def run(server, apiKey, metricName, resource, numRecords):
grok = GrokSession(server=server, apikey=apiKey)
inc = 300
currentTimestamp = int(time.time()) - (numRecords * inc)
with grok.connect() as sock:
for i in xrange(numRecords):
value = random.random()
sock.sendall("%s %f %d\n" % (metricName, value, currentTimestamp))
currentTimestamp += inc
if i % 100 == 99:
print ".",
sys.stdout.flush()
if i == RECORDS_BEFORE_MONITOR:
print
print "Creating model...",
sys.stdout.flush()
# Monitor the metric
modelSpec = {"metric": metricName, "datasource": "custom"}
if resource is not None:
modelSpec["resource"] = resource
model = grok.createModel(modelSpec)
print "done"
def run(server, apiKey, metricName, resource, numRecords):
grok = GrokSession(server=server, apikey=apiKey)
inc = 300
currentTimestamp = int(time.time()) - (numRecords * inc)
with grok.connect() as sock:
for i in xrange(numRecords):
value = random.random()
sock.sendall("%s %f %d\n" % (metricName, value, currentTimestamp))
currentTimestamp += inc
if i % 100 == 99:
print ".",
sys.stdout.flush()
if i == RECORDS_BEFORE_MONITOR:
print
print "Creating model...",
sys.stdout.flush()
# Monitor the metric
modelSpec = {"metric": metricName, "datasource": "custom"}
if resource is not None:
modelSpec["resource"] = resource
model = grok.createModel(modelSpec)
print "done"
# "uid": uid,
# "resource": "Open File Descriptors",
# "unit": "Files Open",
# },
# "modelParams": {
# "min": 0,
# "max": 20000,
# }
# })
#
models = grok.createModel({"datasource": "custom",
"metricSpec": {
"uid": uid,
"resource": "My Resource Name",
"unit": "Files Open",
},
"modelParams": {
"min": 0,
"max": 20000,
}
})
model = models[0]
assert model["uid"] == uid
assert model["name"] == METRIC_NAME
# Get model status
for _ in xrange(30):
modelResponse = grok.get(grok.server + "/_models/" + uid, auth=grok.auth)
models = modelResponse.json()
model = models[0]
for metric in grok.listMetrics("custom"):
if metric["name"] == METRIC_NAME:
uid = metric["uid"]
print 'Metric "%s" has uid: %s' % (METRIC_NAME, uid)
break
else:
print (
'"%s" metric does not exist (yet). You can create the metric by'
' sending data to Grok. See "sample-collect-data.py" for a'
" simple script that you can use to periodically sample open"
" file descriptors, and report the results to the Grok Custom"
" Metrics endpoint" % METRIC_NAME
)
# Send model creation request to create a model connected to the metric
models = grok.createModel({"uid": uid, "datasource": "custom"})
model = models[0]
assert model["uid"] == uid
assert model["name"] == METRIC_NAME
# Get model status
for _ in xrange(30):
modelResponse = grok.get(grok.server + "/_models/" + uid, auth=grok.auth)
models = modelResponse.json()
model = models[0]
if model["status"] == 1:
break
time.sleep(10)
else:
raise Exception('Model did not transition to "ready" status in a ' "reasonable amount of time.")
# "uid": uid,
# "resource": "Open File Descriptors",
# "unit": "Files Open",
# },
# "modelParams": {
# "min": 0,
# "max": 20000,
# }
# })
#
models = grok.createModel({
"datasource": "custom",
"metricSpec": {
"uid": uid,
"resource": "My Resource Name",
"unit": "Files Open",
},
"modelParams": {
"min": 0,
"max": 20000,
}
})
model = models[0]
assert model["uid"] == uid
assert model["name"] == METRIC_NAME
# Get model status
for _ in xrange(30):
modelResponse = grok.get(grok.server + "/_models/" + uid,
auth=grok.auth)
models = modelResponse.json()
