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Using GenAI to Power the Terraform Automated Compliance Engine (TACE)

Introduction

As organizations increasingly rely on cloud infrastructure, managing and deploying compliant infrastructure as code (IaC) has grown more complex. BSC Analytics developed the Terraform Automated Compliance Engine (TACE) to simplify this process, enabling users to describe the infrastructure they need in plain language and generate compliant Terraform code that integrates seamlessly into existing workflows. The TACE engine leverages Generative AI technology, using a repository of pre-hardened and audited Terraform modules to ensure security and compliance while allowing users full control over the resulting code.

TACE combines the flexibility of natural language processing (NLP) with the rigor of compliance-driven infrastructure design, making it easier for users to build secure and scalable cloud environments with minimal manual intervention, leveraging AWS tools throughout the process.

Challenge

Building and managing cloud infrastructure can be daunting, especially when considering the need for security, scalability, and adherence to specific organizational or industry standards. The key challenges faced by users include:

1.        Complexity in Infrastructure Design: Translating business requirements into cloud infrastructure often requires deep expertise in Terraform, cloud platforms (such as AWS), and security standards.

2.        Compliance: Ensuring the infrastructure complies with NIST 800-53 regulations or internal security guidelines often leads to lengthy reviews and auditing processes.

3.        Iterative Feedback: Infrastructure code must be tested to ensure that it runs correctly in a specific environment. This requires multiple iterations of “terraform plan” and code adjustments, which can be time-consuming.

4.        User Control and Flexibility: While automation is crucial, many organizations also want control over the final product, with the ability to tweak the infrastructure code to fit specific needs or naming conventions.

Solution

BSC Analytics engineered TACE to tackle these challenges head-on. The solution was built around the following key elements:

1.        Natural Language Processing for Infrastructure Design:

TACE uses advanced Generative AI models to enable users to describe their cloud infrastructure needs in plain language. Whether it’s specifying virtual networks, storage solutions, or security groups, the TACE engine can interpret user requests and translate them into Terraform code.  BSC Analytics elected to build their solution on AWS utilizing AWS Bedrock for several reasons, including the availability of multiple models that are used in various places in the application, the easy customizability that can be achieved on these models, and the security and compliance that comes as part of the Bedrock service.

2.        Pre-Hardened and Audited Terraform Modules:

A core feature of the TACE engine is its use of pre-hardened and audited Terraform modules, certified for compliance with industry standards like NIST 800-53. These modules form the building blocks of the infrastructure, ensuring that every piece of code generated is secure and compliant from the start.

3.        Reiterative Reasoning Loop:

TACE includes a powerful reiterative reasoning loop, which takes the Terraform code generated by the AI and runs several iterations of the Terraform plan to validate the infrastructure. This ensures that the code will work in the customer’s specific environment, identifying and resolving potential issues before the code is deployed.

4.        Full User Control:

While TACE automates much of the infrastructure design process, users retain full control over the final Terraform code. They can review, edit, and fine-tune the code before submitting it to a version control repository. Additionally, users can customize the pull request names and descriptions, ensuring the code adheres to organizational standards or naming conventions.

5.        Seamless Integration with CI/CD Pipelines:

Once the code is finalized and submitted to the customer’s repository, it flows through their existing CI/CD pipelines. The pipelines are configured to handle the infrastructure deployment while running the necessary security, compliance, and standards testing. This ensures that every piece of infrastructure code deployed meets security guidelines without needing manual intervention.

Conclusion

BSC Analytics’ Terraform Automated Compliance Engine (TACE) revolutionizes the way organizations approach cloud infrastructure. By combining the power of Generative AI with a repository of pre-hardened Terraform modules, TACE simplifies the design and deployment of secure, compliant infrastructure. Its built-in reasoning loop further ensures that the code works as intended, reducing deployment errors and saving time.

Importantly, TACE provides users with the flexibility to modify and control their infrastructure code, ensuring that the final product meets their unique requirements. Once deployed through CI/CD pipelines, the infrastructure is automatically validated and compliant with all necessary security standards.

The development of TACE demonstrates BSC Analytics’ commitment to leveraging cutting-edge AI technologies and AWS tools to drive efficiency, security, and compliance in cloud infrastructure management. By streamlining the entire process from design to deployment, TACE empowers organizations to build, test, and deploy compliant infrastructure faster and more securely than ever before.

Incorporating AWS tools at each step ensures that TACE benefits from AWS’s robust security, automation, and compliance offerings, delivering a complete solution for compliant cloud infrastructure deployment.

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