Deploying to AWS Lambda

Learn how to deploy your trading algorithm to AWS Lambda using the built-in iaf CLI, with an S3 bucket for state persistence.

Prerequisites

• AWS credentials configured (via aws configure or environment variables)
• Python 3.10+ and boto3 installed (pip install investing-algorithm-framework[aws])
• Docker installed (for building the deployment package)

Scaffolding a Project

Use iaf init --type aws_lambda to generate a Lambda-ready project skeleton:

iaf init --type aws_lambda

Options

Option	Default	Description
--type	default	Use aws_lambda for this template.
--path	Current directory	Path to the directory where the project will be created.
--replace	False	If set, existing files will be overwritten.

Generated Files

Everything from the default template, plus:

• app.py — Lambda handler entry point
• Dockerfile — Container image for Lambda deployment
• .dockerignore — Files to exclude from the Docker image
• requirements.txt — Includes boto3 and framework dependencies
• README.md — Lambda-specific deployment instructions

Deploying

The iaf deploy-aws-lambda command packages your project, creates (or updates) an AWS Lambda function, and sets up an S3 bucket for state persistence.

Command

iaf deploy-aws-lambda \
  --lambda_function_name my-trading-bot \
  --region us-east-1

Options

Option	Required	Default	Description
--lambda_function_name	Yes	—	Name of the Lambda function to create or update.
--region	Yes	—	AWS region (e.g., us-east-1, eu-west-1).
--project_dir	No	Current directory	Path to the project directory containing your code.
--memory_size	No	3000	Memory allocation in MB for the Lambda function.
-e KEY VALUE	No	—	Environment variables. Can be repeated: -e API_KEY xxx -e SECRET yyy.

What It Does

1. Packages your project code into a deployment zip.
2. Creates an IAM role for Lambda execution (if it doesn't exist).
3. Creates an S3 bucket for state storage (named after the function).
4. Deploys the Lambda function with the specified memory and environment variables.
5. Sets the AWS_S3_STATE_BUCKET_NAME environment variable on the function automatically.

Example

# Deploy with environment variables for exchange credentials
iaf deploy-aws-lambda \
  --lambda_function_name btc-trading-bot \
  --region eu-west-1 \
  --memory_size 3000 \
  -e BITVAVO_API_KEY your_key \
  -e BITVAVO_SECRET_KEY your_secret

Environment Variables

Store exchange API keys and other secrets as environment variables rather than in code. Pass them with the repeatable -e flag during deployment:

iaf deploy-aws-lambda \
  --lambda_function_name my-bot \
  --region us-east-1 \
  -e BITVAVO_API_KEY your_key \
  -e BITVAVO_SECRET_KEY your_secret

Next Steps

With your bot deployed, refer to the Trading Strategies and Backtesting documentation to refine your algorithms, or head back to the Going Live overview.