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Serverless deployment of Node on AWS (HTTP) #701
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Layers contain all dependencies for the Node
Changed runtime to py3.6
- Returns an instance of FlaskLambda - FlaskLambda can handle events passed by triggers to the lambda function
* Added EFS, Access points, and mount targets * Would be used to store syft and dependencies
* Lambda is added to same VPC as EFS * Lambda can access the EFS via provided access point * Lambda can import dependencies stored in EFS
* Can import syft and it's dependencies including torch from numpy * Syft and dependencies are hosted on efs * efs is mounted on aws lambda * ec2 instance is used to install syft on efs
* Added sqlalchemy-aurora-data-api as a dependency in requirements.txt
* Private subnets would host the lambda function * NAT & Internet gateway would allow lambda to access AWS RDS via Data API * subnets in multiple availability zones allow high availability & fault tolerance
* Associated lambda to private subnets * Assosiated database to private subnets * Added EFS file system to private subnets * [Fix]: Lambda can access database * [Broken]: Lambda can't mount the EFS
* Initialize and seed the remote database
* Remove redundant permissions
*Fix: secretmanager:GetSecretValue permission
cereallarceny
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Sep 29, 2020
AmrMKayid
pushed a commit
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Dec 15, 2020
* Initial template * Add more params to modules * Organize files into folders * Separate resources into files * Add AWS Lambda layers Layers contain all dependencies for the Node * Solved Numpy import issue Changed runtime to py3.6 * Added Lambda compatible create_app() function - Returns an instance of FlaskLambda - FlaskLambda can handle events passed by triggers to the lambda function * Host packaged dependencies on s3 * Added Elastic File system * Added EFS, Access points, and mount targets * Would be used to store syft and dependencies * Integrated AWS Lambda with AWS EFS * Lambda is added to same VPC as EFS * Lambda can access the EFS via provided access point * Lambda can import dependencies stored in EFS * Successful import of syft and dependencies on AWS lambda * Can import syft and it's dependencies including torch from numpy * Syft and dependencies are hosted on efs * efs is mounted on aws lambda * ec2 instance is used to install syft on efs * Integrated database with Lambda * Added support for AWS secret manager * Added IAM policies to access database from lambda * Added bash script to create lambda layer zip file * Added sqlalchemy-aurora-data-api as a dependency in requirements.txt * Added VPC, Public & Private Subnets, NAT & Internet gateway * Private subnets would host the lambda function * NAT & Internet gateway would allow lambda to access AWS RDS via Data API * subnets in multiple availability zones allow high availability & fault tolerance * Lambda can access Database via Data API * Associated lambda to private subnets * Assosiated database to private subnets * Added EFS file system to private subnets * [Fix]: Lambda can access database * [Broken]: Lambda can't mount the EFS * Moved EC2 to a new folder * Added permissions to EFS access point * Added database to create_lambda_app() function * Initialize and seed the remote database * Fix: Register dialects before connecting to database * Tidy up .gitignore * Added flask-lambda-python36 & sqlalchemy-aurora-data-api as dependency * Merged back ec2 instance * Updated lambda layer dependencies * Clean and refactor IAM policies * Remove redundant permissions * Replace torch-gpu with torch-cpu *Fix: secretmanager:GetSecretValue permission * Added functionality to pull latest AMI id Co-authored-by: Patrick Cason <me@patrickcason.com>
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Description
Initial serverless deployment of Node on AWS.
Fixes #642
Affected Dependencies
flask-lambda-python36==0.1.0sqlalchemy-aurora-data-apiHow has this been tested?
Checklist