Suppose you are building a puzzle game with your peers, but in order to expedite the process, every team is assigned to create one unique piece in multiple numbers. Now, there's a problem here because, ideally, the interlocking features of all pieces of the puzzles could be planned in any manner since every team is operating independently.
Now, if you assign every team to simultaneously report that they created the interlocking feature on the left, right, up or down of the puzzle pieces, it would amount to information overload during the time of production and production delays. How do we solve this? By unifying the production process and ensuring real-time information passage and code adjustment accordingly to make necessary changes in the puzzle pieces and place the interlocking extensions on the left, side, up and down based on all the other department's real-time production updates. But who could do this for the production department? 

What is terraform? 

Terraform is a powerful infrastructure as a code (I-A-C) software which converges on-premise and cloud together to speed up the development process when you are building any technological infrastructure. Due to this, it is possible to connect different infrastructure hosts, integrate them together and make real-time necessary changes when required to even achieve complex management outcomes at the time of coding for any sector, Be it AI or Gaming. 

How Terraform Help You When You Are Building AI-Ready Infrastructure?

When you are building an AI-ready infrastructure, there are different components that you need to create in different environments. Now, it is very difficult to standardize them all so that they work like Lego blocks to build your AI infrastructure. It is here where Terraform, when mixed with AWS, creates the real magic. Why? Because if you are not using Terraform, you will have a nightmare doing the following things; 

1. Setting up computational intensity

Remember that you are building an AI-ready infrastructure. So, it could be large LLMs that you want to build and use the extracted data to build an application on top of it. Now, the processing power that you need for assembling all the blocks together so that they function as per your command would be humongous. Imagine setting up 100 GPU units for the same. Forget the cost; you can just burn out simply by setting up the infrastructure firsthand. 

2. Organizing the Data

If you thought that whatever was said earlier was everything, it was just the tip of the iceberg. Now, you have to deal with data management. And mind you, there's structure and unstructured data to break for user settings, app functions and more. Moreover, you have to also check how your models are behaving when you are feeding such data to them. Sounds like a real nightmare, right? 

3. Security Requirements

4. Scalability

Now, by god's grace, you have overcome all the above hurdles, and now, suddenly, you have users flooding your application; how could you deal with the same? 

Now, how everything changes when Terraform lands like your saviour. Yeah, like Iron Man to save the day. 

Read: AI workloads are breaking the cloud: Time for an AI-First Architecture?

Here's how

1. Reproducibility

When you have Terraform, you do not have to worry about the GPUs, rather the reproducibility of Terraform would ensure you can quickly spin up an identical set-up and quickly get started with the test, staging, production. Which means you are not stuck with setting up the processes. On the other hand, you have all the processes in place and you simply have to set them up and viola, they will work on the go. 

2. Version Control

Now, like I already said at the beginning itself, what if someone is building the interlocking extension left, right, up or down as per their whims and fancies? Now, it could be a challenge for you because everyone is working independently in their own environment. But when Terraform and AWS assemble, it is like that Avengers Assemble moment because whenever anyone is doing any specific changes to the Legos blocks, it is simultaneously getting logged in to the GIT. The GIT would give you full control to either roll back or tweak the coding to fit your needs. Moreover, you can also check who has made any changes and subsequently take necessary actions against the same. 

3. Automation

You can also automate the entire process using Terraform and AWS because you can map that to the cloud infrastructure, and whenever there's new coding or feature integration, Terraform will adjust accordingly and make necessary changes instead of you having to build everything from the scratch because some of your lousy ones just messed up. 

4. Coded documenting

You also get coded documentation of everything, streamlining discoverability because with just a click, you can identify what's running where, and you can fix them on the go. You can simply give rest to diagrammatic representations and more, giving you terrible nightmares. 

Conclusion

Now, typically, one would interpret that when they are coding for their AI models, it will take months or years to build since they are simply assembling nuts and bolts with different proportions, threads and designs. But such is not the case when you have Terraform bundled with AWS, because neither you have to worry about setting up those heavy extensive GPU units, nor do you have to wonder once about setting up a new infrastructure that could break your bank. Terraform is transforming things by automating everything and giving the breath to developers that they rightfully deserve.

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