Table of Contents
- Getting Started
- Agent-Based Management
- Data Providers
- Directory Services
- Event Log Archiving for JSIG and CMMC Compliance
- Auditing
- Hosts
- Templates
- Template Properties
- Batch Update Templates
- Assign Templates
- Log Management Templates
- SCAP Compliance Monitor
- File and Directory Monitor Templates
- Windows Monitor Templates
- Account Lockout Monitor Template
- Logon Monitor Template
- CPU Monitor Template
- Memory Monitor Template
- Disk Space Monitor Template
- SMART Monitor Template
- Process Monitor Template
- Service Monitor Template
- Performance Counter Monitor Template
- PowerShell Template
- Registry Value Monitor Template
- System Security Monitor Template
- Active Directory User Monitor Template
- Active Directory User Integrity Monitor Template
- Task Scheduler Template
- Clock Synchronization Template
- Defragment NTFS Disks Template
- Windows Audit Policy Monitor Template
- Windows Logon As Monitor Template
- Windows Update Template
- Windows Management Instrumentation (WMI) Templates
- Database Monitor Template
- Directory Service Monitor Template
- DNS Blacklist Monitor Template
- DNS Monitor Template
- Domain Expiration Monitor Template
- Network Speed Monitor Template
- Ping Monitor Template
- Database Table Reseed
- SQL Server Shrink and Backup Template
- SSH Shell
- TCP Port Scan Monitor Template
- Website Monitor Template
- Wake On LAN Template
- SSL Certificate Monitor Templates
- Email Monitor Templates
- SNMP Monitor Templates
- Windows Accounts Templates
- Monitors
- Reports
- File and Permission Reports
- Summary Reports
- Auto-Configurators
- Filters
- Actions
- Database Actions
- Desktop Actions
- Email Actions
- Event Log Actions
- Executable Actions
- File Actions
- IIS IP Address Restriction Actions
- Microsoft Teams Actions
- PowerShell Actions
- Report Actions
- Service Actions
- SMS Actions
- SNMP Trap Actions
- Syslog Actions
- Template Actions
- IIS IP Address Restriction Actions
- Action Variables
- Schedules
- Environment Variables
- Options
- Account Lockout Monitoring and Reporting
- Merging Logs
- SNMP
- SSH Shell
- Syslog
- Exporting and Importing Configuration Objects
- Shared Views
- Active Directory User and Group Filters
- Assign Actions
- Assign Azure Audit Logs
- Assign Consolidated Logs
- Assign Directories
- Assign Disks
- Assign Event Logs
- Assign Files
- Assign Services
- Assign Shares
- Auto-Config Host Assignment Properties
- Define CSV and W3C Log Entry Columns
- Define Log Entry Columns
- Define Log Entry Columns with Regular Expressions
- Executable Status
- Executable Timeline
- Explicitly Assigned Logs
- File Explorer
- General Executable Properties
- Report Columns
- Report Date/Time Ranges
- Report Security Event Log Filters
- Select Folder or File
- Target Files and Sub-Directories
- Command Line Interface
- Server Configuration
- Agent Configuration
- Troubleshooting
- Terminology
Corner Bowl Server Manager
SIEM, IPS, Server Monitoring, Uptime Monitoring and Compliance Software
AI Anomaly Detection Reports (Template Triggers)
Template Trigger AI Anomaly Detection Reports enable you to scan the History Database for Template Triggers, for example, generate a report that displays the days which the greatest trigger densities occurred. This report is typically used by network administrators that want to identify degraded performance trends.
How to create a Template Trigger Artificial Intelligence Report
- From the Menu Bar select File | New. The Create New Object View displays.
- From the Create New Object View, expand Reports.
- Expand Report | Artificial Intelligence Reports then select AI Anomaly Detection (Template Triggers). The Properties View displays.
- The Properties View contains either 4 configuration tabs.
The Options Tab
Use this view to configure the AI machine learning rules.
- Use the Template drop-down so select the target Template.
- Use the Type drop-down so select the machine learning algorithm to apply.
| Algorithm | Description |
|---|---|
| Spike | Predicts spikes in independent identically distributed (i.i.d.) time series based on adaptive kernel density estimations and martingale scores. |
| Change Point | Predicts change points in an independent identically distributed (i.i.d.) time series based on adaptive kernel density estimations and martingale scores. |
| Seasonality | This method detects this predictable interval (or period) by adopting techniques of fourier analysis. |
- Use the Column definitions controls to specify the columns to include in the report. NoteThe previously assigned Select distict column are automatically added to the 3rd column in the table.
- Use the Sort by drop-down to select the columns to sort by.
- Use the Group by time span to group anomaly periods.
Spike
- Use the Confidence slider to fine tune the anomaly detection confidence.
- Use the Sub type drop-down to determine whether to detect positive or negative anomalies, or both.
| Option | Description |
|---|---|
| Negative | Only negative anomalies are detected. |
| Positive | Only positive anomalies are detected. |
| Two Sided | Both positive and negative anomalies are detected. |
Source: Anomaly Side Enumeration
Change Point
- Use the Confidence slider to fine tune the anomaly detection confidence.
- Use the Sub type drop-down to select the martingale used for scoring.
| Option | Description |
|---|---|
| None | No martingale is used. |
| Power | The Power martingale is used. |
| Mixture | The Mixture martingale is used. |
Source: Martingale Type Enumeration
Seasonality
- Use the Threshold slider to fine tune the anomaly detection threshold.
- Use the Sensitivity slider to fine tune the anomaly detection sensitivity.
AI Anomaly Detection Options Properties View