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This page explains how Compute Engine generates reservation recommendationsand the parameters to configure them.

Compute Engine provides reservation recommendations to help you identifyidle or underutilized on-demand reservations for the previous seven days so thatyou canmodify ordelete the reservations.

Compute Engine generates recommendations automatically based on systemmetrics gathered by the Cloud Monitoring service. You can configurereservations recommendations to receive more or fewer recommendations.

• To identify these recommendations and take action, seeView and apply idle reservation recommendationsorView and apply underutilized reservation recommendations.
• To configure these recommendations, seeConfigure idle reservation recommendationsorConfigure underutilized reservation recommendations.
• For an overview of Compute Engine reservations, seeAbout reservations.

Pricing

There are no costs associated with using idle reservation recommendations. Usingrecommendations to reduce your resource usage can result in cost savings. Thedisplayed cost savings estimate is your potential monthly savings if you adjustyour VM reservation to match your actual usage. For example, if youreserved 8 VMs but consistently use only 1, you see the cost savings ofdownsizing your reservation to 1 VM.

Limitations

Idle and underutilized reservation recommendations are not available for thefollowing reservations:

• On-demand reservations that are attached to committed use discounts (CUDs)
• On-demand reservations for virtual machine (VM) instances with TPUs

How detection of idle and underutilized reservations works

Reservation recommendations for Compute Engine are based onhistorical usage metrics. By default, the historical observation period isthe previous 7 days. By changing the default observation period, you cancustomize the recommendations that you receive.

To generate recommendations, the algorithm considers reservations that accruecosts, but aren't associated with an active Compute Engine resourcefor the previous 7 days.

Frequency of recommendations

After a reservation is created and you haven't consumed any resources for atleast 7 days, Compute Engine begins generating recommendations for it.New recommendations are generated once per day.

Customize recommendations

Compute Engine lets you customize the recommendations you receive foryour project by changing the configuration used by the recommendation algorithm.In particular, by changing the default observation period, you can receiverecommendations that better fit your workloads, applications,and infrastructure needs.

To learn how to modify the configuration for your project,see the following:

• Configure idle reservation recommendations
• Configure underutilized reservation recommendations.

Choose the right configuration

This section describes the values that you can set for the configuration.Changing these values affects the recommendations that you receive.

The observation period

Set the observation period duration to calculate recommendations by modifyingthe value foridle_reservation_lookback_period orunder_utilized_reservation_lookback_period and upload the newconfiguration for your project. You can set the observation periodto a value between 7 days and 30 days, for example:

• For an observation period of the previous 7 days, use"P7D".
• For an observation period of the previous 30 days, use"P30D".

By default, the observation period is 7 days.

• For recommendations based on short-term changes in your workload, use ashorter observation period.
• For recommendations that are not affected by short-term fluctuations in yourworkload, use a longer observation period.

Similarly, set the usage threshold that triggers an underutilized reservationrecommendation by modifying the value forunder_utilized_reservation_utilization_threshold and upload the newconfiguration for your project, for example:

• For a threshold of 80%,"0.8".

What's next

• Learn how toview and apply idle reservation recommendationsorview and apply underutilized reservation recommendations.
• Learn how toconfigure idle reservation recommendationsorconfigure underutilized reservation recommendations.