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check_elasticsearch_jvm
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#!/usr/bin/env python
from nagioscheck import NagiosCheck, UsageError
from nagioscheck import PerformanceMetric, Status
import urllib2
try:
import json
except ImportError:
import simplejson as json
class ElasticSearchJvmCheck(NagiosCheck):
version = '0.3.0'
def __init__(self):
NagiosCheck.__init__(self)
self.add_option('H', 'host', 'host', "Hostname or network "
"address to probe. The ElasticSearch API "
"should be listening here. Defaults to "
"'localhost'.")
self.add_option('p', 'port', 'port', "TCP port to probe. "
"The ElasticSearch API should be listening "
"here. Defaults to 9200.")
self.add_option('w', 'warn', 'warn', "Warning threshold percent")
self.add_option('c', 'crit', 'crit', "Critical threshold percent")
def check(self, opts, args):
host = opts.host or "localhost"
port = int(opts.port or '9200')
#
# Data retrieval
#
# Request a bunch of useful numbers that we export as perfdata.
# Details like the number of get, search, and indexing
# operations come from here.
es_node = get_json(r'http://%s:%d/_nodes/_local/?all=true' % (host, port))
es_stats = get_json(r'http://%s:%d/_nodes/_local/'
'stats?all=true' % (host, port))
myid = es_stats['nodes'].keys()[0]
es_node_jvm = get_json(r'http://%s:%d/_nodes/%s/stats?jvm=true' % (host, port, myid))
#
# Perfdata
#
perfdata = []
def dict2perfdata(base, metrics):
for metric in metrics:
if len(metric) == 2:
label, path = metric
unit = ""
elif len(metric) > 2:
label, path, unit = metric
else:
continue
keys = path.split(".")
value = base
for key in keys:
if value is None:
break
try:
value = value[key]
except KeyError:
value = None
break
if value is not None:
metric = PerformanceMetric(label=label,
value=value,
unit=unit)
perfdata.append(metric)
# Add cluster-wide metrics first. If you monitor all of your ES
# cluster nodes with this plugin, they should all report the
# same figures for these labels. Not ideal, but 'tis better to
# graph this data multiple times than not graph it at all.
metrics = [["heap_committed", 'heap_committed_in_bytes', "B"],
["heap_used", 'heap_used_in_bytes', "B"],
["non_heap_committed", 'non_heap_committed_in_bytes', "B"],
["non_heap_used", 'non_heap_used_in_bytes', "B"],
["old_gen_used", 'pools.CMS Old Gen.used_in_bytes', "B"],
["perm_gen_used", 'pools.CMS Perm Gen.used_in_bytes', "B"],
["eden_used", 'pools.Par Eden Space.used_in_bytes', "B"],
["survivor_used", 'pools.Par Survivor Space.used_in_bytes', "B"],
["code_cache", 'pools.Code Cache.used_in_bytes', "B"]
]
dict2perfdata(es_stats['nodes'][myid]['jvm']['mem'], metrics)
metrics = [["heap_max", 'heap_max_in_bytes', "B"],
["non_heap_max", 'non_heap_max_in_bytes', "B"],
["direct_max", 'direct_max_in_bytes', "B"]]
dict2perfdata(es_node['nodes'][myid]['jvm']['mem'], metrics)
collectors = es_node_jvm["nodes"][myid]["jvm"]["gc"]["collectors"].keys()
for collector in collectors:
# Full collector names are too long for RRD; contract them
# to initialisms.
collector_initials = "".join([ c for c in collector if (
ord(c) >= ord('A') and
ord(c) <= ord('Z')
)])
collector_slug = collector_initials.lower()
metrics = [["%s_collections" % collector_slug, "collectors.%s.collection_count" % collector, "c"],
["%s_time_ms" % collector_slug, "collectors.%s.time_in_millis" % collector, "c"],
]
dict2perfdata(es_node_jvm["nodes"][myid]["jvm"]["gc"], metrics)
metrics = [["collections", "collection_count", "c"],
["collection_time_ms", "collection_time_in_millis", "c"],
]
dict2perfdata(es_node_jvm["nodes"][myid]["jvm"]["gc"], metrics)
heap_used_b = int(es_stats['nodes'][myid]['jvm']['mem']['heap_used_in_bytes'])
heap_max_b = int(es_node ['nodes'][myid]['jvm']['mem']['heap_max_in_bytes'])
# ES 1.0 changed their keys, dropping heap_used & heap_max. If they don't exist, lets create them again from
# their byte values. Expected to be of the form '1.3gb'
try:
heap_used = es_stats['nodes'][myid]['jvm']['mem']['heap_used']
heap_max = es_node ['nodes'][myid]['jvm']['mem']['heap_max']
except KeyError:
heap_used = str(round(es_stats['nodes'][myid]['jvm']['mem']['heap_used_in_bytes']/1048576.0,2))+'gb'
heap_max = str(round(es_node ['nodes'][myid]['jvm']['mem']['heap_max_in_bytes']/1048576.0,2))+'gb'
heap_usage_percent = (float(heap_used_b)/float(heap_max_b))*100
if opts.crit and heap_usage_percent >= float(opts.crit):
raise Status("critical","JVM Heap Usage: %d%% %s/%s" % (heap_usage_percent,str(heap_used),str(heap_max)),perfdata)
if opts.warn and heap_usage_percent >= float(opts.warn):
raise Status("warning","JVM Heap Usage: %d%% %s/%s" % (heap_usage_percent,str(heap_used),str(heap_max)),perfdata)
raise Status("ok","JVM Heap Usage: %d%% %s/%s" % (heap_usage_percent,str(heap_used),str(heap_max)),perfdata)
def get_json(uri):
try:
f = urllib2.urlopen(uri)
except urllib2.HTTPError, e:
raise Status('unknown', ("API failure",
None,
"API failure:\n\n%s" % str(e)))
except urllib2.URLError, e:
# The server could be down; make this CRITICAL.
raise Status('critical', (e.reason,))
body = f.read()
try:
j = json.loads(body)
except ValueError:
raise Status('unknown', ("API returned nonsense",))
return j
if __name__ == '__main__':
ElasticSearchJvmCheck().run()
# vim: ts=8 et