mirror of https://github.com/ceph/ceph
203 lines
6.3 KiB
ReStructuredText
203 lines
6.3 KiB
ReStructuredText
===============
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Perf counters
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===============
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The perf counters provide generic internal infrastructure for gauges and counters. The counted values can be both integer and float. There is also an "average" type (normally float) that combines a sum and num counter which can be divided to provide an average.
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The intention is that this data will be collected and aggregated by a tool like ``collectd`` or ``statsd`` and fed into a tool like ``graphite`` for graphing and analysis. Also, note the :doc:`../mgr/prometheus` and the :doc:`../mgr/telemetry`.
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Users and developers can also access perf counter data locally to check a cluster's overall health, identify workload patterns, monitor cluster performance by daemon types, and troubleshoot issues with latency, throttling, memory management, etc. (see :ref:`Access`)
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.. _Access:
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Access
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------
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The perf counter data is accessed via the admin socket. For example::
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ceph daemon osd.0 perf schema
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ceph daemon osd.0 perf dump
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Collections
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-----------
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The values are grouped into named collections, normally representing a subsystem or an instance of a subsystem. For example, the internal ``throttle`` mechanism reports statistics on how it is throttling, and each instance is named something like::
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throttle-msgr_dispatch_throttler-hbserver
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throttle-msgr_dispatch_throttler-client
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throttle-filestore_bytes
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...
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Schema
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------
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The ``perf schema`` command dumps a json description of which values are available, and what their type is. Each named value as a ``type`` bitfield, with the following bits defined.
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+------+-------------------------------------+
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| bit | meaning |
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+======+=====================================+
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| 1 | floating point value |
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+------+-------------------------------------+
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| 2 | unsigned 64-bit integer value |
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+------+-------------------------------------+
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| 4 | average (sum + count pair), where |
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+------+-------------------------------------+
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| 8 | counter (vs gauge) |
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+------+-------------------------------------+
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Every value will have either bit 1 or 2 set to indicate the type
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(float or integer).
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If bit 8 is set (counter), the value is monotonically increasing and
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the reader may want to subtract off the previously read value to get
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the delta during the previous interval.
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If bit 4 is set (average), there will be two values to read, a sum and
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a count. If it is a counter, the average for the previous interval
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would be sum delta (since the previous read) divided by the count
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delta. Alternatively, dividing the values outright would provide the
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lifetime average value. Normally these are used to measure latencies
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(number of requests and a sum of request latencies), and the average
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for the previous interval is what is interesting.
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Instead of interpreting the bit fields, the ``metric type`` has a
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value of either ``gauge`` or ``counter``, and the ``value type``
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property will be one of ``real``, ``integer``, ``real-integer-pair``
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(for a sum + real count pair), or ``integer-integer-pair`` (for a
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sum + integer count pair).
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Here is an example of the schema output::
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{
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"throttle-bluestore_throttle_bytes": {
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"val": {
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"type": 2,
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"metric_type": "gauge",
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"value_type": "integer",
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"description": "Currently available throttle",
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"nick": ""
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},
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"max": {
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"type": 2,
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"metric_type": "gauge",
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"value_type": "integer",
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"description": "Max value for throttle",
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"nick": ""
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},
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"get_started": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Number of get calls, increased before wait",
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"nick": ""
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},
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"get": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Gets",
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"nick": ""
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},
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"get_sum": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Got data",
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"nick": ""
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},
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"get_or_fail_fail": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Get blocked during get_or_fail",
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"nick": ""
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},
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"get_or_fail_success": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Successful get during get_or_fail",
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"nick": ""
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},
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"take": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Takes",
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"nick": ""
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},
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"take_sum": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Taken data",
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"nick": ""
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},
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"put": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Puts",
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"nick": ""
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},
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"put_sum": {
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"type": 10,
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"metric_type": "counter",
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"value_type": "integer",
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"description": "Put data",
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"nick": ""
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},
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"wait": {
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"type": 5,
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"metric_type": "gauge",
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"value_type": "real-integer-pair",
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"description": "Waiting latency",
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"nick": ""
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}
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}
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Dump
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----
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The actual dump is similar to the schema, except that average values are grouped. For example::
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{
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"throttle-msgr_dispatch_throttler-hbserver" : {
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"get_or_fail_fail" : 0,
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"get_sum" : 0,
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"max" : 104857600,
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"put" : 0,
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"val" : 0,
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"take" : 0,
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"get_or_fail_success" : 0,
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"wait" : {
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"avgcount" : 0,
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"sum" : 0
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},
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"get" : 0,
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"take_sum" : 0,
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"put_sum" : 0
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},
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"throttle-msgr_dispatch_throttler-client" : {
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"get_or_fail_fail" : 0,
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"get_sum" : 82760,
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"max" : 104857600,
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"put" : 2637,
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"val" : 0,
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"take" : 0,
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"get_or_fail_success" : 0,
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"wait" : {
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"avgcount" : 0,
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"sum" : 0
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},
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"get" : 2637,
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"take_sum" : 0,
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"put_sum" : 82760
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}
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}
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