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This is an example code to demonstrate how to deploy serverless functions on AWS lambda using pipeline on Razorops.
It contains simple functions written in Python runtime and includes steps to deploy on AWS lambda service.
We've provided two functions defined in (python-1)[./python-1] and (python-2)[./python-2] directories based on Python runtime supported by Lambda service and automation to deploy them based on AWS.
Before deploying your changes via CI/CD pipeline, you need to create AWS credentials to enable access from the pipeline. You will most likely have a IAM user having the following policy linked to you lambda functions -
lambda:GetFunctionConfiguration
lambda:UpdateFunctionConfiguration
lambda:UpdateFunctionCode
lambda:PublishVersion
We have included terraform script to help you create a IAM role that can be used for deployment in pipeline.
After creating the IAM user, you can set AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY in pipeline's variables in the dashboard.
You can now simply change your code and commit to your main/master branch to trigger the deployment process. It would detect the folders in which you've made the changes and only deploy them if code for a function is changed.
git commit -a -m <mesage>
git push
If you're new to Razorops, feel free to fork this repository and use it to create a project.
.razorops.yaml contains the pipeline code to build and execute the tests for this project. To know more about how to write and customize, refer to the documentation. Here is the link of the pipeline workflows page.
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Distributed under the MIT License. See the file LICENSE.md.