Application service readiness dashboard in configurable workspace
Summarize
Summary of Application service readiness dashboard in configurable workspace
The Application service readiness dashboard in ServiceNow’s configurable workspace helps you verify your readiness to discover and map application services using machine learning (ML) powered by Predictive Intelligence. This dashboard is part of Service Mapping Plus, available on the ServiceNow Store, and supports traffic-based connection suggestions to improve service mapping accuracy.
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Service Mapping leverages ML to analyze connections between application fingerprints, configuration items (CIs), and processes, providing ranked connection suggestions. These suggestions assist in refining service instance mappings by identifying valid connections and highlighting potential issues.
Access and Roles
To access the dashboard, navigate to Workspaces > Service Mapping and select the Application service readiness icon. Users require the servicemappingadmin role on the ServiceNow AI Platform to use this dashboard.
Key Features
- Reports: The dashboard includes several reports offering insights into ML-related service mapping status, application fingerprint training, and traffic-based connection suggestions. These reports help monitor the health and progress of your service mapping deployment.
- Mapping Status Summary: Visualizes the state of application services, highlighting issues such as missing fingerprints, missing process information, unavailable confidence levels, or undiscovered target hosts. This helps prioritize remediation actions like rediscovering hosts or calibrating fingerprint discovery.
- Prerequisite Checks: Lists essential modules and settings required for effective ML-based service mapping, including Predictive Intelligence plugin activation, enabling of ADME probes, scheduled jobs for fingerprint training and connection suggestions, and system property configurations.
- Service Issues: Displays the services most impacted by ML-related issues, assisting administrators in focusing troubleshooting efforts on critical services where connection suggestions are enabled.
Prerequisites
Successful application service mapping with ML requires:
- Installed and active Predictive Intelligence plugin.
- Enabled ADME properties and appropriate ADME probes for relevant operating systems.
- Configured IP address expansion limits.
- Active scheduled jobs for application fingerprint training and traffic connection suggestion generation.
- Enabled system properties to activate connection suggestions.
Practical Benefits
Using this dashboard, ServiceNow customers can quickly assess and resolve configuration gaps impacting ML-driven service mapping. It ensures the environment is properly set up to leverage Predictive Intelligence for automated, accurate application service discovery and dependency mapping. This leads to more reliable service models and improved operational visibility.
Additional Resources
The dashboard integrates links to related lists and forms for detailed issue investigation. It also connects to documentation on calibrating fingerprint discovery, configuring ADME probes, and troubleshooting ML connection suggestions, enabling customers to take informed next steps based on dashboard insights.
Review the information on the dashboard to confirm that you’re ready to discover and map application services based on machine learning (ML). Service Mapping uses data processed by Predictive Intelligence to generate suggestions for traffic-based connections.
Request apps on the Store
Visit the ServiceNow Store website to view all the available apps and for information about submitting requests to the store. For cumulative release notes information for all released apps, see the ServiceNow Store version history release notes.
Predictive Intelligence evaluates connections between application fingerprints, CIs, and processes, and ranks their relevancy. Service Mapping uses this information to create connections based on connection rules. It also generates connection suggestions for servers and load balancers for you to decide which connections to add or remove from the service instances.
Widgets on the ML Dashboard page show the information about prerequisites and issues related to service discovery based on Predictive Intelligence. Select links inside the widgets and reports to navigate to the related list or form.
Required ServiceNow AI Platform roles
service_mapping_admin
Access the Application service readiness dashboard
To open the dashboard, navigate to . Then select the Application service readiness icon
.
Reports
| Title | Type | Source table | Description |
|---|---|---|---|
| Mapping status of application service | A bar report |
ML-Related Service Status [ml_related_service_status] | A bar report that provides the summary of ML-related issues in mapped application services. For detailed information, see Mapping status of application services. |
| Application fingerprints training status | A donut report |
AFP Training Status [afp_training_status] | A donut report that shows the status of application fingerprint training. Predictive Intelligence trains predictive models and machine-learning solutions. View the training status for application fingerprints to understand if your deployment is ready for mapping using Predictive Intelligence. |
| Traffic-based connection suggestions for existing discovered services | A donut report |
Connection Suggestions [sa_ml_connection_suggestion] | A donut report that reflects the ratio of classified connections to valid connections in the Connections Suggestions table. This table is only populated during top-down discovery. |
Mapping status of application services
| Category | Description |
|---|---|
| Mapped without issues | The number of service instances discovered without ML-related issues. |
| Missing source-target AFP | The number of service instances missing some application fingerprints for a source or target process. To solve issues, calibrate the fingerprint-based discovery. |
| Missing source-target process | The number of service instances missing some source-target process information. To solve these issues, rediscover the target hosts and ensure that the relevant processes are discovered. |
| Confidence level unavailable | The confidence level indicates the likelihood of this connection being part of the service instances. If the confidence level appears as N/A, wait until the application fingerprints training is complete. |
| Missing target host | The number of service instances with some CI connections not fully discovered, because the horizontal discovery didn't discover host CIs. To solve these issues, rediscover the target hosts and ensure that the relevant processes are discovered. |
Prerequisites status
Service instance mapping requires the integration of several modules and applications: credentials, Predictive Intelligence, enhanced Application Dependency Mapping (ADME) discovery, and scheduled jobs. Review the list of prerequisites and ensure that the state of all prerequisites is Ready.
| Prerequisite | Description |
|---|---|
| Install and enable Predictive Intelligence (PI) plugin | Service Mapping uses Predictive Intelligence to generate connection suggestions.
|
| Enable ADME property | Service Mapping uses ADME probes. Ensure that the glide.discovery.enable_adme property is set to True. |
| Enable ADME or ADM probe for each relevant OS | There are multiple ADME probes for different types of operating systems. Enable all probes necessary to discover configuration items (CIs) in your environment. |
| Allow IP address expansion |
This setting helps manage the expansion of global addresses (such as '0.0.0.0' or '*') into individual IP addresses. The limit for this expansion must be greater than 0. To verify and set this limit:
|
| Enable application fingerprint (AFP) scheduled job | Ensure that the Applications suggestion - ITOM Autodisco scheduled job that controls the fingerprint-based discovery is set to Active. |
| Enable Connection Suggestion property | Confirm that discovery based on Predictive Intelligence is enabled. Navigate to the System Property [sys_properties] table and verify that the sa_ml.connection_suggestions.active property is set to True. |
| Enable connection suggestion scheduled job | Ensure that the Status of the Service Mapping - Traffic Process to Process scheduled job is Active. This schedule job triggers generation of connection suggestions. |
Service issues
Review the list of service instances most affected by ML-related issues. The list of most affected services is available if the connection suggestions feature is enabled in your deployment. The list shows service names and the number of ML-related issues for each of them. It also indicates if the traffic-based feature is enabled for the services.