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Updates for burrow v3 version of api schema. #9

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Updates for burrow v3 version of api schema. #9

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62 changes: 34 additions & 28 deletions checks.d/burrow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,11 +8,13 @@
# project
from checks import AgentCheck

__version__ = "0.1.1"

SERVICE_CHECK_NAME = 'burrow.can_connect'

DEFAULT_BURROW_URI = 'http://localhost:8000'

CLUSTER_ENDPOINT = '/v2/kafka'
CLUSTER_ENDPOINT = '/v3/kafka'

CHECK_TIMEOUT = 10

Expand Down Expand Up @@ -54,7 +56,7 @@ def _consumer_groups_lags(self, clusters, burrow_address, extra_tags):
status = lag_json["status"]
consumer_tags = ["cluster:%s" % cluster, "consumer:%s" % consumer] + extra_tags

self.gauge("kafka.consumer.maxlag", status["maxlag"], tags=consumer_tags)
self.gauge("kafka.consumer.maxlag", status["maxlag"]["end"]["lag"], tags=consumer_tags)
self.gauge("kafka.consumer.totallag", status["totallag"], tags=consumer_tags)
self._submit_lag_status("kafka.consumer.lag_status", status["status"], tags=consumer_tags)

Expand Down Expand Up @@ -84,9 +86,12 @@ def _submit_lag_status(self, metric_namespace, status, tags):
self.gauge("%s.%s" % (metric_namespace, metric_name.lower()), value, tags=tags)

def _submit_partition_lags(self, partition, tags):
lag = partition.get("end").get("lag")
end = partition.get("end")
if not end:
return
lag = end.get("lag")
timestamp = partition.get("end").get("timestamp") / 1000
self.gauge("kafka.consumer.partition_lag", lag, tags=tags, timestamp=timestamp)
self.gauge("kafka.consumer.partition_lag", lag, tags=tags)

def _check_burrow(self, burrow_address, extra_tags):
"""
Expand All @@ -112,17 +117,16 @@ def _topic_offsets(self, clusters, burrow_address, extra_tags):
Retrieve the offsets for all topics in the clusters
"""
for cluster in clusters:
cluster_path = "%s/%s" % (CLUSTER_ENDPOINT, cluster)
offsets_topic = self._rest_request_to_json(burrow_address, cluster_path)["cluster"]["offsets_topic"]
topics_path = "%s/topic" % cluster_path
topics_path = "%s/%s/topic" % (CLUSTER_ENDPOINT, cluster)
topics_list = self._rest_request_to_json(burrow_address, topics_path).get("topics", [])
for topic in topics_list:
if topic == offsets_topic:
continue
topic_path = "%s/%s" % (topics_path, topic)
response = self._rest_request_to_json(burrow_address, topic_path)
tags = ["topic:%s" % topic, "cluster:%s" % cluster] + extra_tags
self._submit_offsets_from_json(offsets_type="topic", json=response, tags=tags)
offsets_list = []
for offset in response["offsets"]:
offsets_list.append({"offsets": [{"offset": offset, "timestamp": 1}]})
self._submit_offsets_from_json(offsets_type="topic", offsets_list=offsets_list, tags=tags)

def _consumer_groups_offsets(self, clusters, burrow_address, extra_tags):
"""
Expand All @@ -132,30 +136,32 @@ def _consumer_groups_offsets(self, clusters, burrow_address, extra_tags):
consumers_path = "%s/%s/consumer" % (CLUSTER_ENDPOINT, cluster)
consumers_list = self._rest_request_to_json(burrow_address, consumers_path).get("consumers", [])
for consumer in consumers_list:
topics_path = "%s/%s/topic" % (consumers_path, consumer)
topics_list = self._rest_request_to_json(burrow_address, topics_path).get("topics", [])
for topic in topics_list:
topic_path = "%s/%s" % (topics_path, topic)
response = self._rest_request_to_json(burrow_address, topic_path)
if not response:
continue
topics_path = "%s/%s" % (consumers_path, consumer)
topics = self._rest_request_to_json(burrow_address, topics_path).get("topics", [])
for topic in topics:
tags = ["topic:%s" % topic, "cluster:%s" % cluster,
"consumer:%s" % consumer] + extra_tags
self._submit_offsets_from_json(offsets_type="consumer", json=response, tags=tags)
self._submit_offsets_from_json(offsets_type="consumer", offsets_list=topics[topic], tags=tags)

def _submit_offsets_from_json(self, offsets_type, json, tags):
def _submit_offsets_from_json(self, offsets_type, offsets_list, tags):
"""
Find the offsets and push them into the metrics
"""
offsets = json.get("offsets")
if offsets:
# for unconsumed or empty partitions, change an offset of -1 to 0 so the
# sum isn't affected by the number of empty partitions.
offsets = [max(offset, 0) for offset in offsets]
self.gauge("kafka.%s.offsets.total" % offsets_type, sum(offsets), tags=tags)
for partition_number, offset in enumerate(offsets):
new_tags = tags + ["partition:%s" % partition_number]
self.gauge("kafka.%s.offsets" % offsets_type, offset, tags=new_tags)
# for unconsumed or empty partitions, change an offset of -1 to 0 so the
# sum isn't affected by the number of empty partitions.
offsets = []
for partition_number, offset_info in enumerate(offsets_list):
new_tags = tags + ["partition:%s" % partition_number]
latest_offset = None
offset_timestamp = 0
for offset in offset_info["offsets"]:
if not offset:
continue
if offset["timestamp"] > offset_timestamp:
latest_offset = offset["offset"]
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@jrpilat jrpilat Apr 22, 2019 •
edited
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Below this line:
offsets += [latest_offset]

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hi @jrpilat , unfortunately we're still on Kafka v2. Do you mind sharing an example json body what this looks like in v3 to help us confirm if this would break v2 or not.. Thanks!

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@lenfree is this what you need?

curl -s http://localhost:8000/v3/kafka/default/consumer/test | jq .

{
  "error": false,
  "message": "consumer detail returned",
  "topics": {
    "Maker": [
      {
        "offsets": [
          {
            "offset": 247136,
            "timestamp": 1571187859717,
            "lag": 432
          },
          {
            "offset": 247175,
            "timestamp": 1571187860801,
            "lag": 393
          },
          {
            "offset": 247203,
            "timestamp": 1571187861806,
            "lag": 365
          },
          {
            "offset": 247254,
            "timestamp": 1571187862816,
            "lag": 314
          },
          {
            "offset": 247285,
            "timestamp": 1571187863866,
            "lag": 283
          },
          {
            "offset": 247323,
            "timestamp": 1571187865134,
            "lag": 245
          },
          {
            "offset": 247378,
            "timestamp": 1571187866144,
            "lag": 190
          },
          {
            "offset": 247438,
            "timestamp": 1571187867176,
            "lag": 130
          },
          {
            "offset": 247462,
            "timestamp": 1571187868263,
            "lag": 106
          },
          {
            "offset": 247492,
            "timestamp": 1571187869406,
            "lag": 76
          },
          {
            "offset": 247504,
            "timestamp": 1571187871205,
            "lag": 64
          },
          {
            "offset": 247516,
            "timestamp": 1571187872322,
            "lag": 52
          },
          {
            "offset": 247556,
            "timestamp": 1571187873389,
            "lag": 12
          },
          {
            "offset": 247566,
            "timestamp": 1571187875598,
            "lag": 2
          },
          {
            "offset": 247568,
            "timestamp": 1571187978098,
            "lag": 0
          }
        ],
        "owner": "",
        "client_id": "",
        "current-lag": 0
      }
    ]
  },
  "request": {
    "url": "/v3/kafka/default/consumer/test",
    "host": "757320aea5d7"
  }
}

self.gauge("kafka.%s.offsets" % offsets_type, latest_offset, tags=new_tags)
offsets = [max(offset, 0) for offset in offsets]
self.gauge("kafka.%s.offsets.total" % offsets_type, sum(offsets), tags=tags)

def _find_clusters(self, address, target):
"""
Expand Down