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[chrismd <question170578@xxxxxxxxxxxxxxxxxxxxx>]

Question #170578 on Graphite changed:
https://answers.launchpad.net/graphite/+question/170578

    Status: Open => Answered

chrismd proposed the following answer:
You always want your finest precision archive to match up with the
polling interval for that dataset. This typically means you'll have
different storage schemas for datasets with different polling intervals.
As a rule of thumb I try to do everything minutely as I've found that to
be a reasonable default unit of time. It's frequent enough for active
monitoring and infrequent enough to represent a meaningful amount of
data. Of course it all depends on your data and your use cases.

As far as the retention, that's really just a matter of:
a) how old can datapoints get before you no longer care about them?
b) how much disk space do you have?

You can calculate how much disk space a scheme will cost with this
pseudo-python logic:

datapoint_size = 12 #12 bytes per datapoint with whisper (only 8 with ceres)
schema_size = sum([datapoint_size * retention for precision,retention in configured_archives])
disk_space_required = number_of_metrics * schema_size

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