Pattern diagnostic agentic workflow

  • Release version: Zurich
  • Updated June 9, 2026
  • 2 minutes to read
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    Summary of Pattern diagnostic agentic workflow

    The Pattern diagnostic agentic workflow is designed for Discovery administrators to efficiently investigate missing Configuration Item (CI) attributes in the CMDB related to pattern-based Discovery. It automates the process of identifying gaps, parsing discovery logs, diagnosing root causes, and suggesting remediation actions, all accessible directly through the Now Assist panel without manual log file navigation.

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    This workflow specifically supports CIs discovered via pattern-based Discovery, addressing the complexity of analyzing nested JSON logs and multiple database tables by streamlining the investigation into a guided, automated experience.

    Key Features

    • Natural-language interaction: Administrators initiate investigations by asking questions in the Now Assist panel.
    • Automated root cause analysis: The workflow resolves the CI class and attributes, identifies CIs with missing attributes, and parses discovery logs to uncover causes.
    • Suggested remediation: Based on detected root causes, the workflow provides remediation recommendations via the EF Remediation Agent.
    • Agent-based architecture: Utilizes the Pattern diagnostic agent to run autonomous scripts and the EF Remediation Agent to deliver fixes.
    • Scope limitations: Supports only default pattern metadata for pattern-discovered CIs, analyzes up to five sample CIs per query, and focuses on the first CI's logs for issue detection.

    Requirements

    • Now Assist for IT Operations Management (ITOM) plugin must be installed.
    • User must have the discoveryadmin role.

    Practical Use Cases

    The workflow addresses common scenarios involving missing CI attributes across different CI types:

    • Direct infrastructure (Linux Server): Investigates missing attributes like cpumanufacturer by querying discovery logs using the CI’s IP address.
    • Applicative patterns (MySQL database): Handles attributes on CIs discovered via host servers by resolving relationships to the host’s IP and analyzing host discovery logs.
    • Cloud patterns (AWS Auto Scaling Group): Supports cloud CIs identified via SA-LDC identifiers, navigating hosting relationships and querying logs using these identifiers and process IDs.

    Benefits for ServiceNow Customers

    This workflow streamlines the complex investigation of missing pattern-based Discovery CI attributes, reducing manual effort and expertise required to analyze logs and metadata. It accelerates root cause identification and provides actionable remediation guidance, enhancing CMDB data quality and reliability. By integrating with Now Assist, it offers a user-friendly, conversational interface to simplify Discovery troubleshooting.

    The Pattern diagnostic agentic workflow helps Discovery administrators investigate missing CI attributes. It identifies the gap, parses discovery logs, identifies the root cause, and suggests remediation — without manually navigating log files.

    When Discovery runs, it populates CI attributes in the CMDB using both probe-based and pattern-based discovery. The Pattern diagnostic agentic workflow supports investigation into CIs discovered through pattern-based discovery. When an attribute is missing, identifying the cause requires navigating multiple tables and interpreting nested JSON in discovery logs. The Pattern diagnostic agentic workflow automates this investigation and suggests a remediation action, all from the Now Assist panel.

    Requirements

    Now Assist for IT Operations Management (ITOM) must be installed on your instance. For more information, see Install the ServiceNow Otto for IT Operations Management (ITOM) plugin.

    Role required: discovery_admin.

    Pattern diagnostic agentic workflow overview

    A Discovery administrator triggers the workflow by asking a natural-language question in the Now Assist panel. The workflow resolves the CI class and surfaces the attributes that Discovery is responsible for populating. The administrator selects the attribute to investigate. The workflow then identifies affected CI records with the selected attribute missing, parses the relevant discovery logs to identify the root cause, and suggests a remediation.

    The workflow uses two agents:

    • Pattern diagnostic agent: Receives the administrator's query and runs script tools autonomously to investigate the missing attribute.
    • EF Remediation Agent: Receives the identified root cause and suggests a remediation.

    Scope

    The workflow covers attribute coverage gaps for CI classes discovered through pattern-based Discovery. The following conditions apply:

    • Only CIs discovered through patterns are supported for analysis.
    • Analysis is based on the pattern metadata table (sn_disco_ai_pattern_metadata). This table contains metadata about the patterns populating a CI and its attributes. Only default pattern information is included; customizations made to patterns aren't considered.
    • Log analysis focuses on the first CI in the sample. If issues are found, the workflow reports them and stops. If no issues are found, it checks the next CI in the list, up to the sample limit of five.

    Examples

    The following scenarios illustrate how the workflow handles different CI and pattern types.

    Scenario 1: Direct infrastructure (Linux Server)

    The workflow investigates a missing cpu_manufacturer attribute on Linux Server CIs. The workflow resolves the CIs IP address and queries the discovery logs directly. It returns a full report with sample CIs investigated, link to CIs, root cause and remediation guidance.

    Scenario 2: Applicative pattern (MySQL database)

    The workflow investigates a missing attribute on a MySQL database CI. MySQL CIs are discovered through their host servers. The workflow navigates the Runs on relationship to resolve the host server's IP address and queries the discovery logs on the host, not the MySQL instance. It returns a full report with sample CIs investigated, link to CIs, root cause and remediation guidance.

    Scenario 3: Cloud pattern (AWS Auto Scaling Group)

    The workflow investigates a missing cluster_connection attribute on an AWS Auto Scaling Group CI. Cloud CIs use an SA-LDC identifier instead of a traditional IP address. The workflow navigates the Hosted on relationship to resolve the SA-LDC identifier and searches logs using the identifier and process ID. It returns a full report with sample CIs investigated, link to CIs, root cause and remediation guidance.