Optima Recommendations helps you discover and realize saving opportunities to reduce your cloud spend. It includes a variety of features, including:

  • Optimizing costs across all of your clouds
  • Automated recommendations
  • Ad hoc sharing recommendations with team members
  • Customization of recommendations
  • Noise reductions to prevent future alerts on specified items

Accessing Optima Recommendations

Optima provides you recommendations at different levels of granularity to make it easier to take actions.

  • Organization level view: If you wish to see all recommendations for your RightScale Organization, navigate to optima.rightscale.com. You will need actor role (organization scope) to edit recommendations settings and observer role (organization scope) to view recommendations.

  • Billing center level view: If you wish to see recommendations, specific to a billing center, simply navigate to the billing centers from analytics.rightscale.com and you will see a Recommendations tab within each billing centers. You can learn more about billing center recommendations here.

How Recommendations Work

RightScale Optima includes a recommendations engine that embodies a number of rules that analyze cloud consumption data and produce recommendations for reducing costs. The set of rules is fixed and provided by RightScale but each rule can be customized using settings. These settings have defaults provided by RightScale but can be changed to fit each organization's business needs. For example, one of the rules recommends the use of cheaper regions (AWS Ohio is cheaper than AWS Toronto) and for many organization this rule can flag waste, but clearly for some organizations the use of the Toronto region is intentional. These organizations can modify the setting that maps expensive to cheaper regions to better reflect their needs.

Each rule in Optima can produce many recommendations and, in general, a rule produces one recommendation per cloud resource. For example, the rule that flags instances that could be relaunched in a cheaper region produces one recommendation per instance. The recommendations are grouped by rule in the UI and can be filtered to provide an overview about the savings embodied by all recommendations produced by a rule. Having a separate recommendation for each resource makes it easier to dole out specific recommendations to the appropriate stakeholders, to track the status of each affected resource, and to hook-up automation.

In order to calculate savings, Optima uses an estimated current monthly run-rate that is generally calculated over the 7 days preceding the last available data. In essence, recommendations state that if the consumption were to continue indefinitely at the same rate as observed over the past 7 days then by following the recommendation monthly savings of the specified value would be obtained. The monthly run rate includes monthly and daily up-front costs as well as hourly costs (for example, many AWS EC2 reserved instances have a monthly cost and it is common for the run-rate of an instance to be a combination of a portion of this monthly cost and hourly costs).

In addition to settings, Optima also allows individual recommendations to be ignored and patterns to be written to automatically ignore recommendations. There is a subtle difference between settings and ignoring, which is that settings prevent a recommendation from being issued while ignoring a recommendation just marks it as ignored. The ignored recommendations remain part of the user's workflow in Optima in that it is easy to see the value of all ignored recommendations and to come back to them later by placing an expiration on the ignore status. As an example, a setting to recommend moving usage from the AWS N. California region to the cheaper AWS Oregon region may make sense for an organization in general, but a small set of resources tagged norcal may need to remain there for latency reasons, and another set may need to be moved but need to wait 3 months for personnel to become available. In such a situation an ignore pattern based on the tag can auto-ignore the first set of resources, and a manual ignore with a 3 month expiration can provide a reminder for the second set. The forgone and impending savings remain visible at any point in time by checking the ignored recommendations in the Optima UI.

The recommendations produced by Optima, as well as the settings and ignore patterns that modify them, are organization-wide, meaning that all users see the same recommendations based on the same settings and with the same status (active, ignored, etc). This ensures that when recommendations are shared between users all parties see the same data.

RightScale Optima uses two primary data sources for helping you manage costs:

  • Bill data: Bill information is collected from your public cloud provider to enable an accurate view of all of your costs across your accounts and services.
  • Usage data: Usage data is collected from RightScale Cloud Management to provide additional detail for slicing and dicing costs across many different dimensions.

Recommendations in Optima operate on either Bill data or Usage data depending on the recommendation.

However, the existing functionality from Optima operates on both Bill data and Usage data. Follow the instructions below to connect both bill and usage data.

Recommendations Based on Bill Data

Public cloud providers publish billing data as a CSV or JSON dataset on a semi-regular schedule, typically once to 3 times daily. This billing data covers all month-to-date usage up to some time-point a few hours before the dataset was produced. Optima automatically ingests the latest dataset and produces recommendations based on the last consistent hour found in the dataset. It also regenerates all recommendations based on the latest available dataset when any settings are changed to ensure that the new settings are taken into account. The result of this process is that the data on which the recommendations are based may be anywhere from a few hours to 36 hours in the past.

There are two major benefits to using bill data to produce recommendations:

  • in one operation all consumption across all services in all regions in all linked accounts becomes visible
  • the cost information is based on actuals reported by the cloud vendor

The disadvantages of using bill data and the reason for also using usage data are:

  • the data is always a few hours old
  • the granularity is limited and only allows a restricted set of recommendation rules

Recommendations Based on Usage Data

For some recommendations, detailed usage data from the cloud provider is required in order to evaluate the recommendation conditions. In such cases, RightScale requires vendor account-level credentials for every account in which you wish to see recommendations generated. In all cases for recommendations, read-only credentials will suffice for recommendation generation. See the Connecting Clouds section below for more information.

When using usage data for recommendations, resources are polled on a frequent schedule to ensure up-to-date information. For example, the unattached volumes recommendation polls every couple of minutes.

Connecting Clouds

Connecting Bill Data

Provider Instructions
AWS Hourly Cost and Usage CSV Reports
Azure Azure Enterprise Agreement
Google Billing CSVs

Usage Data

List of Optima Recommendations

Optima provides automated recommendations that identify areas where you can save costs. Optima includes a set of predefined Recommendation Rules. Select a rule to see the detailed list of individual recommendations and what the total potential monthly savings would be if the recommendations were implemented.


The current rules include:

Recommendation Rule What It Does Source Data
Low Account Usage Identifies accounts with spend below a configurable threshold. This can represent tests or experiments that can be terminated or usage that can be consolidated into other accounts. Cloud bill only
Low Service Usage Identifies specific cloud services in a particular region with spend below a configurable threshold. This can represent tests or experiments that can be terminated or usage that can be consolidated into other accounts. Cloud bill only
Disallowed Usage Identifies combinations of clouds, accounts, regions, and services that are not allowed according to your organization’s policies. This usage can be investigated for potential termination. Cloud bill only
Cheaper Regions Identifies instances in regions where there is a nearby region with lower costs. These resources can be moved to the less expensive region. Cloud bill only
Superseded Instance Type Identifies older instance types that can be migrated to newer, better, and less expensive instance types. Cloud bill only
Schedule Instances Idenitfies instances that can be stopped or terminated outside of business hours to save on cost. Cloud bill only
Unattached Volumes (AWS Feature Only) Idenitfies volumes that are unattached and can be deleted to save on cost. Usage data only

Reviewing Recommendations

Once you select a recommendation rule from the list, you can review what the individual recommendations and the potential savings would be if that recommendation were implemented.

You can filter the list of recommendations and select View Details to see more information about the recommendation.


Exporting Recommendations as CSV

When reviewing recommendations you can further analyze the data by exporting the information to CSV. You can do this in one of two different ways:

  1. Download a CSV of all recommendations. This can be done by clicking Export all to CSV at the top of the page.
  2. Download a CSV of recommendations based on a specific Recommendation Rule. This can be done by clicking Export to CSV at the top of the table. Note Filters will not be applied to any exports. If you use the filter recommendations functionality under a specific Recommendation Rule and click the Export to CSV, you will receive a full unfiltered export of the currently selected Recommendation Rule.


The same fields are exported for every recommendation type, regardless of whether that field applies to that specific recommendation. If a field is blank, it generally means that field does not apply to that recommendation type. As such it is not unusual to see blank fields dependent on the relevance of that field to a particular recommendation.

Recommendation Details

For each recommendation, you can access all of the information about that recommendation from the Recommendation Details panel. The data at field in the table at the top of the recommendation indicates which hour of data from the cloud bill was used to make the recommendation. The refreshed at field indicates when the recommendations engine was last run, e.g. taking the latest data and latest settings into account.


Configuring Recommendation Rules

You can configure Rule Settings for each of the recommendation rules. Choose the rule you want to configure and use the gear icon above the recommendations list. Each recommendation rule has default settings, but you can adjust the settings for your organization. You must have an actor role on the RightScale organization to change settings.

See Optima Recommendations details for specifics on how to configure each rule and how it works.

Optima Recommendation Actions

Optima has the ability to analyze usage, provide cost savings recommendations, and allow for recommendations to be acted upon: Optima Recommendation Actions

Optima Recommendation Rules Details

RightScale Optima provides a set of recommendations based on a set of rules. Most rules have rule settings that can be configured to tailor the set of recommendations produced. Optima Recommendation Rules Details