Chapter 3 Statistics and Datasets
Determining the impact of a dynamic statistic
Capacity: Capacity Percent Used
Capacity System Pool Bytes Used
Capacity: System Pool Bytes Used
Capacity System Pool Percent Used
Capacity: System Pool Percent Used
Data Movement NDMP Bytes Statistics
Data Movement: NDMP Bytes Statistics
Data Movement NDMP Operations Statistics
Data Movement: NDMP Operations Statistics
Data Movement Replication Bytes
Data Movement: Replication Bytes
Data Movement Replication Operations
Data Movement: Replication Operations
Data Movement Shadow Migration Bytes
Data Movement: Shadow Migration Bytes
Data Movement Shadow Migration Ops
Data Movement: Shadow Migration Ops
Data Movement Shadow Migration Requests
Data Movement: Shadow Migration Requests
Protocol Fibre Channel Operations
Protocol: Fibre Channel Operations
Data Movement NDMP Bytes Transferred to/from Disk
Data Movement: NDMP Bytes Transferred to/from Disk
Data Movement NDMP Bytes Transferred to/from Tape
Data Movement: NDMP Bytes Transferred to/from Tape
Data Movement NDMP File System Operations
Data Movement: NDMP File System Operations
Data Movement Replication Latencies
Data Movement: Replication Latencies
Disk ZFS Logical I/O Operations
Disk: ZFS Logical I/O Operations
Memory Kernel Memory Lost to Fragmentation
Memory: Kernel Memory Lost to Fragmentation
This statistic shows HTTP Service in Oracle ZFS Storage Appliance Administration Guide requests/sec requested by HTTP clients. Various useful breakdowns are available: to show the client, filename and latency of the HTTP request.
HTTP/ WebDAV requests/sec can be used as an indication of HTTP load, and can also be viewed on the Dashboard in Oracle ZFS Storage Appliance Administration Guide .
Use the latency breakdown when investigating HTTP performance issues, especially to quantify the magnitude of the issue. This measures the latency component for which the appliance is responsible for, and displays it as a heat map so that the overall latency pattern can be seen, along with outliers. If the HTTP latency is high, drill down further on latency to identify the file, size and response code for the high latency HTTP requests, and, check other statistics for both CPU and Disk load to investigate why the appliance is slow to respond; if latency is low, the appliance is performing quickly, and any performance issues experienced on the client initiator are more likely to be caused by other factors in the environment: such as the network infrastructure, and CPU load on the client itself.
The best way to improve performance is to eliminate unnecessary work, which may be identified through the client, response code and requested filename breakdowns.
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These breakdowns can be combined to produce powerful statistics. For example:
"Protocol: HTTP/WebDAV operations per second of type get broken down by latency" (to examine latency for HTTP GETs only)
"Protocol: HTTP/WebDAV requests per second for response code '404' broken down by file name (to see which non-existant files were requested)
"Protocol: HTTP/WebDAV requests per second for client 'deimos.sf.fishpong.com' broken down by file name" (to examine files requested by a particular client)
See Network: Device bytes for a measure of network throughput caused by HTTP activity; also see Cache: ARC accesses to learn how well an HTTP read workload is returning from cache, and Disk: I/O operations for the back-end disk I/O caused.