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Use prometheus as a metric backend

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This entails writing a metric aggregation program since each worker has its
own memory, and thus own metrics because of python gunicorn. The python
client is a simple wrapper that makes web requests to it.
This commit is contained in:
Matt Jibson 2015-11-20 15:32:17 -05:00 • committed by Joseph Schorr
parent 781f2eec72
commit 3d9acf2fff
10 changed files with 502 additions and 0 deletions
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9
util/saas/metricqueue.py
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@ -4,12 +4,17 @@ import time
from functools import wraps
from Queue import Queue, Full
from util.prometheus import Histogram, Counter
from flask import g, request
logger = logging.getLogger(__name__)
resp_time = Histogram('response_time', 'HTTP response time in seconds', labelnames=['endpoint'])
resp_code = Counter('response_code', 'HTTP response code', labelnames=['endpoint', 'code'])
non_200 = Counter('response_non200', 'Non-200 HTTP response codes', labelnames=['endpoint'])
class MetricQueue(object):
def __init__(self):
self._queue = None
@ -54,10 +59,14 @@ def time_after_request(name, metric_queue):
metric_queue.put('ResponseTime', dur, dimensions=dims, unit='Seconds')
metric_queue.put('ResponseCode', r.status_code, dimensions=dims)
resp_time.Observe(dur, labelvalues=[request.endpoint])
resp_code.Inc(labelvalues=[request.endpoint, r.status_code])
if r.status_code >= 500:
metric_queue.put('5XXResponse', 1, dimensions={'name': name})
elif r.status_code < 200 or r.status_code >= 300:
metric_queue.put('Non200Response', 1, dimensions={'name': name})
non_200.Inc(labelvalues=[request.endpoint])
return r
return f