Customers are responsible for making their own independent assessment of the information in this document and repository.
This document and repository:
(a) is for informational purposes only,
(b) represents current AWS product offerings and practices, which are subject to change without notice, and
(c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers.
(d) is not to be considered a recommendation or viewpoint of AWS
Additionally, all prototype code and associated assets should be considered:
(a) as-is and without warranties
(b) not suitable for production environments
(d) to include shortcuts in order to support rapid prototyping such as, but not limited to, relaxed authentication and authorization processes
All work produced is open source. More information can be found in the GitHub repo.
This project will use a simple git branching strategy and naming convention.
Branches should be in the following format.
{category}/what-it-is-addressing
Example categories: | Branch | Description |
---|---|---|
hotfix | For quickly fixing critical issues, usually with a temporary solution | |
bugfix | For fixing a bug | |
enhancement | For adding, removing or modifying a enhancement | |
test | For experimenting something which is not an issue | |
wip | For a work in progress |
Reference Site: https://waterbot-stream-bda64cf22bc1.herokuapp.com/
Not tracked on github; dynamic based on deploy.
#!/bin/sh
aws ecr get-login-password --region {region} | docker login --username AWS --password-stdin {act_num}.dkr.ecr.{region}.amazonaws.com/{repo}
Give it run permissions: chmod +x ecr_auth.sh
Grab additional software
sudo apt-get install jq
Set your environment variables
export AWS_ACCESS_KEY_ID=""
export AWS_SECRET_ACCESS_KEY=""
export AWS_SESSION_TOKEN=""
export OPENAI_API_KEY=""
export SECRET_HEADER_KEY=""
export BASIC_AUTH_SECRET=""
export MESSAGES_TABLE=""
export CLUSTER_NAME=""
export SERVICE_NAME=""
_Note: You won't know CLUSTER_NAME, SERVICE_NAME, MESSAGES_TABLE until post deployment; these variables are only necessary for fargate_updatecluster.sh script
cd application
python3.11 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
fastapi dev main.py
_Note: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN, OPENAI_API_KEY, MESSAGES_TABLE must be set; you can place OPENAI_API_KEY and MESSAGESTABLE in your .env file
./docker_build.sh
./docker_run.sh
Note: You will need CDK preqruisites.
Reference: https://cdkworkshop.com/
1) Bootstrap CDK
2) cdk deploy cdk-ecr-stack
3) ./docker_build.sh
4) ./docker_run.sh (to test)
5) ./ecr_auth.sh
6) https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html
----> docker tag {container_id} {act_id}.dkr.ecr.us-east-1.amazonaws.com/{repo}:latest
----> docker push {act_id}.dkr.ecr.us-east-1.amazonaws.com/{repo}:latest
7) build rest of cdk stack
----> cdk deploy '*'
The stack has the ability to deploy out multiple instances if necessary. By default, env is null and CDK will deploy out a "cdk-{name}-stack"; if context is set, a new instance with "cdk-{name}-stack-{env} will deploy out
# Deploy for dev environment
cdk deploy {stack_name}-dev --context env=dev
# Deploy for staging environment
cdk deploy {stack_name}-staging --context env=staging
# Deploy for production environment
cdk deploy {stack_name}-prod --context env=prod