Enhancing AWSCC provider documentation with GenAI

The AWS Cloud Control (AWSCC) provider for Terraform hosts an incredible 1000+ resources, all of which are generated from their respective schemas, with rapid time to market. But: where code is "easy" to generate, documentation often wasn't and required manual, tiresome worked that simply couldn't keep up with the development speed. Two years ago, we started to augment the provider documentation efforts with a handful of GenAI techniques. Join this session to learn how we take advantage of LLMs to assist in enriching the provider documentation, what prompt techniques worked for us, and how you can replicate this for your own projects.

Deployment patterns with Terraform and GitHub Actions for public and private infrastructure

The session aims to introduce
1. VCS workflow with AWS Dynamic Credentials
2. CLI based workflow :
2.a : GitHub actions structure/deployment templates
2.b : Trunk based with feature flags using GitHub environments and variables.
2.c : On-demand workflows for deploying to higher lifecycle environments.
2.d : HCP Terraform components to consider for application and platform teams
2.e : Deployment into private infrastructure using Cloud agents
3. AWS & AWSCC provider

Deploy your AI ( and non AI) workloads in AWS using Terraform AWS Cloud Control provider

We will look into the AWSCC Terraform provider to provision workloads to support AWS resources and feature coverage as soon as a week into the announcement.

Bake security and compliance into your automation

In today's rapidly evolving technology landscape, where infrastructure and applications are increasingly deployed through code-driven automation, the importance of incorporating security measures into this process cannot be overstated. As organizations embrace the power of Infrastructure as Code (IaC) and streamlined deployment scripts, the potential for security vulnerabilities to slip through the cracks has grown exponentially. Traditional security approaches, relying on manual reviews and ad-hoc security checks, often struggle to keep pace with the speed and complexity of modern infrastructure deployments. This is where the integration of security into the automation process becomes vital. By proactively addressing security concerns within the code that defines the infrastructure, organizations can ensure that security is an inherent part of the development process, rather than an afterthought. We will explore some common themes around incorporating these in your organization from the IDE of a developer to your deployment pipeline.

AWS Cloud Control provider: Tackling the treadmill problem

Introducing the AWSCC provider for Terraform to support the feature gaps on resource support for services/features which are currently not available with the standard AWS provider.

Target audience : Anyone deploying workloads to AWS using Terraform

Ephemerality in Terraform

Lets discuss what ephemerality means in HCP Terraform and Terraform. We will review security policies which can nudge your organization to adopt these if they are using non-ephemeral resources. And yes, this is across all of the providers which have some form of ephemeral resources.

Guard Rails via Chat: Crafting Security Policies for your infrastructure with Amazon Q

Discover how to leverage Amazon Q chat to streamline your AWS security policy creation process among other productivity improvement applications. This session demonstrates the practical application of crafting Policy as Code using Sentinel policy language or checkov checks( Python based) for HashiCorp Terraform AWSCC Provider. Learn how conversational AI can accelerate the development of infrastructure guardrails, helping teams efficiently scale their security policy implementation while preventing common misconfigurations. We'll demo the actual implementation , share the available policies for teams to use right away, and lessons learnt from using Amazon Q to automate and enhance policy creation workflows.

Key Focus Areas:

* Introduce AWSCC provider for Terraform, Sentinel and Checkov
* Implementing Policy as Code for the Terraform AWSCC Provider ( CIS, Foundational Best practices and so on)
* Leveraging Amazon Q for policy generation and validation
* Lessons learnt

Making AI Work for You: Terraform Engineer Blueprint

AI coding assistants for Terraform often give inconsistent results. This session shows proven techniques for reliable infrastructure code using AI. Learn practical strategies: repository context, reusable prompts, MCP servers, and validation workflows. See live demos with Amazon Q Developer covering provider
contributions, module building, and troubleshooting. Get actionable templates and skills that work across any AI assistant.