6ea362da0b
The prometheus datasource was reporting host_ram_usage in MiB as
described in the docstring for the base datasource interface
definition [1].
However, the gnocchi datasource is reporting it in KiB following
ceilometer metric `hardware.memory.used` [2] and the strategies
using that metric expect it to be in KiB so the best approach is
to change the unit in the prometheus datasource and update the
docstring to avoid missunderstandings in future. So, this patch
is fixing the prometheus datasource to return host_ram_usage
in KiB instead of MiB.
Additionally, it is adding more unit tests for the check_threshold
method so that it covers the memory based strategy execution, validates
the calculated standard deviation and adds the cases where it is below
the threshold.
[1] 15981117ee/watcher/decision_engine/datasources/base.py (L177-L183)
[2] https://docs.openstack.org/ceilometer/train/admin/telemetry-measurements.html#snmp-based-meters
Closes-Bug: #2113776
Change-Id: Idc060d1e709c0265c64ada16062c3a206c6b04fa
15 lines
634 B
YAML
15 lines
634 B
YAML
---
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fixes:
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- |
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When running an audit with the `workload_stabilization` strategy with
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`instance_ram_usage` metric in a deployment with prometheus datasource,
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the host metric for the ram usage was wrongly reported with the incorrect
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unit which lead to incorrect standard deviation and action plans due to the
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application of the wrong scale factor in the algorithm.
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The host ram usage metric is now properly reported in KB when using a
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prometheus datasource and the strategy `workload_stabilization` calculates
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the standard deviation properly.
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For more details: https://launchpad.net/bugs/2113776
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