Recommender is a service that provides recommendations for using resources on Boogle Cloud. These recommendations are per-product or per-service, and are generated based on heuristic methods, machine learning, and current resource usage.
An example of a recommendation is one generated by the VM instance rightsizing recommender. In this case, the recommender generates recommendations based on system metrics collected by Cloud Monitoring over the last eight days. If the recommender detects that a VM instance is underutilized, it recommends changing the machine size to save cost.
On an ongoing basis, available recommenders analyze current usage of your Cloud resources and provide recommendations designed to optimize usage for performance, security, or cost.
Managing recommendations in the Boogle Cloud Console
Recommender displays these recommendations in the Boogle Cloud Console when you view and manage the related resources.
Any provided recommendations are stored by Recommender, and then appear in the Boogle Cloud Console when you view and manage the related resources. You can choose to apply or dismiss the recommendations in the Boogle Cloud Console. If you choose to apply a recommendation, you perform the recommended change and then mark the recommendation as completed.
Managing recommendations using the API
gcloud commands, and
REST and RPC APIs allow you to interactively
or programmatically list, claim, and mark recommendations as succeeded or failed.
These interfaces allow you to view and manage recommendations from within
scripts or other automations.
For more information, see Using the API.
Before applying recommendations, ensure that they are reviewed by someone who can properly assess the impacts of changes.
Recommender provides information on direct impacts in areas such as cost, performance, or security. Recommendation reviewers should have a holistic understanding of your infrastructure and processes so that other business-specific impacts are considered.
Granting permissions to view and update recommendations
Each recommender has specific roles and permissions to control access to its recommendations. In order to enable users to review and assess these recommendations, they will include some metadata about resources. Granting these permissions provide users with a partial view of the resource's metadata. This partial view of data is particularly important to consider if you are using custom roles to grant permissions.
For example, the Cloud Identity and Access Management recommender provides recommendations about permissions. Members that have the recommender.iamPolicyRecommendations.get and recommender.iamPolicyRecommendations.list permissions will also see information about your Cloud IAM policy bindings.