--- sourceDocument: Zurich IT Operations Management sourceDocumentLink: https://www.servicenow.com/docs/r/zurich/it-operations-management Release : - zurich ft:locale : - en-US ft:publication_title : - Zurich IT Operations Management ft:clusterId : - itom bundleId : - itom workflow : - Technology --- # Application service readiness dashboard in configurable workspace # Application service readiness dashboard in configurable workspace {#ariaid-title1} * Release version: Zurich * * Updated July 31, 2025 * * ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 4 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Application service readiness dashboard in configurable workspace The Application service readiness dashboard in the Service Mapping workspace helps ServiceNow customers assess their readiness to discover and map application services using machine learning (ML). It leverages Predictive Intelligence to generate connection suggestions based on traffic analysis, enabling more accurate and automated service mapping. This dashboard is part of Service Mapping Plus, available on the ServiceNow Store. Show full answer Show less Customers use the dashboard to review prerequisites, identify issues related to ML-based service discovery, and monitor the training status of application fingerprints, ensuring their environment is properly configured for ML-driven service mapping. ## Key Features * **ML-Related Service Status Report:** A bar chart summarizing ML-related issues in mapped application services, helping identify problem areas such as missing fingerprints or processes. * **Application Fingerprints Training Status:** A donut chart showing the status of training for application fingerprints, which is critical for enabling accurate ML predictions. * **Traffic-Based Connection Suggestions:** A donut chart reflecting the ratio of classified to valid connections, providing insight into the effectiveness of ML in suggesting service connections. * **Prerequisite Validation:** Checks the status of essential components such as Predictive Intelligence plugin activation, ADME probe enablement, scheduled jobs, and system properties required for ML-driven discovery. * **Service Issues Listing:** Displays services most impacted by ML-related issues, helping prioritize troubleshooting and calibration efforts. ## Practical Use and Benefits Using this dashboard, ServiceNow customers can: * Confirm all required plugins and settings are enabled for ML-based service mapping. * Monitor the training progress of application fingerprints to anticipate when ML suggestions will be reliable. * Identify and address missing data or configuration gaps that prevent accurate service mapping, such as undiscovered hosts or incomplete process information. * Review connection suggestions to refine service instance mappings and improve service accuracy. * Navigate easily from dashboard widgets to detailed lists or forms for deeper investigation. ## Access and Roles To access the dashboard, navigate to **Workspaces \> Service Mapping** and select the Application service readiness icon. Users require the **servicemappingadmin** role to view and manage this dashboard. 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. The Application service readiness dashboard is part of Service Mapping Plus, available on the ServiceNow Store. ## Request apps on the Store {#readiness-dashboard-ml__section_gvb_cql_rlb} Visit the [ServiceNow Store](https://store.servicenow.com/sn_appstore_store.do#!/store/home) 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](https://www.servicenow.com/docs/r/store-release-notes/sn-store-release-notes.html).{#readiness-dashboard-ml__inline-send-to-store} 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 {#readiness-dashboard-ml__section_ccd_3fst_yrb} service_mapping_admin ## Access the Application service readiness dashboard {#readiness-dashboard-ml__section_ecd_5vt_yrb} To open the dashboard, navigate to WorkspacesService Mapping. Then select the Application service readiness icon![application service readiness icon](). ## Reports {#readiness-dashboard-ml__section_pln_b5v_dsb} The dashboard includes the following reports. {#readiness-dashboard-ml__table_qln_b5v_dsb__entry__4} | Title | Type | Source table | Description | |-|-|-|-| | Mapping status of application service | A bar report ![Bar report icon]() | 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](https://www.servicenow.com/docs/h5NhjVPhhKlnR0W6mm9Djw#readiness-dashboard-ml__section_kpj_npq_xrb). | | Application fingerprints training status | A donut report ![Donut report icon]() | 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 ![Donut report icon]() | 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. | [ ] {#readiness-dashboard-ml__table_qln_b5v_dsb} ## Mapping status of application services {#readiness-dashboard-ml__section_kpj_npq_xrb} Review the summary of ML-related issues in mapped application services. {#readiness-dashboard-ml__id_efx_gjq_zrb__entry__2} | 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. | [ ] {#readiness-dashboard-ml__id_efx_gjq_zrb} ## Prerequisites status {#readiness-dashboard-ml__section_zfn_1jr_xrb} 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. {#readiness-dashboard-ml__id_jdp_1ps_1sb__entry__2} | Prerequisite | Description | |-|-| | Install and enable Predictive Intelligence (PI) plugin | Service Mapping uses Predictive Intelligence to generate connection suggestions. 1. Ensure that the Predictive Intelligence plugin appears Installed. 2. Click the Predictive Intelligence tile and verify that the Status is Active. If the status is Inactive, select the Activate/Repair link under Related Links. {#readiness-dashboard-ml__ol_g4y_grr_xrb} | | 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: 1. Navigate to the System Property \[sys_property\] table. 2. Locate the sn.adm.ip_expansion_limit property. 3. Ensure that this property is set to a positive number. {#readiness-dashboard-ml__ol_n5l_ksq_t2c} | | 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. | [ ] {#readiness-dashboard-ml__id_jdp_1ps_1sb} ## Service issues {#readiness-dashboard-ml__section_l15_xtr_xrb} 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. {#readiness-dashboard-ml__readiness-list-def} **Related concepts** * [Calibrate fingerprint-based discovery](https://www.servicenow.com/docs/FiWdrpcsXhihIChm2mipTA#calibrate-process-based-discovery "Fine-tune discovering applications based on processes, if the discovery results are not satisfactory.") **Related tasks** * [Verify fingerprint-based discovery generates suggestions](https://www.servicenow.com/docs/FiWdrpcsXhihIChm2mipTA#ensure-suggestion-generation-fingerprint "Fingerprint-based discovery relies on Predictive Intelligence for generating suggestions for discovery. If the Application Fingerprints dashboard does not display any suggestions, verify that the Predictive Intelligence is configured correctly.") **Related reference** * [Learn about ADME probes](https://www.servicenow.com/docs/FiiwvCpodIkDeCXfZmCt~w "Discovery identifies and classifies information about TCP connections using the ADM and ADME probes.") * [Enable and configure discovery using ADME probes](https://www.servicenow.com/docs/oVRkYplYNHcKUrtzLBUqZg "Discovery properties allow you to control several aspects of the horizontal discovery process.") **Related topics** * [Troubleshooting guide for Service Mapping ML Connection Suggestions \[KB0963421\]](https://support.servicenow.com/nav_to.do?uri=/kb?id=kb_article_view&sysparm_article=KB0963421) *[\>]: and then