Collection of some scripts to automate AWS Lambda and API Gateway deployments
Project description
AWSDeployer
Collection of some scripts to automate AWS Lambda deployments. They are useful for quick development and deployment of AWS Lambda functions and layers, as well as a REST API Gateway integration.
Just set your working directory, your awsdeployer configs and you should be good to focus on actual development.
Currently only supporting Python lambda functions.
Lambda Deployer
Easily deploy Lambda functions and their layers.
Usage
These scripts assume a working directory like that of sample_lambda:
awsdeployer.ini
file with your secrets (see sample file)awsdeployer_lambda.json
with your layer and function configurationsfunction_name.py
files, one for each of your Lambda functions
The executable is lambda
, which accepts the following commands:
$ lambda layer <layer-name>
: deploy layer "layer-name" into AWS (requires docker to build)$ lambda config [<function-name>]
: update all function configs in AWS (specify a function name to only update that function's configs); non-existing functions are created (default Lambda IAM permissions)$ lambda <function-name>
: if no option above is matched, the specified function has its code and configs updated (probably the most common case); non-existing functions are created (default Lambda IAM permissions)
Tip: all parameters can be replaced by a shorthand, which you can specify in your awsdeployer_lambda.json
.
Configs
main_file
: specify the main function file (if not present, function_name.py is assumed)additional_files
: additional files to include with the main function file in the deployment
Environment packages
If you need to add the same set of variables to multiple functions (eg. database configurations) you can define a global pack of environment variables that you can then reference in each function that needs it. Example in samples/lambda/awsdeployer_lambda.json
Special layer building
If you need to build a specific package for your layer (eg. psycopg2) you can use pre and post build hooks for the layer build, and add docker arguments to the command.
To build psycopg2 compile it separately, then use these configs:
"layer_configs": {
"psycopg2layer": {
"requirements_file": "requirements.txt",
"requirements_ignore": ["psycopg2"],
"build_args": "-v ~/psycopg2-build:/bar",
"pre_build_command": "echo 'Something before pip'",
"post_build_command": "cp -r /bar /foo/python/psycopg2",
"common": true
}
}
API Gateway Deployer
Easily deploy API gateway, handling input parameters and error codes, so you can focus on the code.
Usage
These scripts assume a working directory like that of sample_apigateway:
awsdeployer.ini
file with your secrets (see sample file)awsdeployer_api.json
with your API definition in JSON (NOT nested!)function_xxxx.py
files, one for each of your Lambda functions associated with the endpoints
The apigateway
executable accepts two commands:
$ apigateway all
: deploy the full API (destroys already existing ones)$ apigateway <method> <path>
: deploy a single method (also destroys already existing ones)
The script also helps automating HTTP error codes, which you can find in status_codes.md
. They are automatically
deployed into API Gateway and caught by it, as long as you import the awsdeployer
package, as seen in sample_apigateway/get.py
.
If you're not using Python, your errors should follow the following JSON syntax to be caught effectively:
{
'gatewayResponse': True,
'status': 'error',
'type': _status_code_from_md_file,
'userMessage': your_user_message_which_can_be_empty
}
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