- About LogicMonitor
- Cloud Monitoring
- Dashboards and Widgets
- Getting Started
- LM Service Insight
- About LogicModules
- Creating & Managing DataSources
- Active Discovery
- Data Collection Methods
- Groovy Support
- PowerShell Support
- Setting Up JobMonitors
- Help & Troubleshooting
- User-Defined AppliesTo Functions
- SNMP sysOID Maps
- Rest API Developers Guide
- RPC API Developers Guide - Deprecated
- Servicenow CMDB Integration
- Terminology and Syntax
DataSources are templates that define what numerical data should be collected, how it should be collected, and what values should be graphed and trigger alerts.
There are four sections included in every DataSource definition:
The General Information section includes identifying information about the DataSource. This includes the collection method that will be used to collect data, how often data will be collected, and from which devices data will be collected.
The unique name of the DataSource. As a best practice, this name should be descriptive: specify the platform or application name first, then specify a specific component of the platform.
For instance: “Tomcat Threads-“, or “Aruba Controller Power Supply-“.
The name the DataSource will be displayed with on the Devices page. This name does not need to be unique (e.g. there can be several DataSource that display as “CPU”, as they apply to different kinds of devices). As a best practice, the display name should be shorter than the full DataSource name. For example, “Services” instead of “Windows Services”, or “VIPs” instead of “Citrix Netscaler VIPs.”
Note that the DataSource name and display name cannot include the operators and comparison functions available in LogicMonitor’s datapoint expression syntax, as discussed in Complex Datapoints.
The description that will be associated with this DataSource. As a best practice, if the DataSource name is not unambiguous as to what the DataSource is collecting, the description field should provide enough information that someone seeing the name and the description will be clear what the DataSource does.
This field can contain any technical notes associated with the DataSource.
The DataSource Group to which the DataSource will be added. If this field is left empty, the DataSource will not be added to a DataSource group. If you enter text that does not match an existing DataSource Group, one will be created.
For example, all the Dell hardware monitoring DataSources are assigned the group Dell. This collapses those DataSources to a single DataSource group entry that can be expanded.
The Applies To field accepts LogicMonitor’s AppliesTo scripting as input to determine which resources will be associated with this DataSource. For detailed information on using this field (including its wizard and test functionality), along with an overview of the AppliesTo scripting syntax, see AppliesTo Scripting Overview.
The Collect every field defines how frequently data is collected. This field should be set to a collection interval (i.e. polling cycle) that is appropriate for the type of data being collected. Metrics that change frequently (e.g. CPU) or require immediate attention in the event of an error (e.g. ping loss) should have a shorter polling cycle, such as one minute, whereas metrics that can tolerate a longer delay in alerting or change less frequently (e.g. drive loss in a RAID system, disk utilization) should have a longer polling cycle, such as five minutes.
Note: Longer polling cycles impose less load on the resource being monitored, the Collector, and the LogicMonitor platform.
Changing the Collection Interval
Once a DataSource has been applied to one or more resources and monitored instances are created for those resources, the underlying data storage is created with some dependency on the collection interval. In order to minimize data loss, this underlying data storage isn’t updated when you change the collection interval for the DataSource.
This impacts how data is stored and displayed. For example, if the collection interval is decreased (e.g. reduced from 15 minutes to one minute), the data is collected and evaluated for alerts on the new schedule, but only stored (and hence graphed) according to the old schedule. In other words, 15 data values will be collected (one per minute according to the new collection interval), but instead of each being stored individually, the average of these 15 values will be what gets stored every 15 minutes (per the old collection interval).
Note: You can view the collection interval with which the underlying datastore was created by downloading a DataSource graph’s raw data. The downloaded data will show timestamps for each new entry of collected data. For more information on downloading data from a DataSource graph, see Graphs Tab.
The Collector field defines the mechanism that will be used to collect data.
If this option is checked, the DataSource will be multi-instance. You should make your DataSource multi-instance if you know that there are multiple occurrences of the object you would like to monitor (e.g. multiple disks or volumes on a server).
If the DataSource is multi-instance (i.e. the Multi-instance option is selected in the General Information section), then you can use LogicMonitor’s Active Discovery process to find (and place into monitoring) all of the similar components of a particular type on a given system. The output of an Active Discovery process is one or more instances for which LogicMonitor can collect a particular type of data. For detailed information on Active Discovery, including configuration, see Active Discovery.
Certain data collection methods require you to configure specific attributes in this section. As a best practice, the Name field in the SNMP, JMX, etc. Collector Attributes section should reflect the name used by the entity that defined the object to be collected (i.e. use the oid object name for SNMP data, the WMI property name for WMI data, etc.). For more information, see the Data Collection Methods topic, which features specific instructions for each of the data collection protocols supported.
Each DataSource must have one or more datapoints that define what information to collect and store. Once datapoints are identified, they can be used to trigger alerts when data from a device exceeds the threshold(s) you’ve specified, or when there is an absence of expected data. For more information on configuring a DataSource’s datapoints, see Datapoint Overview.
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