Support memory profiling metrics #4239
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therve
previously approved these changes
Jul 30, 2019
truthbk
reviewed
Jul 30, 2019
| __slots__ = ('name', 'value') | ||
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| def __init__(self, name, value): | ||
| self.name = 'datadog.agent.profile.memory.{}'.format(name) |
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perhaps we could put the datadog.agent.profile.memory namespace in a global, or at least datadog.agent.profile so we can reuse when/if the cpu profiling metrics come along?
| @@ -121,9 +129,11 @@ def write_pretty_top(path, snapshot, unit_formatter, key_type, limit, cumulative | |||
| amount, unit = unit_formatter(total) | |||
| f.write('Total allocated size: {} {}\n'.format(amount, unit)) | |||
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| metrics.append(MemoryProfileMetric('check_run_total', total)) | |||
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maybe check_run_alloc? I feel like total might mislead to think it's the entire memory being used by the check, where that wouldn't be entirely accurate.
therve
approved these changes
Jul 30, 2019
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Additional Notes
The first metric is
datadog.agent.profile.memory.check_run_alloctagged by check name and version