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Managing the Exadata Database Machine
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Exadata Storage Server Monitoring
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The need for monitoring the hardware and software components comprising the Exadata Database Machine is unquestionable Sometimes, a malfunctioning hardware component or an erratic behavior of a software component can cause failures that can adversely affect performance, or even the availability of the Exadata Database Machine Being able to proactively detect and fix hardware and software issues will ensure optimal performance and healthy functioning of the Database Machine components This section will discuss the different tools and utilities available to monitor the Exadata Storage Servers The monitoring methods will ensure that the different software and hardware components of the Exadata Storage Servers are operating as advertised and, more importantly, performing to their full potential without incurring undue bottlenecks Any anomalies in the behavior of these components will be captured by the monitoring infrastructure, and the administrators will be alerted so that the corrective actions can be immediately implemented The tools available for monitoring the Exadata Storage Servers are the command-line utilities such as CellCLI and SQLPlus, and the web-based Oracle Enterprise Manager The following options for monitoring the Exadata Storage Servers are discussed in this section:
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Monitoring with metrics and alerts Monitoring of active requests on the Exadata Storage Server Monitoring using the Oracle Database v$views Using Oracle Enterprise Manager for monitoring Using Oracle Integrated Lights Out Manager
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Monitoring with Metrics and Alerts
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The Exadata Storage Server Software has a built-in infrastructure to monitor the overall health of the server and the health of its individual hardware and software components The monitoring infrastructure periodically collects information about certain parameters that are deemed critical for the normal
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Achieving Extreme Performance with Oracle Exadata
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functioning of the Exadata Storage Server When these parameters cross predefined threshold boundaries, the monitoring infrastructure will automatically trigger alerts to the concerned administrators The alerts will assist administrators to take corrective actions in a timely manner and help ensure a speedy resolution to the problem These types of problems, if left unresolved, can hamper the availability of the Exadata Storage Servers and the Exadata Database Machine Metrics and alerts form the core infrastructure behind the monitoring of Exadata Storage Servers These topics are discussed in this section
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The software and hardware components that comprise the Exadata Storage Server are characterized into entities called objects Examples of objects are cell disks, grid disks, Exadata Smart Flash Cache, host interconnect network, and the Exadata Storage Server itself Each object is associated with certain properties that measure its performance or state, and these properties are characterized as metrics An example of a metric associated with the cell disk object is the property that measures the total MBs read from the cell disk due to large I/O requests (the metric MBytes read from disk for large I/Os) The metrics are categorized into the following types based on their values:
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Instantaneous metrics always capture the current value of the property of the object being measured Cumulative metrics measure the property of the object whose values have accumulated since the metric was created Rate metrics record the rate of change of the metric value measured over a given period Transition metrics capture a change in the state of the object when the object transitions to a different state
The metric values are categorized into different domains called thresholds The different types of thresholds that are predefined by the system are normal, warning, and critical When the object associated with the metric is working as expected, the metric value will fall in the normal range, below the warning threshold A metric that falls over the critical
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Managing the Exadata Database Machine
threshold indicates that the Exadata Storage Server has encountered a critical issue with the object or the metric and the object may not be functioning as expected The metric value that falls between the warning and critical thresholds is considered to be in the warning range Metrics are measured in units that correlate to the type of metric For example, the CPU utilization metric will be measured as a percentage, and the CPU temperature will be measured in degrees Celsius Multiple metrics will be associated with an object, and all the possible metrics that have an effect on the overall functioning and behavior of the Exadata Storage Server have been predefined by the Exadata Storage Server Software Users are not allowed to modify or add to the system-defined metrics; however, they are allowed to modify the preset thresholds or create new thresholds on the built-in metrics The metric collection process in the Exadata Storage Server is similar to the Automatic Workload Repository (AWR) metrics collection of the Oracle database The CELLSRV process periodically records the metric values in the main process memory The Management Server (MS) process will periodically flush the metrics accumulated by CELLSRV from the main memory and persist it to the hard disk The metrics are then kept on disk for a default period of seven days This default period can be modified, if needed, by altering the metricHistoryDays attribute using CellCLI This example will modify the metricHistoryDays attribute to store 12 days worth of metric history:
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