Analysis: Policy
Analysis: Policy
#340450
Description
- /analysis/cloud/aws/policy
- /analysis/cloud/gcp/policy
- /analysis/cloud/azure/policy
- /analysis/containers/kubernetes/policy
Policies are used to define the business and technical behaviors and requirements for optimization. Densify optimization analysis utilizes the platform-specific default policy employing industry best practices. You can use the returned policies from the platform-specific /policy resource to override the default policy used during an optimization analysis. Contact Densify support ([email protected]) to review your policy settings and to adjust or enable additional cloud policies for your environment.
The following cloud policies are available to the DevOps service tier:
- DevOps-Default—The default policy reflects best practices for generating actionable recommendations. Specifically:
- The resource utilization of each system is modeled using a minimum of 7 days and up to 60 days of historical workload.
- When optimizing instance sizes and families, the predicted CPU and memory usage levels must not exceed 70% and 90%, respectively.
- When memory usage metrics are not available, the analysis uses the existing memory allocation of the instance and will not change the memory configuration.
- DevOps-Automation—The automation is intended for generating recommendations that require little or no review before being implemented. Densify utilizes rule-driven analytics to predict the effort of changing instance from the current to the recommended type, and this policy favors low-effort recommendations, resulting in increased automation at the expense of reduced cost savings. Specifically:
- The resource utilization of each system is modeled using a minimum of 7 days and up to 90 days of historical workload.
- When optimizing instance sizes and families, the predicted CPU and memory usage must not exceed 65% and 85%, respectively.
- This policy will not specify burstable (T-series) instance families for workloads unless they are already running in a burstable family and will not change CPU Architecture from Intel to AMD or vice versa.
- When memory usage metrics are not available, the analysis uses the existing memory allocation of the instance and will not change the memory configuration.
- DevOps-Efficiency—The efficiency policy is intended for generating recommendations that provide maximum operational efficiency (and lowest operating cost). This policy also includes recommendations rated as moderate effort required , generating higher cost reduction than the DevOps default policy and so recommendations should be reviewed before implementing.
- The resource utilization of each system is modeled using a minimum of 3 day and up to 30 days of historical workload.
- When optimizing instance sizes and families, the predicted CPU and memory usage levels must not exceed 75% and 95%, respectively.
- When memory usage metrics are not available, the analysis uses the existing memory allocation of the instance and will not change the memory configuration.
You can also verify the specific details of the cloud policy used during an analysis through the Densify user interface, see
Resource
/analysis/cloud/aws/policy
/analysis/cloud/gcp/policy
/analysis/cloud/azure/policy
/analysis/containers/kubernetes/policy
Supported Operations
Table: Policy Supported Operations
|
HTTP Method |
Input |
Output |
Description |
|
Query String Parameter: |
|
Used to return a list of AWS policies available for analysis purposes. |
|
|
Query String Parameter: |
|
Used to return a list of GCP policies used for analysis. |
|
|
Query String Parameter: |
|
Used to return a list of Azure policies used for analysis. |
|
|
Query String Parameter: |
|
Used to return a list of Kubernetes Container policies available for analysis purposes. Note: DevOps policies are not supported for Container analysis. Contact support ([email protected]) to review your policy settings for Container resource optimization. |
Table: Analysis Policy Query String Parameters
|
Parameter Name |
Type |
Description |
|
(optional) |
string |
This option returns additional policy description details. |
Table: Analysis Policy Response Schema
|
Element |
Type |
Sort By |
Filter |
Description |
|
string |
|
|
The analysis policy type ID. |
|
|
string |
|
|
The entity ID of the policy instance. |
|
|
string |
|
|
The policy name. |
|
|
(optional) |
string |
|
|
A description of the policy. This element is only returned when the ?details=true option is added to the request. |
Examples
Example: List All the AWS Cloud Policies Available
The following example shows you how to list all the available AWS cloud policies.
Example: Listing AWS Cloud Policies
Request:
GET /analysis/cloud/aws/policyResponse:
[
{
"policyId": "4a63f651-a583-4157-97ff-35651370ffbe",
"policyInstanceId": "69fa4c99-1be2-4048-94a7-36fd83d07f37",
"name": "DevOps-Default"
},
{
"policyId": "4a63f651-a583-4157-97ff-35651370ffbe",
"policyInstanceId": "0c0ef18b-9367-4071-b733-396f63e51925",
"name": "DevOps-Automation"
},
{
"policyId": "4a63f651-a583-4157-97ff-35651370ffbe",
"policyInstanceId": "70a2ef4a-2ebb-4209-8ec8-9f6c70f77a74",
"name": "DevOps-Efficiency"
}
]Example: Listing AWS Cloud Policies with Descriptions
The following example shows you a request to list all the available AWS cloud policies with description.
Example: Listing AWS Cloud Policies with Description
Request:
GET /analysis/cloud/aws/policy?details=trueResponse:
[
{
"policyId": "4a63f651-a583-4157-97ff-35651370ffbe",
"policyInstanceId": "0c0ef18b-9367-4071-b733-396f63e51925",
"name": "DevOps-Automation",
"description": "This policy is intended for generating instance sizing and instance family optimization recommendations that require little or no review before being implemented. CLOE utilizes rule-driven analytics to predict the effort of changing instance type from current to recommended, and this policy favors Low effort recommendations, producing higher automation at the expense of lower cost savings.\r\nThe resource utilization of each system is modeled using a minimum of 7 days and up to 90 days of historical workload.\r\nWhen optimizing instance sizes and families, the predicted CPU and memory usage must not exceed 65% and 85%, respectively.\r\nThis policy will not specify burstable (T-series) instance families for workloads unless they are already running in a burstable family and will not change CPU Architecture from Intel to AMD or vice versa.\r\nWhen memory usage metrics are not available, the analysis assumes the existing memory allocation is required and will not change the memory configuration."
},
{
"policyId": "4a63f651-a583-4157-97ff-35651370ffbe",
"policyInstanceId": "69fa4c99-1be2-4048-94a7-36fd83d07f37",
"name": "DevOps-Default",
"description": "This policy reflects best practices for generating instance sizing and instance family optimization recommendations.\r\nThe resource utilization of each system is modeled using a minimum of 7 days and up to 60 days of historical workload.\r\nWhen optimizing instance sizes and families, the predicted CPU and memory usage levels must not exceed 70% and 90%, respectively.\r\nWhen memory usage metrics are not available, the analysis effectively assumes the existing memory allocation of the instance is required and will not change the memory configuration."
}
]Example: Listing GCP Cloud Policies with Descriptions
The following example shows you a request to list all the available GCP cloud policies with description.
Example: Listing GCP Cloud Policies with Description
Request:
GET /analysis/cloud/gcp/policy?details=trueResponse:
[
{
"policyId": "4fe32fc6-6067-4647-8a87-9bd1dc74389e",
"policyInstanceId": "43636c78-851b-4f25-8733-5debbbb6856b",
"name": "DevOps-Automation",
"description": "This policy is intended for generating instance sizing and instance family optimization recommendations that require little or no review before being implemented. CLOE utilizes rule-driven analytics to predict the effort of changing instance type from current to recommended, and this policy favors Low effort recommendations, producing higher automation at the expense of lower cost savings.\r\nThe resource utilization of each system is modeled using a minimum of 7 days and up to 90 days of historical workload.\r\nWhen optimizing instance sizes and families, the predicted CPU and memory usage must not exceed 65% and 85%, respectively.\r\nThis policy will not specify burstable (T-series) instance families for workloads unless they are already running in a burstable family and will not change CPU Architecture from Intel to AMD or vice versa.\r\nWhen memory usage metrics are not available, the analysis assumes the existing memory allocation is required and will not change the memory configuration."
},
{
"policyId": "4fe32fc6-6067-4647-8a87-9bd1dc74389e",
"policyInstanceId": "6131f154-8453-48c3-9747-edb327ec0bed",
"name": "DevOps-Efficiency",
"description": "This policy is intended for generating instance sizing and family optimization that provide maximum operational efficiency (and lowest operating cost). This policy also includes recommendations rated as Moderate effort, generating higher cost reduction than the Densify Defaults policy. Because of this, any recommendations should be reviewed before implementing.\r\nThe resource utilization of each system is modeled using a minimum of 3 day and up to 30 days of historical workload.\r\nWhen optimizing instance sizes and families, the predicted CPU and memory usage levels must not exceed 75% and 95%, respectively.\r\nWhen memory usage metrics are not available, the analysis effectively assumes the existing memory allocation of the instance is required and will not change the memory configuration."
},
{
"policyId": "4fe32fc6-6067-4647-8a87-9bd1dc74389e",
"policyInstanceId": "9b8cb5db-5045-4dbe-a6ee-740038c6b0b0",
"name": "DevOps-Default",
"description": "This policy reflects best practices for generating instance sizing and instance family optimization recommendations.\r\nThe resource utilization of each system is modeled using a minimum of 7 days and up to 60 days of historical workload.\r\nWhen optimizing instance sizes and families, the predicted CPU and memory usage levels must not exceed 70% and 90%, respectively.\r\nWhen memory usage metrics are not available, the analysis effectively assumes the existing memory allocation of the instance is required and will not change the memory configuration."
}
]