Application service readiness dashboard in configurable workspace
Summarize
Summary of Application Service Readiness Dashboard in Configurable Workspace
The Application Service Readiness Dashboard is a key feature of Service Mapping Plus, designed to help you prepare for discovering and mapping application services using machine learning (ML). It utilizes data processed by Predictive Intelligence to suggest connections based on traffic, thus enhancing the efficiency of service mapping.
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Key Features
- Predictive Intelligence: Evaluates connections between application fingerprints, configuration items (CIs), and processes, providing ranked suggestions for connections.
- Dashboard Reports: Includes reports on mapping status, application fingerprint training, and traffic-based connection suggestions, allowing for an overview of ML-related issues and readiness.
- Widgets: Display prerequisites and issues related to service discovery, with navigable links to relevant details.
Key Outcomes
By utilizing the Application Service Readiness Dashboard, you can:
- Confirm readiness for application service mapping based on ML.
- Identify and resolve ML-related issues in service instances, enhancing the accuracy of your mappings.
- Stay informed about the status of application fingerprints and connection suggestions, facilitating timely decision-making on connections.
Ensure all prerequisites are in place, including enabling necessary plugins and scheduled jobs, to optimize your service mapping process. This proactive approach helps in reducing service disruptions and improving overall service management efficiency.
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.
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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 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.