Service-aware and application service context-aware data in the ServiceNow platform drives AI-powered service operations. Top-down mapping helps identify applications with URL entry points, while tag-based mapping simplifies the process for cloud and container environments. Imagine Service Mapping technology using Machine Learning (ML) to create no-code service maps.

The Service Mapping Plus application extends Service Mapping functionality, allowing you to accelerate the mapping process with an ML-powered framework. On the homepage, it enables the visualization of data related to application services, ML-powered candidates, and servers. In the navigation list, it gives you an option to select and experience the tag-based mapping workspace and along with the newly introduced multi-source Service Mapping.

**Automated Service Suggestions** : Service Mapping uses Machine Learning (ML) to suggest potential application services. ML automatically calculates entry points, enabling you to preview the service map. With just a few clicks, you can create and update application services based on these suggestions, which include multiple service name options from various sources.
 
**Service Mapping Homepage** : The home page has the following components: 

- _Search a server_: Use the search bar to search for a server and view its details.
- _Populate data_: Select the Populate data button on the home page to update all the tiles and widgets with the most recent data.
- _Mapped application service_s: This tile shows the count and list of application services. 
- _ML-powered candidates_: This tile shows the count and list of application service candidates that can be converted to a service.
- _Mapped servers_: This tile shows the count and list of servers mapped to an application service.
- _Unmapped server_s: This tile shows a bar graph of 'Unmapped servers without candidate' and 'Unmapped servers with candidate'. These bars navigate to the respective lists in list navigation.
- Widgets that show service map data by operational type, creation method, and criticality, using visual bar graphs and a pie chart."

  **Application service readiness dashboard**  - Perform a health check and validate all prerequisites for ML-powered service mapping.

**Tag-Based Mapping Workspace-** Easily view data and create new tag-based services through an enhanced workspace that includes a dedicated dashboard for management.

**Multi-Source Service Mapping-** gain a single, trusted view of your services by eliminating fragmented maps and blind spots across tools. Unify Top down, tag-based, and Service Graph Connector based maps into composite service maps, so your teams troubleshoot faster, understand dependencies at a glance, and make change decisions with confidence. Supported from Australia onwards.