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import agent_util
from base64 import b64encode
import string
import urllib
import logging
try:
# Python 2.x
from httplib import HTTPConnection, HTTPSConnection, HTTPException
except:
from http.client import HTTPConnection, HTTPSConnection, HTTPException
BYTES_TO_KB_KEYS = [
"memory",
"nodes.mem_used",
"nodes.io_read_bytes",
"nodes.mem_used_details.rate",
"nodes.io_read_bytes_details.rate",
"nodes.io_write_bytes",
"nodes.io_write_bytes_details.rate",
]
def execute_query(config, command, option=""):
if command == "nodes":
# For nodes we want to double check we haven't got a local cache version
# first.
cached_result = agent_util.LOCAL_CACHE_RESULTS.get("rabbit@/api/nodes")
if cached_result:
logging.info(
"Retrieved information from the local cache for rabbit@/api/nodes"
)
return cached_result
elif command == "queues":
cached_result = agent_util.LOCAL_CACHE_RESULTS.get("rabbit@/queues")
if cached_result:
logging.info(
"Retrieved information from the local cache for rabbit@/api/queues"
)
auth = b64encode("%s:%s" % (config["username"], config["password"]))
headers = {
"Authorization": "Basic %s" % auth,
}
output = None
conn_host = config.get("management_interface_host", "http://localhost")
if conn_host.startswith("https"):
conn = HTTPSConnection(
string.replace(conn_host, "https://", ""),
config["management_interface_port"],
)
else:
conn = HTTPConnection(
string.replace(conn_host, "http://", ""),
config["management_interface_port"],
)
conn.request("GET", "/api/" + command, headers=headers)
r = conn.getresponse()
status, output = r.status, r.read()
conn.close()
if command == "nodes":
# Save the latest result in our internal cache
agent_util.LOCAL_CACHE_RESULTS["rabbit@/api/nodes"] = output
elif command == "queues":
agent_util.LOCAL_CACHE_RESULTS["rabbit@/queues"] = output
return output
class RabbitMQPlugin(agent_util.Plugin):
textkey = "rabbitmq"
label = "rabbitmq"
DEFAULTS = {
"management_interface_host": "http://localhost",
"management_interface_port": 15672,
"username": "guest",
"password": "guest",
}
@classmethod
def get_metadata(self, config):
status = agent_util.SUPPORTED
msg = None
# check if rabbitmq is even installed
installed = agent_util.which("rabbitmqctl")
if not installed and not config.get("from_docker"):
self.log.info("rabbitmqctl binary not found")
status = agent_util.UNSUPPORTED
msg = "rabbitmqctl binary not found"
return {}
INTERFACE_NOT_FOUND_ERROR = """
No [rabbitmq] config block was found in the config file and we were unable
to access the HTTP management interface via the expected port (%s). Please
verify that the RabbitMQ management plugin is installed.
"""
# check that management plugin is installed and running
if config:
new_config = self.DEFAULTS.copy()
new_config.update(config)
config = new_config
else:
config = self.DEFAULTS
# check the specified port
try:
conn_host = config.get("management_interface_host", "http://localhost")
if conn_host.startswith("https"):
conn = HTTPSConnection(
string.replace(conn_host, "https://", ""),
config["management_interface_port"],
)
else:
conn = HTTPConnection(
string.replace(conn_host, "http://", ""),
config["management_interface_port"],
)
conn.request("GET", "/")
r = conn.getresponse()
conn.close()
except Exception:
status = agent_util.MISCONFIGURED
msg = INTERFACE_NOT_FOUND_ERROR % config["management_interface_port"]
self.log.exception(
"Interface not found %s" % config["management_interface_port"]
)
self.log.info(msg)
if status == agent_util.SUPPORTED and r.status != 200:
status = agent_util.MISCONFIGURED
msg = INTERFACE_NOT_FOUND_ERROR % config["management_interface_port"]
self.log.info(msg)
objects, queue_opts = None, None
queues_schema = {"resource": "string", "vhost": "string", "queue": "string"}
queue_opts = []
node_opts = []
if status == agent_util.SUPPORTED:
try:
overview = agent_util.json_loads(execute_query(config, "overview"))
objects = [obj.title() for obj in overview["object_totals"].keys()]
queues = agent_util.json_loads(execute_query(config, "queues"))
for entry in queues:
resource_name = entry["vhost"] + ":" + entry["name"]
queue_opts.append(
{
"resource": resource_name,
"queue": entry["name"],
"vhost": entry["vhost"],
}
)
nodes = agent_util.json_loads(execute_query(config, "nodes"))
node_opts = [node["name"] for node in nodes]
except:
self.log.exception("error querying rabbitmq management API")
status = agent_util.MISCONFIGURED
msg = "Unable to access RabbitMQ metrics. Please ensure that the management plugin is installed and that your credentials are valid in the agent config file."
metadata = {
"object_totals": {
"label": "# of Objects",
"options": objects,
"status": status,
"error_message": msg,
},
"queue.messages": {
"label": "Queue Length",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"error_message": msg,
},
"queue.memory": {
"label": "Queue Memory Usage (kB)",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "kB",
"error_message": msg,
},
"queue.messages_ready": {
"label": "Queue number of messages ready for delivery",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.messages_unacknowledged": {
"label": "Queue number of unacknowledged messages",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.message_stats.publish": {
"label": "Queue messages published recently",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.message_stats.publish_details.rate": {
"label": "Queue message publishing rate",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count/sec",
"error_message": msg,
},
"queue.message_stats.deliver_get": {
"label": "Queue messages delivered recently",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.message_stats.deliver_get_details.rate": {
"label": "Queue message delivery rate",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.message_stats.redeliver": {
"label": "Queue message redelivered recently",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count",
"error_message": msg,
},
"queue.message_stats.redeliver_details.rate": {
"label": "Queue messages redeliver rate",
"options": queue_opts,
"options_schema": queues_schema,
"status": status,
"unit": "count/sec",
"error_message": msg,
},
"overview.queue_totals.messages_ready": {
"label": "Cluster number of messages ready for delivery",
"options": None,
"status": status,
"error_message": msg,
"unit": "count",
},
"overview.queue_totals.messages_unacknowledged": {
"label": "Cluster number of unacknowledged messages",
"options": None,
"status": status,
"error_message": msg,
"unit": "count",
},
"overview.message_stats.publish": {
"label": "Cluster messages published recently",
"options": None,
"status": status,
"error_message": msg,
"unit": "count",
},
"overview.message_stats.publish_details.rate": {
"label": "Cluster messages publish rate",
"options": None,
"status": status,
"error_message": msg,
"unit": "msgs/sec",
},
"overview.message_stats.deliver_get": {
"label": "Cluster messages delivered to consumers recently",
"options": None,
"status": status,
"error_message": msg,
"unit": "count",
},
"overview.message_stats.deliver_details.rate": {
"label": "Cluster message delivery rate",
"options": None,
"status": status,
"error_message": msg,
"unit": "msgs/sec",
},
"overview.message_stats.redeliver": {
"label": "Cluster messages redelivered to consumers recently",
"options": None,
"status": status,
"error_message": msg,
"unit": "count",
},
"overview.message_stats.redeliver_details.rate": {
"label": "Cluster message redelivery rate",
"options": None,
"status": status,
"error_message": msg,
"unit": "msgs/sec",
},
"nodes.mem_used": {
"label": "Node total amount of memory used",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs",
},
"nodes.mem_used_details.rate": {
"label": "Node memory used rate",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs/sec",
},
"nodes.io_read_count": {
"label": "Node total number of read operations by the persister",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count",
},
"nodes.io_read_count_details.rate": {
"label": "Node rate of read count",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count/sec",
},
"nodes.io_read_bytes": {
"label": "Node total number of bytes read from disk by the persister",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs",
},
"nodes.io_read_bytes_details.rate": {
"label": "Node rate of read kBs",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs/sec",
},
"nodes.io_write_bytes": {
"label": "Node total number of bytes written to disk by the persister",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs",
},
"nodes.io_write_bytes_details.rate": {
"label": "Node rate of written bytes",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "kBs/sec",
},
"nodes.fd_used": {
"label": "Node file descriptors used",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count",
},
"nodes.fd_used_details.rate": {
"label": "Node file descriptors used rate",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count/sec",
},
"nodes.sockets_total": {
"label": "Node sockets available",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count",
},
"nodes.sockets_used": {
"label": "Node sockets used",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count",
},
"nodes.socktets_used_details.rate": {
"label": "Node sockets used rate",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count/sec",
},
"nodes.proc_used": {
"label": "Node number of Erlang processes in use",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count",
},
"nodes.proc_used_details.rate": {
"label": "Node processor used rate",
"options": node_opts,
"status": status,
"error_message": msg,
"unit": "count/sec",
},
}
return metadata
@classmethod
def get_metadata_docker(self, container, config):
if "management_interface_host" not in config:
try:
ip = agent_util.get_container_ip(container)
config["management_interface_host"] = ip
except Exception as e:
self.log.exception(e)
config["from_docker"] = True
return self.get_metadata(config)
def check(self, textkey, option, config):
if config:
new_config = self.DEFAULTS.copy()
new_config.update(config)
config = new_config
else:
config = self.DEFAULTS
if "." in textkey:
command, key = textkey.split(".", 1)
if command.startswith("queue"):
command += "s"
try:
json_data = execute_query(config, command, option)
except Exception:
self.log.exception(
"Unable to get %s from %s"
% (command, config.get("management_interface_host"))
)
return None
data = agent_util.json_loads(json_data)
# If no object (queue, exchange, host, etc.) is specified, report an aggregate
try:
if isinstance(data, list):
if command.startswith("nodes"):
# Node calls return all nodes information,
# need to filter them by option
found_data = None
for entry in data:
if entry.get("name") == option:
# Found our node
found_data = entry
break
if not found_data:
self.log.info(
"Unable to find information for node %s" % option
)
return None
else:
res = self._parse_dict_tree(key, found_data)
elif command.startswith("queues"):
# Queue calls are organized by vhost and queue name.
# Need to filter them
found_data = None
vhost, queue_name = option.split(":")
for entry in data:
if (
entry.get("vhost") == vhost
and entry.get("name") == queue_name
):
found_data = entry
break
if not found_data:
self.log.info(
"Unable to find information for vhost %s queue %s"
% (vhost, queue_name)
)
return None
else:
res = self._parse_dict_tree(key, found_data)
else:
res = sum([obj[key] for obj in data])
else:
if "." not in key:
res = data[key]
if not bool(res):
res = None
else:
res = self._parse_dict_tree(key, data)
except Exception:
self.log.exception("Error gathering data")
return None
if key == BYTES_TO_KB_KEYS:
res /= 1000.0
elif textkey == "object_totals":
json_data = execute_query(config, "overview")
res = agent_util.json_loads(json_data)["object_totals"][option.lower()]
if textkey.endswith("rate") and res < 0:
# Rates that go below 0 we will turn to 0.
res = 0
return res
def check_docker(self, container, textkey, option, config):
if "management_interface_host" not in config:
try:
ip = agent_util.get_container_ip(container)
config["management_interface_host"] = ip
except Exception as e:
self.log.exception(e)
config["from_docker"] = True
return self.check(textkey, option, config)
def _parse_dict_tree(self, key, data):
"""
Using the key as the nodes, parse the data dictionary to extract the
information.
E.g metric_used_details.rate looks for data['metric_used_details']['rate']
"""
entries = key.split(".")
value = data
for entry in entries:
value = value.get(entry)
if not bool(value):
value = None
break
return value
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