[checkmk-commits] Fix predictive monitoring when using single RRDs

Module: check_mk Branch: master Commit: 6dc8ddc89f60b3764a91c5b9204a5ef2caf4fc64 URL: http://git.mathias-kettner.de/git/?p=check_mk.git;a=commit;h=6dc8ddc89f60b3… Author: Mathias Kettner &lt;mk(a)mathias-kettner.de&gt; Date: Wed Feb 3 11:30:15 2016 +0100 Fix predictive monitoring when using single RRDs --- modules/check_mk.py | 4 +- modules/nagios.py | 2 +- modules/prediction.py | 102 +++++++++++-------------------------------------- 3 files changed, 25 insertions(+), 83 deletions(-) diff --git a/modules/check_mk.py b/modules/check_mk.py index 5a1d584..a07d3c8 100755 --- a/modules/check_mk.py +++ b/modules/check_mk.py @@ -137,8 +137,8 @@ tcp_cache_dir = var_dir + '/cache' logwatch_dir = var_dir + '/logwatch' www_group = None # unset logwatch_notes_url = "/nagios/logwatch.php?host=%s&file=%s" -rrdcached_socket = None # used by prediction.py -rrd_path = None # used by prediction.py +rrdcached_socket = None +rrd_path = None # Stuff for supporting Nagios check_result_path = '/usr/local/nagios/var/spool/checkresults' diff --git a/modules/nagios.py b/modules/nagios.py index f90367b..0c05879 100644 --- a/modules/nagios.py +++ b/modules/nagios.py @@ -1011,7 +1011,7 @@ no_discovery_possible = None 'aggr_summary_hostname', 'nagios_command_pipe_path', 'check_result_path', 'check_submission', 'monitoring_core', 'var_dir', 'counters_directory', 'tcp_cache_dir', 'tmp_dir', 'log_dir', - 'snmpwalks_dir', 'check_mk_basedir', 'nagios_user', 'rrd_path', 'rrdcached_socket', + 'snmpwalks_dir', 'check_mk_basedir', 'nagios_user', 'omd_root', 'www_group', 'cluster_max_cachefile_age', 'check_max_cachefile_age', 'piggyback_max_cachefile_age', 'fallback_agent_output_encoding', 'simulation_mode', 'agent_simulator', 'aggregate_check_mk', diff --git a/modules/prediction.py b/modules/prediction.py index 80b84fa..be5b674 100644 --- a/modules/prediction.py +++ b/modules/prediction.py @@ -29,85 +29,29 @@ # Export data from an RRD file. This requires an up-to-date # version of the rrdtools. -def rrd_export(filename, ds, cf, fromtime, untiltime, rrdcached=None): - # rrdtool xport --json -s 1361554418 -e 1361640814 --step 60 DEF:x=/omd/sites/heute/X.rrd:1:AVERAGE XPORT:x:HIRNI - cmd = "rrdtool xport --json -s %d -e %d --step 60 " % (fromtime, untiltime) - if rrdcached and os.path.exists(rrdcached): - cmd += "--daemon '%s' " % rrdcached - cmd += " DEF:x=%s:%s:%s XPORT:x 2>&1" % (filename, ds, cf) - # if opt_debug: - # sys.stderr.write("Running %s\n" % cmd) - f = os.popen(cmd) - output = f.read() - exit_code = f.close() - if exit_code: - raise MKGeneralException("Cannot fetch RRD data: %s" % output) - - # Parse without json module (this is not always available) - # Our data begins at "data: [...". The sad thing: names are not - # quoted here. Don't know why. We fake this by defining variables. - about = "about" - meta = "meta" - start = "start" - step = "step" - end = "end" - legend = "legend" - data = "data" - null = None - - # begin = output.index("data:") - # data_part = output[begin + 5:-2] - data = eval(output) - - return data["meta"]["step"], [ x[0] for x in data["data"] ] - - -def find_ds_in_pnp_xmlfile(xml_file, varname): - ds = None - name = None - for line in file(xml_file): - line = line.strip() - if line.startswith("<DS>"): - ds = line[4:].split('<')[0] - if name == varname: - return int(ds) - elif line.startswith("<LABEL>"): - name = line[7:].split('<')[0] - if ds and name == varname: - return int(ds) - else: - ds = None - elif line == '<DATASOURCE>': - ds = None - name = None - +# Fetch RRD historic metrics data of a specific service. returns a tuple +# of (step, [value1, value2, ...]) def get_rrd_data(hostname, service_description, varname, cf, fromtime, untiltime): - global rrdcached_socket - rrd_base = "%s/%s/%s" % (rrd_path, pnp_cleanup(hostname), - pnp_cleanup(service_description)) - # First try PNP storage type MULTIPLE - rrd_file = rrd_base + "_%s.rrd" % pnp_cleanup(varname) - ds = 1 - if not os.path.exists(rrd_file): - # We need to look into the XML file of PNP in order to - # find the correct DS number. - xml_file = rrd_base + ".xml" - if not os.path.exists(xml_file): - raise MKGeneralException("Cannot do prediction: XML file %s missing" % xml_file) - rrd_file = rrd_base + ".rrd" - if not os.path.exists(rrd_file): - raise MKGeneralException("Cannot do prediction: RRD file missing") - - # Let's parse the XML file in a silly, but fast way, that does - # not need any further module. - ds = find_ds_in_pnp_xmlfile(xml_file, varname) - if ds == None: - raise MKGeneralException("Cannot do prediction: variable %s not known" % varname) - - if omd_root and not rrdcached_socket: - rrdcached_socket = omd_root + "/tmp/run/rrdcached.sock" - return rrd_export(rrd_file, ds, cf, fromtime, untiltime, rrdcached_socket) + step = 1 + rpn = "%s.%s" % (varname, cf.lower()) # "MAX" -> "max" + lql = "GET services\n" \ + "Columns: rrddata:m1:%s:%d:%d:%d\n" \ + "OutputFormat: python\n" \ + "Filter: host_name = %s\n" \ + "Filter: description = %s\n" % ( + rpn, fromtime, untiltime, step, hostname, service_description) + try: + response = eval(simple_livestatus_query(lql))[0][0] + except Exception, e: + if opt_debug: + raise + raise MKGeneralException("Cannot get historic metrics via Livestatus: %s" % e) + + real_fromtime, real_untiltime, step = response[:3] + values = response[3:] + return step, values + daynames = [ "monday", "tuesday", "wednesday", "thursday", @@ -172,9 +116,8 @@ def get_prediction_timegroup(t, period_info): until_time = t - rel_time + period_info["slice"] return timegroup, from_time, until_time, rel_time -def compute_prediction(pred_file, timegroup, params, period_info, from_time, dsname, cf): - import math +def compute_prediction(pred_file, timegroup, params, period_info, from_time, dsname, cf): # Collect all slices back into the past until the time horizon # is reached begin = from_time @@ -206,7 +149,6 @@ def compute_prediction(pred_file, timegroup, params, period_info, from_time, dsn num_points = len(slices[0][2]) consolidated = [] for i in xrange(num_points): - # print "PUNKT %d --------------------------------------" % i point_line = [] for from_time, scale, data in slices: idx = int(i / float(scale))