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Home > Technology > Data Collection & Analysis
Data Collection & Analysis
MetiLinx uses a centralized data collection strategy to minimize the resource impact on the MetiLinx Sensor. Only one component, the MetiLinx Analyzer (DCM), requests data from the Sensors. It then passes out this information to the Console (for reports and real-time graphs), to iAlarm (for pre-emptive alerting when thresholds are crossed) and to other network management applications (via MetiLinx Connect).
MetiLinx can store Local Node Value (LNV), Composite Node Value (CNV) and critical sensor data (CPU, RAM, Network traffic, etc.) in a centralized repository using one of three methods:
. Flat File
. Microsoft SQL Server
. Oracle Database
Selecting one of the two database options has the added benefit of allowing administrators to generate their own customized reports. MetiLinx facilitates this by providing the database schema.
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Field Name
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Description
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Unit
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dcmid
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Internal dcm ID
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Integer
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nodeid
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Internal node ID
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Integer
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alias
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IP address of the node
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IP Format
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datemin
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Earliest date
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MM/DD/YY HH:MM:SS
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datemax
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Most Recent Data
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MM/DD/YY HH:MM:SS
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MetiLinx's alarming capabilities allow administrators to set threshold values and be alerted when crossed.
The Alarm component can monitor for several values, all selectable by the administrator. For instance, the database administrator can be alerted if the amount of free disk space on Database Server 2 drops below 1GB; thereby allowing time to take corrective action and preventing a server crash. Similarly, a web administrator can be alerted if a web server is becoming overly stressed with too much traffic.
These capabilities are an extension of the data gathered by the MetiLinx Sensors on the servers and stored by the MetiLinx Analyzer. When the administrator creates an alarm, the system notifies the MetiLinx Analyzer to gather the required sensor data from the selected servers' MetiLinx Sensors. The specific servers to monitor, the frequency and the alerting mechanism are all configurable.
Notification can be made through pop-up messages, audible sounds, email messages and SNMP traps.
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