densify-dev · amitjohry · May 22, 2026 · Feb 25, 2026 · Feb 25, 2026 · Feb 25, 2026
diff --git a/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze.mdx b/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze.mdx
@@ -10,40 +10,12 @@ The `/analysis/cloud/aws/analyze` resource is used to collect AWS CloudWatch da
 * Subsequent analysis is scheduled to run on a nightly basis after the completion of data collection.
 * Optionally, you can configure the results to be sent to a webhook URI upon analysis completion. See [Add webhook to an analysis](./Analysis_Webhook#_AddWebhook) for details.
 
-3. While data collection or analysis is in progress, you can check the status (using `/analysis/AWS/<``subscriptionId``>/status` resource) or wait for the results to be published to an optional webhook URI.
+3. Once data collection succeeds and an `analysisId` is created for the account, you can check progress with `/analysis/cloud/aws/<analysisId>/status` or wait for the results to be published to an optional webhook URI. Accounts that have not produced an `analysisId` (for example, due to unsupported resources or insufficient data) cannot use the status endpoint until an analysis run begins.
 4. The reporting database update is scheduled to run automatically on a nightly basis after the completion of the analysis. This process produces reports for each instance recommendation, which is useful for analysts or application owners. These reports are only created after the scheduled analysis is completed, and may therefore only be available on the following day for a new analysis. Exact timing depends on the size of your environment.
-
-### Ad-Hoc Tasks
-
-Generally you do not need to run once-off tasks as both data collection and analysis tasks are scheduled automatically. In cases where you need make an ad-hoc request in addition to the scheduled job, the functionality exists for this endpoint.
-
-#### Historical Data Collection 
-
-When Kubex initiates data collection, normally audits collect only the last 24 hours of data. You can optionally collect up to 60 days of historical data. The historical data provides a more representative set of data on which to base resizing and optimization recommendations. You can run an ad-hoc task to collect the historical data.
-
 <Note>
-Collection of historical data can take a significant amount of time, depending on the number of instances from which Kubex is collecting data. Contact [support@kubex.ai](mailto:support@kubex.ai) to enable historical data collection and details of the performance impact.
+When onboarding an account using the `/analysis/cloud/aws/analyze` endpoint, receiving a 200 status code signals that the onboarding was successful.
 </Note>
 
-The following settings define the range of historical data to be collected:
-
-* Start date offset--This is number of days from the 60-day maximum, used to define the start of the range.
-
-These extra API parameters allow you to reduce the number of days of historical data to be collected. If, for example, the daily audit has been running for a few days before the historical audit can be executed then you can set the end offset to exclude the number of days that have already been collected. Sixty days is the maximum number of days that you can go back and collect historical data.
-
-* End date offset--This is number of days from yesterday, to end the range of data collected.
-
-<Accordion title="Figure: Adjusting Historical Range Using Start and End Dates">
-<Frame>![](/images/docs-api/WebHelp_Densify_API_Cloud/Content/Resources/Images/CiRBA_API_Guide/03000025_356x218.png)</Frame>
-</Accordion>
-
-
-A connection to the specified cloud account must already exist before you can run an ad hoc audit. When you execute an ad hoc refresh an audit task will be configured but a new connection will not be created. If the cloud connection does not already exist and the API POST contains `triggerAdhocAudit=true`, then you will get an error message.
-
-If there is more than one account associated with the specified account ID (i.e. a payer account with many linked accounts), the Kubex API handles it in the same way that analyses are currently rerun using the POST operation.
-
-Once the audit is complete you need to rerun the associated analyses as indicated below or you can wait for the next scheduled execution of the analyses and RDB populate.
-
 #### Analysis Update
 
 You can make an ad-hoc request to refresh an existing analysis, outside of the scheduled nightly run using `/analysis/cloud/<aws|azure|gcp>/analyze`. This manual, ad hoc analysis request does not perform data collection or reporting database (RDB) updates. It only runs the analysis on the existing data collected with the following behavior:
@@ -70,9 +42,9 @@ Before you can collect AWS CloudWatch data, you need to create an IAM role for
 ## Endpoints
 
 <CardGroup cols={2}>
-    <Card title="Analyze Aws" href="/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze/analyzeAws" arrow/>
+    <Card title="Analyze AWS" href="/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze/analyzeAws" arrow/>
 </CardGroup>
 
 <CardGroup cols={2}>
-    <Card title="List Aws Analyses" href="/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze/listAwsAnalyses" arrow/>
+    <Card title="List AWS Analyses" href="/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_AWS_Analyze/listAwsAnalyses" arrow/>
 </CardGroup>
diff --git a/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_Azure_Analyze.mdx b/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_Azure_Analyze.mdx
@@ -8,36 +8,15 @@ The `/analysis/azure/analyze` resource is used to collect Microsoft Azure infra
 2. Initiate analysis on the data collected using the default policy.
    * Subsequent analysis is scheduled to run on a nightly basis after the completion of data collection.
    * Optionally, you can configure the results to be sent to a webhook URI upon analysis completion. See [Add webhook to an analysis](./Analysis_Webhook#_AddWebhook) for details.
-3. While data collection or analysis is in progress, you can check the status (using `/analysis/azure/<``subscriptionId``>/status` resource) or wait for the results to be published to an optional webhook URI.
+3. Once data collection succeeds and an `analysisId` is created for the subscription, you can track progress with `/analysis/cloud/azure/<analysisId>/status` or wait for the results to be published to an optional webhook URI. Subscriptions that have not produced an `analysisId` (for example, unsupported resources or insufficient data) cannot use the status endpoint until an analysis run begins.
 4. The reporting database update is scheduled to run automatically on a nightly basis after the completion of the analysis. This process produces reports for each instance recommendation, which is useful for analysts or application owners. These reports are only created after the scheduled analysis is completed, and may therefore only be available on the following day for a new analysis. Exact timing depends on the size of your environment.
 
-The `/analysis/cloud/azure` resource is also used to return a list of Microsoft Azure optimization analyses currently in Kubex.
-
-### Ad-Hoc Tasks
-
-Generally you do not need to run once-off tasks as both data collection and analysis tasks are scheduled automatically. In cases where you need make an ad-hoc request in addition to the scheduled job, the functionality exists for this endpoint.
-
-#### Historical Data Collection
-
-When Kubex initiates data collection, normally audits collect only the last 24 hours of data. You can optionally collect up to 30 days of historical data. The historical data provides a more representative set of data on which to base resizing and optimization recommendations. You can run an ad-hoc task to collect the historical data.
-
 <Note>
-Collection of historical data can take a significant amount of time, depending on the number of instances from which Kubex is collecting data. Contact [support@kubex.ai](mailto:support@kubex.ai) to enable historical data collection and details of the performance impact.
+When onboarding a subscription using the `/analysis/cloud/azure/analyze` endpoint, receiving a 200 status code signals that the onboarding was successful.
 </Note>
 
+The `/analysis/cloud/azure` resource is also used to return a list of Microsoft Azure optimization analyses currently in Kubex.
 
-The following settings define the range of historical data to be collected:
-
-* Start date offset--This is the number of days from the 30-day maximum, used to define the start of the range.
-* End date offset--This is number of days from yesterday, to end the range of data collected.
-
-These parameters allow you to reduce the number of days of historical data to be collected. If, for example, the daily audit has been running for a few days before the historical audit can be executed then you can set the end offset to exclude the number of days that have already been collected. Thirty days is the maximum number of days that you can go back and collect historical data for Azure and GCP environments.
-
-A connection to the specified cloud account must already exist before you can run an ad hoc audit. When you execute an ad hoc refresh an audit task will be configured but a new connection will not be created. If the cloud connection does not already exist and the API POST contains `triggerAdhocAudit=true`, then you will get an error message.
-
-If there is more than one account associated with the specified account ID (i.e. a payer account with many linked accounts), the Kubex API handles it in the same way that analyses are currently rerun using the POST operation.
-
-Once the audit is complete you need to rerun the associated analyses as indicated below or you can wait for the next scheduled execution of the analyses and RDB populate.
 
 #### Analysis Update
 

diff --git a/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_GCP_Analyze.mdx b/docs-api/WebHelp_Densify_API_Cloud/Content/API_Guide/Analysis_GCP_Analyze.mdx
@@ -14,34 +14,13 @@ The `/analysis/gcp/analyze` resource is used to collect Google Cloud Platform i
 * Subsequent analysis is scheduled to run on a nightly basis after data collection.
 * You can optionally configure the results to be sent to a webhook URI upon analysis completion. See [Add webhook to an analysis](./Analysis_Webhook#_AddWebhook) for details.
 
-3. While data collection or analysis is in progress, you can check for status (using `/analysis/gcp/<``projectId``>/status` resource) or wait for the results to be published to an optional webhook URI.
+3. Once data collection succeeds and an `analysisId` is created for the project, you can check progress via `/analysis/cloud/gcp/<analysisId>/status` or wait for the results to be published to an optional webhook URI. Projects that do not yet have an `analysisId` (for example, unsupported resources or insufficient data) must wait for an analysis run before the status endpoint becomes available.
 4. The reporting database update is scheduled to run automatically on a nightly basis after the completion of the analysis. This process produces reports for each instance recommendation, which is useful for analysts or application owners. These reports are only created after the scheduled analysis is completed, and may therefore only be available on the following day for a new analysis. Exact timing depends on the size of your environment.
 
-### Ad-Hoc Tasks
-
-Generally you do not need to run once-off tasks as both data collection and analysis tasks are scheduled automatically. In cases where you need make an ad-hoc request in addition to the scheduled job, the functionality exists for this endpoint.
-
-#### Historical Data Collection
-
-When Kubex initiates data collection, normally audits collect only the last 24 hours of data. You can optionally collect up to 30 days of historical data. The historical data provides a more representative set of data on which to base resizing and optimization recommendations. You can run an ad-hoc task to collect the historical data.
-
 <Note>
-Collection of historical data can take a significant amount of time, depending on the number of instances from which Kubex is collecting data. Contact [support@kubex.ai](mailto:support@kubex.ai) to enable historical data collection and details of the performance impact.
+When onboarding a project using the `/analysis/cloud/gcp/analyze` endpoint, receiving a 200 status code signals that the onboarding was successful.
 </Note>
 
-The following settings define the range of historical data to be collected:
-
-* Start date offset--This is the number of days from the 30-day maximum, used to define the start of the range.
-* End date offset--This is number of days from yesterday, to end the range of data collected.
-
-These parameters allow you to reduce the number of days of historical data to be collected. If, for example, the daily audit has been running for a few days before the historical audit can be executed then you can set the end offset to exclude the number of days that have already been collected. Thirty days is the maximum number of days that you can go back and collect historical data for Azure and GCP environments.
-
-A connection to the specified cloud account must already exist before you can run an ad hoc audit. When you execute an ad hoc refresh an audit task will be configured but a new connection will not be created. If the cloud connection does not already exist and the API POST contains `triggerAdhocAudit=true`, then you will get an error message.
-
-If there is more than one account associated with the specified account ID (i.e. a payer account with many linked accounts), the Kubex API handles it in the same way that analyses are currently rerun using the POST operation.
-
-Once the audit is complete you need to rerun the associated analyses as indicated below or you can wait for the next scheduled execution of the analyses and RDB populate.
-
 #### Analysis Update
 
 You can make an ad-hoc request to refresh an existing analysis, outside of the scheduled nightly run using `/analysis/cloud/<aws|azure|gcp>/analyze`. This manual, ad hoc analysis request does not perform data collection or reporting database updates. It only runs the analysis on the existing data collected with the following behavior:

diff --git a/docs-kubex/Content/Cloudex/Catalog_Map_Tab.mdx b/docs-kubex/Content/Cloudex/Catalog_Map_Tab.mdx
@@ -8,7 +8,7 @@ import { ImageCard } from "/snippets/ImageCard.mdx";
 
 The Kubex catalog map allows you to view a range of recommended instance type options for public cloud instances. The map view shows the AWS or Azure catalog scores for the selected instance.
 <Note>
-**Note:** The catalog map is **not** currently available for ASGs, VM Scale Sets or GCP cloud instances.
+**Note:** The catalog map is **not** currently available for ASGs, VM Scale Sets, GCP CE Instances or OCI Instances.
 </Note>
 
 Filters allow you to limit the catalog based on items such as processor type, processor features and instance cost.

diff --git a/docs-kubex/Content/Cloudex/Cloud_Connections.mdx b/docs-kubex/Content/Cloudex/Cloud_Connections.mdx
@@ -34,13 +34,22 @@ Before creating a connection you need to grant access to Kubex so that it can co
     <a href="/docs/WebHelp_Densify_Cloud/Content/Data_Collection_for_Public_Cloud_Systems/AWS_Data_Collection_Prerequisites_for_an_IAM_Role__CloudWatch_only_">
     AWS Data Collection Using IAM Roles Prerequisites
     </a>
-    .
   </li>
   <li>
     <a href="/docs/WebHelp_Densify_Cloud/Content/Data_Collection_for_Public_Cloud_Systems/Microsoft_Azure_Data_Collection_Prerequisites_for_a_Service_Principal">
     Microsoft Azure Data Collection Prerequisites
     </a>
   </li>
+  <li>
+    <a href="/docs/WebHelp_Densify_Cloud/Content/Data_Collection_for_Public_Cloud_Systems/Google_Cloud_Platform_Data_Collection_Prerequisites">
+    Google Cloud Platform Data Collection Prerequisites
+    </a>
+  </li>
+  <li>
+    <a href="/docs/WebHelp_Densify_Cloud/Content/Data_Collection_for_Public_Cloud_Systems/Oracle_Cloud_Infrastructure_Data_Collection_Prerequisites">
+    Oracle Cloud Infrastructure Data Collection Prerequisites
+    </a>
+  </li>
 </ul>
 
 
@@ -58,6 +67,16 @@ Once you have completed the prerequisites you can create the connections using t
     Creating Azure Cloud Connections
     </a>
   </li>
+  <li>
+    <a class="MCXref xref" href="/docs-kubex/Content/Cloudex/Data_Collection_GCP_Connections">
+    Creating GCP Cloud Connections
+    </a>
+  </li>
+  <li>
+    <a class="MCXref xref" href="/docs-kubex/Content/Cloudex/Data_Collection_OCI_Connections">
+    Creating OCI Cloud Connections
+    </a>
+  </li>
 </ul>
 
 

diff --git a/docs-kubex/Content/Cloudex/Data_Collection_GCP_Connections.mdx b/docs-kubex/Content/Cloudex/Data_Collection_GCP_Connections.mdx
@@ -0,0 +1,87 @@
+---
+title: "Connecting GCP to Kubex"
+sidebarTitle: "Connecting GCP to Kubex"
+---
+
+Kubex uses an API-Key user to access your Google Cloud Platform (GCP) project. See [Google Cloud Platform Data Collection Prerequisites](/docs/WebHelp_Densify_Cloud/Content/Data_Collection_for_Public_Cloud_Systems/Google_Cloud_Platform_Data_Collection_Prerequisites) for details on configuring the API-Key user and obtaining the required credentials.
+
+## Configuring GCP Connections
+
+<ol start="1">
+  <li>
+    Click the **Add** button and select GCP.
+    <Frame caption="Figure: Accessing the Add Button">
+      <img src="/images/docs-kubex/Content/Cloudex/add_cloud_connection.png"/>
+    </Frame>
+  </li>
+  <li>
+    Enter the GCP-specific connection parameters.
+    <Frame caption="Figure: GCP Connection Window">
+      <img src="/images/docs-kubex/Content/Cloudex/add_gcp_connection.png"/>
+    </Frame>
+    <Accordion title="Table: GCP Connection Parameters">
+      <table style={{ width: "100%", borderCollapse: "collapse" }}>
+        <colgroup>
+          <col style={{ width: "30%" }} />
+          <col style={{ width: "70%" }} />
+        </colgroup>
+        <thead>
+          <tr>
+            <th style={{ verticalAlign: "middle" }}>Field</th>
+            <th style={{ verticalAlign: "middle" }}>Description</th>
+          </tr>
+        </thead>
+        <tbody>
+          <tr>
+            <td style={{ verticalAlign: "middle" }}>Service Account Key File</td>
+            <td style={{ verticalAlign: "middle" }}>
+              The JSON key file for the service account you created in GCP for Kubex data collection.
+            </td>
+          </tr>
+          <tr>
+            <td style={{ verticalAlign: "middle" }}>Client ID</td>
+            <td style={{ verticalAlign: "middle" }}>
+              The client ID for the service account you created in GCP for Kubex data collection. This is auto filled when you upload the service account key file.
+            </td>
+          </tr>
+          <tr>
+            <td style={{ verticalAlign: "middle" }}>Client Email</td>
+            <td style={{ verticalAlign: "middle" }}>
+              The client email for the service account you created in GCP for Kubex data collection. This is auto filled when you upload the service account key file.
+            </td>
+          </tr>
+
+        </tbody>
+      </table>
+    </Accordion>
+  </li>
+  <li>
+    Verify your connection by clicking the **Verify Connection** button.
+    <ul>
+    <li class="ListBullet">
+    If the credentials are valid, you will be connected and authenticated.
+    </li>
+    <li class="ListBullet">
+    If the credentials cannot be validated, then review the displayed error message and correct your credentials. See <a href="/docs/WebHelp_Densify_Cloud/Content/Data_Collection_Troubleshooting/GCP_Cloud_Connections">Troubleshooting GCP Cloud Connections</a> for details.
+    </li>
+    </ul>
+  </li>
+  <li>
+    Once the account is verified, the available projects that are associated with the service account are listed. Select the projects that you want to include in this connection and click **Next**.
+  </li>
+  <Frame caption="Figure: Select GCP Project Window">
+    <img src="/images/docs-kubex/Content/Cloudex/select_gcp_connection.png"/>
+  </Frame>
+  <li>
+    Review the connection details and add a name for your connection. Click **Save** to save the connection.
+  </li>
+  <Frame caption="Figure: Save GCP Connection Window">
+    <img src="/images/docs-kubex/Content/Cloudex/save_gcp_connection.png"/>
+  </Frame>
+
+
+  <li>
+  If you want to connect another tenancy, click **Add** and repeat these steps to configure the connection.
+  </li>
+</ol>
+