Feature Deployment Summary

Feature Deployment

Feature Deployment is a deployment process that will allow you to easily deploy both metadata and data components using the feature migration template or using the dataset configured either from your Salesforce Org or Version Control.

Feature Deployment History

The Feature Deployment History lists every deployment you have previously run using AutoRABIT. It is also where you can view detailed deployment reports or re-deploy the nCino objects to your Salesforce Org/ Version Control.

Accessing Feature Deployment History Page

You can visit ncino > Deployment History to view the Feature Deployment summary page or you'll be auto-redirected to this page whenever you trigger a deployment (using Feature Deployment).

By default, the jobs are listed in reverse chronological order; that is, the most recent job shows up first. Deployment history is shared amongst team members in AutoRABIT, so you may see deployments performed by other members of your team.

My Deployments tab lists all of the deployment operations you have performed. The Others tab will list all other deployments made in AutoRABIT by your team.

For each deployment, the following information is displayed:

  1. Deployment label: The deployment label name. You can search for deployments by label name using the search filter in the top right of the page

  2. Feature Name: Feature name assigned to the deployment

  3. Status: Successful, Failed, Partially Failed, or In progress

  4. Deployment Version: Version number for the deployment

  5. Source: The source Salesforce Org

  6. Date: The date and time of the deployment

  7. Owner: Which user performed the deployment

  8. Iteration: The number of revisions for your deployment; for dataset deployments, the iteration number will appear as "dataset"

  9. Destination: Target salesforce org

  10. Redeploy: Redeploy will allow you to re-trigger the deployment process again [Refer to "Re-trigger the Deployment" section on this page]

Filtering Deployment History

You can search for items in your history using the search box in the top right of the page.

You can view all deployments (default), or only successful, failed, partially failed, in-progress or timeout deployments, or filter results by deployment label, feature name, the owner who carried out the deployment, or between to/fro dates.

To filter the deployment via Feature Name, you will have the versions list auto-populated to fetch the exact result.

Data Retrieval Workspace

Deployments will be in the queue for dataset refresh jobs and will be displayed under Data Retrieval Workspace.

Applicable only if the deployment is carried via:

  1. Template using Version Control

  2. Version Control using Salesforce Org

Viewing the Deployment Summary

Click on one of the Labels to view the detailed deployment summary info.

Feature Template- Revision Details

For each template revision, you can find the list of all data nCino objects that were either deployed or failed. View the individual object deployment details by clicking on the object or view the success or failed count directly.

Object Information: Click on the object to view their detailed information on the right side of the page.

Retrieved: This section will tell you the total records that are being retrieved. You can even download the records on your local machine. The file format is downloaded in CSV format.

Success: Fetch the successful records for each data object.

Failed: Displays the failed records for each object.

Deployment Log

Re-triggering the Deployment

Once you have fixed the deployment error or you like to re-trigger the deployment once again, you can click on the Re-Deploy button to quickly restart your deployment.

Choose the 'Destination Org' and the deployment criteria you want to set for the deployment process.

Once the deployment is re-triggered, a new iteration gets auto-generated with new deployment log details. If the deployment gets failed due to any metadata or data objects, such a report can be found on this page.

Important Note: AutoRABIT recommends fixing the errors generated and redeploying the process once again until the status changes to Success.

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