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weblogic12c.py	18.75 KB	-rw-r--r--

Code Editor : rabbitmq.py

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.
        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

${this.title}

Code Editor : rabbitmq.py