Availability Management

Auto-Discovery of Infrastructure Components

Zenoss scans the entire IT infrastructure discovering all the devices on the network and their relationships. Auto-Discovery enables Operators and Administrators to have confidence and certainty about what is in their environment, to clearly understand how each component is configured, and to perceive dependencies among components.

• Streamlines the setup and configuration of monitoring
• Begins monitoring as soon as the device is discovered
• Removes the need for cumbersome manual entry of IP addresses and server names
• Continuously finds new devices as they are added to the network

Inventory and Change Tracking

Zenoss provides inventory management and change tracking services that allow operators to maintain a current understanding of their IT environment. Specific Inventory and Change Tracking features include:

Automatic Change History & Detection

• Automatic logging of change history during auto-discovery and manual population
• Automatic event generation and alerting based on change type and affected resource

Manual Field Population

• Manual addition of new devices
• Creation of custom fields to capture device information
• Search for devices based on custom fields

Reporting

• Global Inventory
• Change History
• Device Detail Information

External API

• Easily import IT Component information from outside resources
• Integrate with other inventory repositories via Web Services

Grouping, Organization & Classification

• Organize devices into user-defined groups representing business services
• Association of devices with geographic locations
• Ability to classify devices with varying "production level" tags such as "in maintenance" or "decommissioned"

Availability Monitoring

Zenoss provides a complete set of availability monitors that actively test key resources across the infrastructure to ensure that all devices are ready to respond to end user requests. These tests are all performed with agentless technology, which eliminates the risk associated with loading monitoring software on target systems. Specific tests and features include:

Scheduled Availability Tests

• ICMP response
• SNMP response
• Standard TCP/IP services (HTTP, SMTP, etc.)
• Specified TCP/IP ports with regular expression matching
• Windows service availability
• Windows process availability
• Linux/Unix process availability
• URL availability
• Nagios Plug-In Support

Dependency Tracking

• Intelligently suppress "downstream" tests and alerts based on layer 3 network dependencies

Event Generation

• Generate real-time events and alerts based on availability issues

Reporting

• Ping Issues
• SNMP Issues
• SLA Reporting

Performance Monitoring

Zenoss Performance monitoring helps ensure that any IT resource (or any defined group of resources) is meeting expected service levels. The Zenoss high-speed Agentless collection mechanism ensures that data is available in real-time, without adding overhead to the monitored component.

Collection Types

• Any SNMP enabled device
• Agentless JMX performance monitoring for all Java Application Servers
• Nagios and Cacti performance collection scripts
• Custom performance collection plug-ins
• Windows data collection via WMI & Perfmon
• Secure Shell (SSH) data collection for Unix and Linux Servers

Thresholds

• Ability to set multiple threshold levels on a specific metric
• Ability to generate events & alerts based on thresholds with unique severities

Graphing & Reporting

• Graphing of Trends over time: hourly, weekly, monthly & yearly
• Historical reports available for all performance data collected

Synthetic Transactions

Combining end user perspective tests (such as URL monitoring) with process, component, and interface monitoring gives IT staff information they need to quickly identify problems and potential outage locations. Synthetic Transaction monitoring provides:

• Active availability and performance monitoring of e-mail, database, and web applications
• Scheduled Control Transactions at key times of the day
• Standard reports for availability and performance trends

Predictive Threshold Trending

Predictive thresholds use statistical algorithms to help determine when an outage is occurring. Instead of using hard-coded threshold values, predicative thresholds will alert when a parameter measurement starts to suddenly change beyond its typical values.

• Smart Alerts that make intelligent decisions based on statistical data trends
• Find problems associated with sudden spikes that are not detected with statistical thresholds
• Achieve better Service Level Management using both static and dynamic thresholds