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02_INFRASTRUCTURE_DEPLOYMENT.md

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Plan: Infrastructure Deployment

Status: ✅ COMPLETED
Date: 2025-11-23

1. Task Description

Deploy the core AWS infrastructure required to support the Generative AI application. This includes storage for vector embeddings (if needed) or documents, and the compute layer for the AI logic.

Requirements

  • Use Terraform for Infrastructure as Code (IaC).
  • Deploy to us-west-2 (or configured region).
  • Resources:
    • S3 Bucket: For storing documents/assets.
    • Lambda Function: For handling chat requests and streaming responses.
    • CloudFront: For content delivery and lightweight validation (CloudFront Functions).

2. Implementation Plan

Architecture

  • Location: /infra
  • State Management: Local state (for now).

Files

  • infra/provider.tf: AWS Provider configuration.
  • infra/variables.tf: Project variables.
  • infra/main.tf: Resource definitions.
  • infra/lambda-chat.tf: Chat Lambda configuration.
  • infra/cloudfront.tf: CloudFront distribution.
  • infra/ecr.tf: ECR Repository.

Steps

  1. Define Resources: Update main.tf to define the S3 bucket and basic Lambda execution role.
  2. Initialize: Run terraform init.
  3. Plan: Run terraform plan to preview changes.
  4. Apply: Run make deploy to provision resources.

3. Verification Plan

Infrastructure Validation

  • terraform validate passes.
  • make deploy completes successfully.

Functional Testing (via Notebook)

  • S3 Access: Use infrastructure_test.ipynb to verify the created bucket is accessible and writable.
  • Create Embeddings: Verify that embeddings can be generated and stored (Pending).
  • Lambda Invocation: Test invoking the Lambda function directly via AWS SDK.

Credits

Created by Warike technologies