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recommender-iac-pipeline-nodejs-tutorial's Introduction

GCP Recommender and IaC pipeline integration

This repository contains the code to build an automation pipeline that comprises of the recommdender-parser service hosted in managed Cloud Run and other ancillary GCP services. The service is invoked by scheduled Cloud Scheduler jobs. This service calls the Recommender API to retrieve Recommender recommendations for the projects that you specify.It parses these VM rightsizing and IAM role recommendations to map them to the configuration you have in your Terraform manifests. It updates your IaC manifests to reflect these recommendations and generates a pull request for your to review and merge. Once you review and merge the pull request, a Cloud Build job rolls out the changes to your infrastructure in your GCP organisation

How to use this example

Use the tutorial to understand how to configure your Google Cloud Platform projects to use this pipeline.

  1. Check it out from GitHub.
  2. Create a new local repository and copy the files from this repo into it.
  3. Develop and enhance it for your use case

Quickstart

Clone this repository

git clone https://github.com/GoogleCloudPlatform/recommender-iac-pipeline-nodejs-tutorial.git

Change directory to one of the included directories

Follow the walkthrough in the tutorial associated with the Nodejs example for configuration details of Cloud platform products (Cloud Storage, Cloud Run, Cloud Build and other ancillary services) and adapt accordingly using the accompanying README for each example.

The following sequence diagram outlines the key interactions in the functions called by this service. Please note that the interactions are specifically outlined for 'IAMRoleBindings' flow. The VM rightsizing flow follows a similar interaction pattern.

Recommender service sequence diagram:

License

Copyright 2019 Google LLC

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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