|Performance metrics / Pending task metrics|
As with any database system, Cassandra performance greatly depends on underlying systems on which it is running. Tracking operating system metrics on your Cassandra nodes to watch for disk I/O, network, memory and CPU utilization trends can help you identify and troubleshoot hardware-related performance problems.
Monitoring Cassandra nodes for increasing disk and CPU utilization can help identify and remedy issues before performance degrades to unacceptable levels. The graphs in OpsCenter provide a quick way to view variations in OS metrics at a glance, and drill-down for specific data points. Especially in systems with heavy write loads, monitoring disk space is also important. It allows for advanced expansion planning while there is still adequate capacity to handle expansion and rebalancing operations.
The amount of work that a computer system performs. An idle computer has a load number of 0 and each process using or waiting for CPU time increments the load number by 1. Any value above one indicates that the machine was temporarily overloaded and some processes were required to wait. Shows minimum, average, and maximum OS load expressed as an integer.
Tracks growth or reduction in the amount of available disk space used. If this metric indicates a growth trend leading to high or total disk space usage, consider strategies to relieve it, such as adding capacity to the cluster. DataStax recommends leaving 30-50% free disk space for optimal repair and compaction operations.
The percentage of disk space that is being used by Cassandra at a given time. When Cassandra is reading and writing heavily from disk, or building SSTables as the final product of compaction processes, disk usage values may be temporarily higher than expected.
The average disk throughput for read and write operations, measured in megabytes per second. Exceptionally high disk throughput values may indicate I/O contention. This is typically caused by numerous compaction processes competing with read operations. Reducing the frequency of memtable flushing can relieve I/O contention.
The speed at which data is received and sent across the network, measured in kilobytes per second.