployment capabilities such as:

  • Blue-green βœ…
  • Canary βœ…
  • Canary analysis βœ…
  • Experimentation βœ…

Also, Argo provides a declarative approach to application deployment that simplifies the deployment process and reduces the risk of errors.

Argo tool
Argo Tool to get more done with Kubernetes.

If you’re thinking, can Argo meet your advanced deployment requirements? Here’s a step-by-step tutorial by @pavanbelagatti on how to implement advanced deployment strategies:


Tool #3: Pulumi

Storing infrastructure as code is great but how to write code for one? Well Pulumi has solved that for you. It simplifies and automates your cloud infrastructure and optimizes for speed of releases.

Best part? You can do that in your familiar programming language with autocomplete, type checking and up-to-date documentation. Leaving no reason to procrastinate πŸ˜…

Pulumi AI
Pulumi AI responding to prompt.

Here’s what Matt Stephenson, Senior Principal Software Engineer at Starburst Analytics has to say about Pulumi:

Pulumi let us build and automate cloud infrastructure projects at a scale that simply wasn’t imaginable using prior-generation infrastructure as code technologies

Pulumi is truly your partner for scaling cloud infrastructure.


Wrap Up

That’s it!

Now, I hope these tools will help you in automating your project infrastructure.

If you need any help in setting up these tools, feel free to ping me on discord. We have an awesome community there πŸ’—

If you found this valuable, follow me for more open source related articles πŸ™‚

Top comments (4)

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matijasos profile image
Matija Sosic

I love that Pulumi went with the SDK approach, although Terraform also introduced it soon enough. What's your preference DSL, or the SDK?

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markphelps profile image
Mark Phelps

Same! I always prefer native code over learning a DSL whenever possible

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utpalnadiger profile image
Utpal Nadiger

Super cool write up. Thanks for mentioning Digger @markphelps!

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fernandezbaptiste profile image
Bap • Edited

Noice!! Really enjoyable read :)

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