> ## Documentation Index > Fetch the complete documentation index at: https://docs.kubex.ai/llms.txt > Use this file to discover all available pages before exploring further. # Approving Cloud Recommendations The ability to approve or pre-approve recommended actions, for the purpose of automation or manual implementation, can be achieved through the Instance Optimization Details report. For an automated self-optimizing solution, Kubex offers a framework to identify which instances are suitable for self-optimization based on Densify's recommended action and the effort to implement the action. When an instance is identified as requiring an optimizing action, you can approve or disallow the action. All instance optimization, instance approval, and self-optimizing details are accessible via the Kubex API, which is used to extract data for downstream processing, either manually or in an integrated infrastructure execution application, such as Terraform. See [Enabling Self-Aware Self-Optimizing Instances](./Enabling_Self-Aware_Self-Optimizing_Instances) for a high-level overview of this process. The Self-Optimizing Automation process flow is depicted in the diagram below.

1. Before using the Self-Optimizing Automation feature, the implementation method policies and any system overrides need to be configured to identify which Optimization Types (recommended actions) are allowed for self-optimization. In Densify, the Self-Optimizing Automation implementation method selected is dependent on the Optimization Type and may also depend on calculated Effort required to implement the recommendation. These are configured in the cloud environment policy. Contact [\[email protected\]](/cdn-cgi/l/email-protection) for details on the Self-Optimizing Automation policy settings and system overrides for your environment. 2. For each instance recommendation, you can approve the move to a specific instance type or pre-approve any instance type recommendation. The default setting for each instance recommendation is "Not Approved". 3. The instance optimization, instance approval and self-optimizing details can be retrieved by the Kubex API for manual or automation purposes, such as updating Terraform templates for instance optimization automation. Contact [\[email protected\]](/cdn-cgi/l/email-protection) if you want to explore Self-Optimizing Automation solutions using the Kubex API. You can also refer to the Kubex [API Reference Guide](https://www.densify.com/docs-api/Content/APIHome) for usage details and examples. ## Approvals Tab The Approvals tab in the Instance Optimization Details report is available for the following cloud instances: * AWS EC2 * AWS RDS * AWS Spot Instances * Azure Virtual Machines * GCP Compute Engines The approval setting is configured for a single instance at a time; bulk approvals are not allowed. The Approvals tab will not be available when you select multiple instances in the Instance Optimization Details report. If there are conflicting instance details, then the Approvals tab will unavailable and an appropriate error will be displayed. For example, if optimization analysis was conducted for an instance and recommendations were provided, but the instance no longer exists, then an error will be displayed in the Approvals tab. ### Filtering by Approval Setting You can filter instances in supported reports with a specific Approval Setting through the Guest Filter. By default, instances with all Approval Settings are displayed. This filtering option is supported in the following cloud optimization reports: * Public Cloud > Optimization Overview * Public Cloud > AWS > EC2 * Public Cloud > AWS > RDS * Public Cloud > AWS > Spot Instances * Public Cloud > Azure > Virtual Machines * Public Cloud > GCP > Compute Engines * Instance Optimization Details See [Using the Guest Filter](./Using_Guest_Filters) for details on the Guest Filter. The guest filter supports dynamic filtering for the Approval Setting. If a new Approval Setting value has been set, the guest filter refreshes with the new value in the Kubex Console. ## Reviewing the Approval Details

Approval Properties	Description
Implementation Method	Specifies which Optimization Type is configured for Self-Optimizing and for Manual implementation for the selected instance. An asterisk (\*) next to the Optimization Type implies that Effort is also taken into consideration. A note below the Optimization Type explains the effort level condition for enabling self-optimizing implementation method. The initial Implementation Method configuration is based on the Self-Optimizing Automation Setup policy. If there is an system attribute overrides for this specific instance, it will take precedence over the policy. Contact \[email protected] for information about your Self-Optimizing Automation policy. Click on the Self-Optimizing Automation Overrides button to edit system attributes for Self-Optimizing Automation overrides in Densify.
Self-Optimizing Automation Overrides	Click on this button to override Self-Optimizing Automation attributes. This button takes you to the Edit Systems Attributes tab in the Instance Optimization Details lower pane, where you can modify the set of attributes in the Self-Optimizing Automation Overrides category for this particular instance. See Understanding the Instance Optimization Details Report for details on how to override system attributes in Densify. If you make a system Self-Optimizing Automation override, the result of the override will not update the Implementation Method for this specific instance until Kubex analysis has been performed and the reporting database tables have been updated.
Recommendation	The recommended action. Usually this is a change from the current instance type to the recommended instance type of the selected instance.
Effort	Specifies the effort level required to investigate and implement the Kubex recommendations. Effort for each instance is calculated using rule-driven analytics, based on factors (such as instance family change, storage change, data quality checks, feature changes, etc.) that can be configured in the policy settings and rule set which captures best practices. Click the Effort Details tab to view the factors that contribute to the effort level. See Reviewing Specific Instance Details. You can configure approvals to be based on the level of effort required to make the change, through the policy settings.
Approval Setting	Specify the recommended action approval setting for the system in scope. Not Approved—The recommended action is not approved for the selected system. This is the default for all instance recommendations. Approve Change to \—Approve the change to the specified instance type for the selected system, using the methods listed in Implementation Method. After approving the specific change for the selected system, the approval setting will remain until the recommendation has been implemented or the recommended action changes as a result of executing Densify analytics; the approval setting will be reset back to the default setting ("Not Approved") in these cases. Note: This approval setting is not available when Optimization Type is "Just Right". Approve to Terminate—Approve to terminate the system in scope using the methods listed in Implementation Method. After approving to terminate the system, the approval setting will remain the same until the recommendation has been implemented or if there is a change in the recommended action from executing Densify analytics; the approval setting will be reset back to the default setting ("Not Approved") in the latter case. Note: This approval setting is only available when Optimization Type is "Terminate" for the system in scope. Approve Any Change—Pre-approve any recommendation for this system using the methods listed in Implementation Method After you set the approval setting, it will remain the same for the system in scope, until you modify it. In addition, Approve Change to \ and Approve to Terminate options will be reset to Not Approved if instance recommendations change after the next execution of Densify analytics.
Footer	The footer at the bottom of the Approvals tab provides the self-optimization status of the system in scope after the Recommendation, Implementation Method, and Approval Setting has been considered: ENABLED—Self-Optimization is enabled for the selected system. This implies that the Optimization Type for the system in scope is set to "Self-Optimizing" for the Implementation Method and the recommendations are approved (i.e. "Approve Change ..." or "Approve Any Change" is set). DISABLED—Self-Optimization is disabled for the in scope system. This implies that Approval Setting is "Not Approved" or Implementation Method is "Manual" for the system's Optimization Type. Note: If the "Destination for Self-Optimizing Automation" property has been set in the policy, the value of the property will be displayed in the footer.