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109 lines
3.5 KiB
Python
109 lines
3.5 KiB
Python
#!/usr/bin/env python
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# copy .rrd files from a remote munin master host, sum the 'df' stats from a
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# list of hosts, use them to estimate a rate-of-change for the past month,
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# then extrapolate to guess how many weeks/months/years of storage space we
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# have left, and output it to another munin graph
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import sys, os, time
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import rrdtool
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MUNIN_HOST = "munin.allmydata.com"
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PREFIX = "%s:/var/lib/munin/prodtahoe/" % MUNIN_HOST
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FILES = [ "prodtahoe%d.allmydata.com-df-_dev_sd%s3-g.rrd" % (a,b)
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for a in (1,2,3,4,5)
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for b in ("a", "b", "c", "d")
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]
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REMOTEFILES = [ PREFIX + f for f in FILES ]
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LOCALFILES = ["/var/lib/munin/prodtahoe/" + f for f in FILES ]
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WEBFILE = "/var/www/tahoe/spacetime.json"
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def rsync_rrd():
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# copy the RRD files from your munin master host to a local one
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cmd = "rsync %s rrds/" % (" ".join(REMOTEFILES))
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rc = os.system(cmd)
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assert rc == 0, rc
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def format_time(t):
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return time.strftime("%b %d %H:%M", time.localtime(t))
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def predict_future(past_s):
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start_df = []
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end_df = []
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durations = []
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for fn in LOCALFILES:
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d = rrdtool.fetch(fn, "AVERAGE", "-s", "-"+past_s, "-e", "-1hr")
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# ((start, end, step), (name1, name2, ...), [(data1, data2, ..), ...])
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(start_time, end_time ,step) = d[0]
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#print format_time(start_time), " - ", format_time(end_time), step
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names = d[1]
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#for points in d[2]:
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# point = points[0]
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# print point
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start_space = d[2][0][0]
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if start_space is None:
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return None
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# I don't know why, but the last few points are always bogus. Running
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# 'rrdtool fetch' on the command line is usually ok.. I blame the python
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# bindinds.
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end_space = d[2][-4][0]
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if end_space is None:
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return None
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end_time = end_time - (4*step)
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start_df.append(start_space)
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end_df.append(end_space)
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durations.append(end_time - start_time)
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avg_start_df = sum(start_df) / len(start_df)
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avg_end_df = sum(end_df) / len(end_df)
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avg_duration = sum(durations) / len(durations)
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#print avg_start_df, avg_end_df, avg_duration
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rate = (avg_end_df - avg_start_df) / avg_duration
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#print "Rate", rate, " %/s"
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#print "measured over", avg_duration / 86400, "days"
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remaining = 100 - avg_end_df
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remaining_seconds = remaining / rate
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#print "remaining seconds", remaining_seconds
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remaining_days = remaining_seconds / 86400
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#print "remaining days", remaining_days
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return remaining_days
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def write_to_file(samples):
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# write a JSON-formatted dictionary
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f = open(WEBFILE + ".tmp", "w")
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f.write("{ ")
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f.write(", ".join(['"%s": %s' % (k, samples[k])
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for k in sorted(samples.keys())]))
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f.write("}\n")
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f.close()
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os.rename(WEBFILE + ".tmp", WEBFILE)
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if len(sys.argv) > 1 and sys.argv[1] == "config":
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print """\
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graph_title Tahoe Remaining Space Predictor
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graph_vlabel days remaining
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graph_category tahoe
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graph_info This graph shows the estimated number of days left until storage space is exhausted
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days_2wk.label days left (2wk sample)
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days_2wk.draw LINE2
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days_4wk.label days left (4wk sample)
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days_4wk.draw LINE2"""
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sys.exit(0)
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#rsync_rrd()
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samples = {}
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remaining_4wk = predict_future("4wk")
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if remaining_4wk is not None:
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print "days_4wk.value", remaining_4wk
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samples["remaining_4wk"] = remaining_4wk
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remaining_2wk = predict_future("2wk")
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if remaining_2wk is not None:
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print "days_2wk.value", remaining_2wk
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samples["remaining_2wk"] = remaining_2wk
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write_to_file(samples)
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