Application service readiness dashboard in configurable workspace
Review the information on the dashboard to ensure that you are 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.
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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 application services.
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
. 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. |
| Discovered connection suggestion status | A donut report |
Connection Suggestions Training Status [connection_suggestion_training_status] | A donut report that shows the status of connection suggestions. For details, see Status of discovered connection suggestions. |
Mapping status of application services
| Category | Description |
|---|---|
| Mapped without issues | The number of application services discovered without ML-related issues. |
| Missing source-target AFP | The number of application services 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 application services 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 application services 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
Application service 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 all relevant ADME - data collector probes | There are multiple ADME probes for different types of operating systems. Enable all probes necessary to discover configuration items (CIs) in your environment. |
| Assure minimum number of running processes | Check that the clustering solution created enough process groups, which become suggestions. If there are fewer processes than necessary, calibrate fingerprint-based discovery. |
| 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. |
Status of discovered connection suggestions
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 application services.
- High - This connection is likely to an internal component that is only used by this specific component or application.
- Medium - This connection is likely to a middleware component used by multiple services, such as IBM MQ or Oracle WebLogic Server.
- Low - This connection is likely to an application deployed on numerous servers in the organization, typically for monitoring purposes, such as Tivoli Enterprise Monitoring Agents or MID Server.
- Very low - This connection is likely to a central application used by the entire organization, for example, Microsoft Active Directory or Okta.
You can use connection suggestions without the confidence level for mapping application services.
Service issues
Review the list of application services 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.