Analyze potential impact agentic workflow
Summarize
Summary of Analyze potential impact agentic workflow
The Analyze potential impact agentic workflow in ServiceNow evaluates how a change request might affect operational servers and associated services. This analysis aids in making informed decisions on managing change requests by identifying up to 10 relevant servers and 3 services potentially impacted by the change. The workflow automatically saves the impact analysis to the change request work notes for traceability.
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Key Features
- Automated Impact Analysis: Uses the Analyze Potential Impact Agent to assess the influence of change requests on servers and services based on configuration items linked to the request.
- Server and Service Selection: Prioritizes servers that are active and part of services, excluding non-operational or retired servers.
- Service Mapping AI Skills Integration: Employs generative AI capabilities to identify, classify, and evaluate services by analyzing process data and infrastructure connections.
- Two Primary AI Skills:
- Service Mapping Candidate Skill: Identifies and categorizes application service candidates by analyzing process characteristics, providing detailed descriptions and naming.
- Service Mapping Candidates Impact Skill: Predicts downstream effects of changes on connected servers and services, generating comprehensive impact summaries.
- User Interaction: The agent retrieves the change request number automatically if open or prompts for it; it then displays impact results in the ServiceNow Otto panel.
- Domain Separation Limitation: The workflow does not support domain-separated instances and is optimized for English-language interactions.
Practical Benefits for ServiceNow Customers
- Enables proactive risk identification by highlighting potentially impacted servers and services before implementing changes.
- Supports better change management decisions by providing detailed impact summaries based on actual infrastructure relationships.
- Automates and documents impact assessments to improve auditability and communication among change management teams.
- Integrates seamlessly with existing change request processes through the ServiceNow Otto panel for easy access and action.
Usage Recommendations
Use this workflow to assess change requests to uncover hidden dependencies and risks within your IT infrastructure. Ensure your servers and services are accurately mapped for the AI skills to deliver precise analyses. Note that domain separation environments are currently unsupported, so plan accordingly. Conduct interactions in English for best results.
The Analyze potential impact agentic workflow analyzes how a change request might impact servers and services. This analysis helps you make informed decisions about the next steps regarding the change request.
Analyze potential impact agentic workflow overview
AI agent used in the Analyze potential impact agentic workflow
| AI Agent | AI Agent role |
|---|---|
| Analyze Potential Impact Agent | Analyzes the potential impact of a change on relevant servers and services and generate an impact analysis. |
Generating the impact analysis
- Prerequisite verification: The agent verifies that all prerequisites have been met.
- Change request identification: If you have a change request open, the agent retrieves the change request number from the current active page. Otherwise, it prompts you to provide the change request number.
- Server selection: The agent selects up to 10 affected servers from the configuration items (CIs) in the change request.
- Match identification: The agent identifies matches between servers and suggested services.
- Impact analysis: Eventually, the agent prioritizes and displays up to 10 impacted relevant servers, giving priority to servers that are part of services, and up to 3 impacted services. Additionally, the agent provides you with a summary about each service and how it might be impacted by related servers. This information is displayed in the ServiceNow Otto panel.
- Saving the impact analysis: The analysis generated by the Analyze potential impact agentic workflow is saved to the change request work notes.
To learn more about using the workflow, see Assess a change request with the Analyze potential impact workflow.
Analyze potential impact agentic workflow sample report
Domain separation
Currently, the Analyze potential impact agentic workflow doesn’t support instances with domain separation. For optimal results, conduct all conversations in English.
Service Mapping AI Skills
Service Mapping skills are intelligent capabilities that enhance the Analyze potential impact agentic workflow. These skills leverage generative AI to identify, classify, and assess the impact of changes to your IT infrastructure.
- Service Mapping Candidate
- Service Mapping Candidates Impact
Service Mapping Candidate skill
This skill automatically identifies and names processes and application service candidates by analyzing process characteristics, commands, and parameters. It provides detailed descriptions and categorization to help you understand which services are running in your environment.
The skill uses a two-stage process:
- In the process classification stage, the agent uses the skill to analyze individual processes within an application service candidate. The agent uses the skill to extract:
- Publisher: The company or organization that released the product. For example: "Project Calico".
- Product: The specific product name. For example: "Calico".
- Description: Detailed explanation of what the process does. For example: "BIRD (BIRD Internet Routing Daemon) process running as part of Calico networking solution for Kubernetes and container orchestration. This process handles BGP routing functionality with remote control socket enabled, running as a daemon with specific Calico configuration for pod-to-pod networking and network policy enforcement."
- Service Hints: Keywords that help identify the service type. For example: "bird,calico,BGP,routing,daemon,networking,kubernetes,container,policy,socket".
- In the service information generation stage, the agent combines process details with load balancer information to generate:
- Service Name: A concise, accurate name for the service candidate. For example: "Calico BGP Routing Service".
- Service Description: A comprehensive description of the service's purpose. For example: "BIRD Internet Routing Daemon process running as part of Project Calico's networking solution for Kubernetes container orchestration. This service handles BGP routing functionality for pod-to-pod networking and network policy enforcement, operating as a daemon with remote control socket capabilities. The component is connected through Calico's container networking infrastructure to provide routing services in Kubernetes environments".
- G2 Category: Industry-standard categorization from G2.com. For example: "Container Networking".
Service Mapping Candidates Impact skill
This skill generates comprehensive impact assessments when changes are made to your infrastructure. It analyzes service connections and dependencies to predict how a change to a single component might affect other services and servers. In addition, it provides a summary of the impact analysis.
- Connection Topology: How servers within a service candidate are connected.
- Affected Servers: Which servers are directly impacted by a change.
- Service candidate: "bird [ASC000000015]".
- Impact: "Network routing disruption affecting pod-to-pod communication across Kubernetes cluster nodes due to Calico Bird BGP routing daemon failure on p-kubenode1-2, potentially causing connectivity issues for workloads on connected nodes p-kubenode1-3, p-kubenode1-4, and p-kubenode1-5".