Prerequisites
Before you begin, install and verify the following tools.
Local development
To run AIDLC Collaborative locally, install the following tools.
| Tool | Version | Purpose |
|---|---|---|
| Node.js | 22 or later | Runtime for the frontend and Lambda functions |
| npm | 10 or later | Package manager (ships with Node.js) |
| Git | 2.x | Repository cloning and branch management for agent execution |
Run the following commands to verify your local development environment.
node --version # Expected output: v22.x or later
npm --version # Expected output: 10.x or later
git --version # Expected output: 2.x
AWS deployment
To deploy AIDLC Collaborative to AWS, install the following additional tools. For detailed deployment instructions, see Setup.
| Tool | Version | Purpose |
|---|---|---|
| Terraform | 1.0 or later | Infrastructure provisioning |
| AWS Command Line Interface (AWS CLI) | v2 | AWS resource management and credential handling |
| Docker | 20.10 or later | Lambda packaging and container builds |
Run the following commands to confirm your deployment tools are installed.
terraform --version # Expected output: v1.0 or later
aws --version # Expected output: aws-cli/2.x
docker --version # Expected output: Docker version 20.10 or later
You must also have an AWS account with permissions to manage the following services.
| Category | Services |
|---|---|
| Compute | AWS Lambda, Amazon ECS with Fargate, AWS Step Functions |
| Networking | Amazon VPC, Amazon API Gateway (REST and WebSocket), Amazon CloudFront, Elastic Load Balancing |
| Storage | Amazon S3, Amazon DynamoDB, Amazon Neptune |
| Security | Amazon Cognito, AWS Identity and Access Management (IAM), AWS Secrets Manager, AWS Systems Manager Parameter Store |
| Integration | Amazon EventBridge, Amazon Elastic Container Registry (Amazon ECR), Amazon SQS |
| Observability | Amazon CloudWatch Logs |
Optional tools
The following tools are optional. Install them to enable additional features.
| Tool | Purpose |
|---|---|
| AWS credentials | Required for large language model (LLM) features through Amazon Bedrock |
| GitHub personal access token | Enables pushing tasks as GitHub issues and syncing issue status |
Agent authentication
Agents authenticate using API keys configured through the platform UI. The platform supports two options:
An agent CLI cannot start until its credential is configured. The platform runs a pre-flight check before dispatching a job and blocks it with a clear error if the credential is missing, so set the relevant value below before starting agents for a project.
Kiro CLI API key (required for the Kiro CLI driver)
Kiro API keys are turned off by default. A Kiro administrator must first enable them in the Kiro console (Settings → Kiro settings → Enable users to generate API keys → On). Users can then sign in to the Kiro portal and generate a key. See the Kiro API keys documentation for details.
In the platform settings, enter this key as the Kiro API Key. Agent containers use it to authenticate with the Kiro CLI during Construction, and the driver validates it at startup with kiro-cli whoami.
Amazon Bedrock API key (required for Claude Code and OpenCode setups)
Generate an Amazon Bedrock API key in the AWS Console (Amazon Bedrock → API keys → Generate long-term API key, scoped to your account and region). In the platform settings, enter this key as the Bedrock Bearer Token. The platform stores it and provides it to agent containers as the AWS_BEARER_TOKEN_BEDROCK environment variable.
This token is required for Claude Code and OpenCode agents: the ECS task IAM role intentionally has no Amazon Bedrock permissions, so there is no IAM-role fallback. Agents authenticate to Bedrock exclusively through this token.
Where these values are stored
Both credentials are stored in AWS Systems Manager Parameter Store as SecureString parameters: /<project_name>/<environment>/bedrock-bearer-token and /<project_name>/<environment>/kiro-api-key. An unset credential holds the literal value placeholder, which the platform treats as "not configured." Saving an empty value in the platform settings resets the parameter to placeholder rather than deleting it.
AWS credentials for LLM features
AIDLC Collaborative uses Amazon Bedrock to access Claude models. You must have valid AWS credentials with Amazon Bedrock access in your environment.
If you don't have AWS credentials, the platform still starts. You can browse the UI, create organizations and projects, and manage specs. However, the large language model (LLM) chat and agent features return a connection error.