Use alerts to monitor your instance

  • Release version: Australia
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of Use Alerts to Monitor Your Instance

    ServiceNow Instance Observer offers a comprehensive alerting system to monitor your platform’s health, performance, and user experience. These alerts are categorized to help you quickly identify and take action on issues affecting transactions, infrastructure, database health, email processing, job execution, user sessions, event queue management, messaging bus performance, data volume growth, application host health, and AI/ML-driven anomalies.

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    Key Features

    • Transaction Monitoring: Detects anomalies like transaction volume drops or spikes, slow response times, and database query delays at both system-wide and node levels.
    • Node and Infrastructure Health: Alerts on CPU, memory usage, garbage collection delays, and load balancer container resource utilization to prevent bottlenecks or failures.
    • Database Performance: Monitors CPU usage on database hosts, replication lag, row locks, and abnormal growth of databases and tables to maintain data reliability.
    • Email Processing: Tracks delays or failures in inbound and outbound email flows to ensure timely communication.
    • Scheduler and Job Execution: Identifies stuck schedulers, long-running jobs, and abnormal thread activity to facilitate smooth job lifecycle management.
    • User Sessions and Activity: Provides insight into user login patterns across the instance and individual nodes for security and usage monitoring.
    • Event Queue and Semaphore Management: Monitors event backlog, semaphore wait times, and queue depths critical for debugging event handling and job throttling.
    • Asynchronous Messaging Bus (AMB): Observes outgoing message queue sizes and utilization for real-time application behavior insights.
    • Data Volume Monitoring: Flags excessive growth in history or list data that could degrade performance.
    • Application Host Health: Alerts on CPU overload at the application layer to maintain service responsiveness.
    • AI/ML Intelligent Alerts: Employs AI-driven anomaly detection to proactively identify unusual patterns affecting instance health.
    • Key Alerts and Notifications: Enables setting customized alert thresholds using historical data and configuring targeted notification recipients.

    Practical Application for ServiceNow Customers

    • Manage Alerts Efficiently: Directly act on threshold alerts from notifications to quickly resolve performance or health issues.
    • Monitor Application Performance: Set alerts to track average response times and receive proactive notifications about degradations.
    • Use Popular and Guided Alerts: Leverage pre-configured common alerts for quick setup and notifications tailored to instance performance monitoring.
    • Customize Long Pending Jobs Alerts: Configure notifications based on job priority to manage groups of pending jobs efficiently.
    • Integrate with ServiceNow and Third-Party Systems: Route Instance Observer alert notifications to ServiceNow instances, external systems, or via email/SMS for unified monitoring.
    • Custom Payloads for Integrations: Define and manage JSON payloads for alert integrations to tailor notifications to your operational workflows.

    Expected Outcomes

    By utilizing Instance Observer alerts, ServiceNow customers can maintain optimal platform health, quickly detect and respond to performance anomalies, ensure timely communication processing, and streamline job and user activity monitoring. The integration capabilities and AI-driven insights empower teams to proactively manage their instances, reduce downtime, and enhance overall user experience.

    ServiceNow Instance Observer provides a comprehensive set of alerts designed to monitor platform health, performance, and user experience. These alerts are categorized for easy consumption and actionability.

    Transactions
    Monitors application transactions for anomalies, spikes, or degradations in performance such as:
    • Transaction Decrease: Detects a drop in total transaction volume
    • Transaction Decrease Node: Identifies transaction volume drop per node
    • Transaction Increase: Flags unexpected transaction surges
    • Transaction Increase Node: Highlights node-level transaction spikes
    • Response Time: Triggers when system-wide response time increases
    • Response Time Node: Flags nodes with degraded response times
    • Database Response Time: Monitors database-level latency impacting transactions
    • Slow Queries Per Second: Identifies the volume of slow database queries affecting responsiveness
    Node health (CPU, memory, or garbage collection)
    Tracks node infrastructure health to avoid bottlenecks or failures:
    • Node CPU time: High CPU usage alert for a node
    • Node memory: Monitors memory consumption patterns
    • Node garbage collection time: Tracks JVM GC delays
    • Load balancer container CPU utilization: Flags CPU overload on LB containers
    • Load balancer container memory utilization: Detects memory exhaustion on LB containers
    Database performance and health
    Covers critical database indicators to verify query health and data reliability:
    • Database host health CPU: High CPU on primary DB host
    • Shards host health CPU: Resource issues on shard hosts
    • Read replica host health (CPU): Read-replica CPU anomalies
    • Standby replication lag: Lag in standby DB replication
    • InnoDB row lock: Frequency of row lock waits
    • Primary database growth: Flags abnormal growth in primary DB
    • Database table growth: Specific table-level growth indicators
    Inbound and outbound email
    Promotes timely delivery and ingestion of email-based communications:
    • Outbound email: Delays or failures in outbound email processing
    • Inbound email: Issues in ingesting incoming emails
    Scheduler and job execution
    Helps detect issues in the job execution life cycle:
    • Scheduler stuck: Scheduler not progressing or blocked
    • Long-running jobs: Jobs exceeding typical run time
    • Specific long-running jobs: Custom job monitoring
    • Thread running: Threads running unusually long or in high volume
    Session and user activity
    Tracks user login behavior across instance and nodes:
    • User session logged in – Instance: Log in activity across instance
    • User session logged in – Node: Node-wise session metrics
    Event queue and semaphore management
    Critical for debugging platform event handling and job execution throttling:
    • Default semaphore mean: Semaphore wait time trends
    • Default semaphore QDepth: Depth of queued semaphore requests
    • Integrated semaphore: Monitors integrated semaphore contention
    • Event queue check: Tracks backlog in event queues
    • Specific queue for events: Custom event queue monitoring
    • High priority event queue: Monitors mission-critical event queues
    • ECC queue: External communication channel backlog alerts
    Asynchronous Messaging Bus (AMB)
    Internal messaging bus observability for real-time app behavior:
    • AMB send queue depth: Size of outgoing message queue
    • AMB send in use: Utilization of AMB sending capacity
    Historical or list data volume
    Monitors growth of historical or list data that can impact performance:

    History list length: Flags excessive record count in history tables.

    Application host health
    Monitors health at the application layer:

    Application host health CPU: Application-tier CPU overload alerts.

    AI/ML or intelligent alerting
    Includes alerts generated via AI/ML-based behavior analysis:

    Auriga Intelligent: AI-driven anomaly or pattern detection alerts.