Python CloudWatchConnection.list_metrics方法代码示例

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]
 def test_get_metric_statistics(self):
     c = CloudWatchConnection()
     m = c.list_metrics()[0]
     end = datetime.datetime.now()
     start = end - datetime.timedelta(hours=24*14)
     c.get_metric_statistics(
         3600*24, start, end, m.name, m.namespace, ['Average', 'Sum'])

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]
def get_cloudwatch_top_metrics():
    conn = CloudWatchConnection()

    metrics_names = []
    next_token = None
    while True:
        res = conn.list_metrics(next_token=next_token,
                                dimensions=settings.CLOUDWATCH_DIMENSIONS,
                                namespace=settings.CLOUDWATCH_NAMESPACE)
        metrics_names.extend([m.name for m in res])
        next_token = res.next_token
        if next_token is None:
            break

    # List of tuples like [(metric_name, count), ...]
    metrics = []

    for metric_name in metrics_names:
        res = conn.get_metric_statistics(int(START_DELTA_AGO.total_seconds()),
                                         datetime.datetime.now() - START_DELTA_AGO,
                                         datetime.datetime.now(),
                                         metric_name,
                                         settings.CLOUDWATCH_NAMESPACE,
                                         'Sum',
                                         settings.CLOUDWATCH_DIMENSIONS,
                                         'Count')

        if not res:
            # Some metrics will not have (or no longer have) results
            continue

        count = int(res[0]['Sum'])

        if count >= TOP_THRESHOLD_COUNT:
            metrics.append((metric_name, count))

    metrics.sort(key=lambda x: x[1], reverse=True)

    text = 'Responses sent\n----------------------\n'
    for metric in metrics:
        metric_name = 'TOTAL' if metric[0] == settings.CLOUDWATCH_TOTAL_SENT_METRIC_NAME else metric[0]
        if metric_name == settings.CLOUDWATCH_PROCESSING_TIME_METRIC_NAME:
            continue
        text += '%s %s\n' % (str(metric[1]).rjust(5), metric_name)

    return text

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]
class BotoWatchInterface(WatchInterface):
    conn = None
    saveclcdata = False

    def __init__(self, clc_host, access_id, secret_key, token):
        #boto.set_stream_logger('foo')
        path='/services/CloudWatch'
        port=8773
        if clc_host[len(clc_host)-13:] == 'amazonaws.com':
            clc_host = clc_host.replace('ec2', 'monitoring', 1)
            path = '/'
            reg = None
            port=443
        reg = RegionInfo(name='eucalyptus', endpoint=clc_host)
        if boto.__version__ < '2.6':
            self.conn = CloudWatchConnection(access_id, secret_key, region=reg,
                                  port=port, path=path,
                                  is_secure=True, security_token=token, debug=0)
        else:
            self.conn = CloudWatchConnection(access_id, secret_key, region=reg,
                                  port=port, path=path, validate_certs=False,
                                  is_secure=True, security_token=token, debug=0)
        self.conn.http_connection_kwargs['timeout'] = 30

    def __save_json__(self, obj, name):
        f = open(name, 'w')
        json.dump(obj, f, cls=BotoJsonWatchEncoder, indent=2)
        f.close()

    def get_metric_statistics(self, period, start_name, end_time, metric_name, namespace, statistics, dimensions, unit):
        obj = self.conn.get_metric_statistics(period, start_name, end_time, metric_name, namespace, statistics, dimensions, unit)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/CW_Statistics.json")
        return obj

    def list_metrics(self, next_token, dimensions, metric_name, namespace):
        obj = self.conn.list_metrics(next_token, dimensions, metric_name, namespace)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/CW_Metrics.json")
        return obj

    def put_metric_data(self, namespace, name, value, timestamp, unit, dimensions, statistics):
        return self.conn.put_metric_data(namespace, name, value, timestamp, unit, dimensions, statistics)

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]
class BotoWatchInterface(WatchInterface):
    conn = None
    saveclcdata = False

    def __init__(self, clc_host, access_id, secret_key, token):
        # boto.set_stream_logger('foo')
        path = "/services/CloudWatch"
        port = 8773
        if clc_host[len(clc_host) - 13 :] == "amazonaws.com":
            clc_host = clc_host.replace("ec2", "monitoring", 1)
            path = "/"
            reg = None
            port = 443
        reg = RegionInfo(name="eucalyptus", endpoint=clc_host)
        self.conn = CloudWatchConnection(
            access_id, secret_key, region=reg, port=port, path=path, is_secure=True, security_token=token, debug=0
        )
        self.conn.https_validate_certificates = False
        self.conn.http_connection_kwargs["timeout"] = 30

    def __save_json__(self, obj, name):
        f = open(name, "w")
        json.dump(obj, f, cls=BotoJsonWatchEncoder, indent=2)
        f.close()

    def get_metric_statistics(self, period, start_name, end_time, metric_name, namespace, statistics, dimensions, unit):
        obj = self.conn.get_metric_statistics(
            period, start_name, end_time, metric_name, namespace, statistics, dimensions, unit
        )
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/CW_Statistics.json")
        return obj

    def list_metrics(self, next_token=None, dimensions=None, metric_name=None, namespace=None):
        obj = self.conn.list_metrics(next_token, dimensions, metric_name, namespace)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/CW_Metrics.json")
        return obj

    def put_metric_data(self, namespace, name, value, timestamp, unit, dimensions, statistics):
        return self.conn.put_metric_data(namespace, name, value, timestamp, unit, dimensions, statistics)

    def describe_alarms(
        self,
        action_prefix=None,
        alarm_name_prefix=None,
        alarm_names=None,
        max_records=None,
        state_value=None,
        next_token=None,
    ):
        obj = self.conn.describe_alarms(
            action_prefix, alarm_name_prefix, alarm_names, max_records, state_value, next_token
        )
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/CW_Alarms.json")
        return obj

    def delete_alarms(self, alarm_names):
        return self.conn.delete_alarms(alarm_names)

    def enable_alarm_actions(self, alarm_names):
        return self.conn.enable_alarm_actions(alarm_names)

    def disable_alarm_actions(self, alarm_names):
        return self.conn.disable_alarm_actions(alarm_names)

    def put_metric_alarm(self, alarm):
        return self.conn.put_metric_alarm(alarm)

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]

#.........这里部分代码省略.........
		try:
			# only monitor if we are told to (this will break, if not set)
			monitoring = self.userdata['monitoring']
		except:
			monitoring = 'on'

		if monitoring in ['on', 'all']:
			# first get all we need
			[names, values, units, dimensions] = self.collect(monitoring)
			while len(names) > 0:
				names20 = names[:20]
				values20 = values[:20]
				units20 = units[:20]

				# we can't send all at once, only 20 at a time
				# first aggregated over all
				result = self.cloudwatch.put_metric_data(self.namespace,
								names20, value=values20, unit=units20)
				for dimension in dimensions:
					dimension = { dimension : dimensions[dimension] }
					result &= self.cloudwatch.put_metric_data(
								self.namespace, names20, value=values20,
								unit=units20, dimensions=dimension)

				del names[:20]
				del values[:20]
				del units[:20]
		else:
			print "we are not monitoring"

		return result
	
	def metrics(self):
		return self.cloudwatch.list_metrics()

	def _get_nr_wal_files(self):
		try:
			cursor = self.connection.cursor()

			sql = "select count(name) from (select pg_ls_dir('pg_xlog') as name) as xlogs where name != 'archive_status'"
			cursor.execute(sql)
			
			[size] = cursor.fetchone()
		finally:
			cursor.close()

		return size

	def _get_tables_size(self, connection):
		try:
			cursor = connection.cursor()

			sql = "select sum(pg_relation_size(relid)) from pg_stat_user_tables"
			cursor.execute(sql)
			
			[size] = cursor.fetchone()
		finally:
			cursor.close()

		return size

	def _get_indexes_size(self, connection):
		try:
			cursor = connection.cursor()

			sql = "select sum(pg_relation_size(indexrelid)) from pg_stat_user_indexes"

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]

#.........这里部分代码省略.........
		units.append('Count')

		#
		names.append('loading')
		values.append(items['loading'])
		units.append('Count')

		names.append('bgsave_in_progress')
		values.append(items['bgsave_in_progress'])
		units.append('Count')

		# clients
		names.append('connected_clients')
		values.append(items['connected_clients'])
		units.append('Count')

		names.append('blocked_clients')
		values.append(items['blocked_clients'])
		units.append('Count')

		# connection/command totals
		#names.append('total_connections_received')
		#values.append(items['total_connections_received'])
		#units.append('Count')

		#names.append('total_commands_processed')
		#values.append(items['total_commands_processed'])
		#units.append('Count')

		# client input/output
		names.append('client_biggest_input_buf')
		values.append(items['client_biggest_input_buf'])
		units.append('Bytes')

		names.append('client_longest_output_list')
		values.append(items['client_longest_output_list'])
		units.append('Bytes')

		# keys
		names.append('expired_keys')
		values.append(items['expired_keys'])
		units.append('Count')

		names.append('evicted_keys')
		values.append(items['evicted_keys'])
		units.append('Count')

		# last_save
		names.append('changes_since_last_save')
		values.append(items['changes_since_last_save'])
		units.append('Count')

		# keyspace
		#names.append('keyspace_misses')
		#values.append(items['keyspace_misses'])
		#units.append('Count')

		#names.append('keyspace_hits')
		#values.append(items['keyspace_hits'])
		#units.append('Count')

		return [names, values, units, dimensions]

	def put(self):
		result = False
		try:
			# only monitor if we are told to (this will break, if not set)
			monitoring = self.userdata['monitoring']
		except:
			monitoring = 'on'

		if monitoring in ['on', 'all']:
			# first get all we need
			[names, values, units, dimensions] = self.collect(monitoring)
			print [names, values, units, dimensions]
			while len(names) > 0:
				names20 = names[:20]
				values20 = values[:20]
				units20 = units[:20]

				# we can't send all at once, only 20 at a time
				# first aggregated over all
				result = self.cloudwatch.put_metric_data(self.namespace,
								names20, value=values20, unit=units20)
				for dimension in dimensions:
					dimension = { dimension : dimensions[dimension] }
					result &= self.cloudwatch.put_metric_data(
								self.namespace, names20, value=values20,
								unit=units20, dimensions=dimension)

				del names[:20]
				del values[:20]
				del units[:20]
		else:
			print "we are not monitoring"

		return result
	
	def metrics(self):
		return self.cloudwatch.list_metrics()

# 需要导入模块: from boto.ec2.cloudwatch import CloudWatchConnection [as 别名]
# 或者: from boto.ec2.cloudwatch.CloudWatchConnection import list_metrics [as 别名]

#.........这里部分代码省略.........
		values.append(items['used_memory_rss'])
		units.append('Bytes')

		names.append('mem_fragmentation_ratio')
		values.append(items['mem_fragmentation_ratio'])
		units.append('None')

		names.append('connected_slaves')
		values.append(items['connected_slaves'])
		units.append('Count')

		#
		names.append('loading')
		values.append(items['loading'])
		units.append('Count')

		names.append('bgsave_in_progress')
		values.append(items['bgsave_in_progress'])
		units.append('Count')

		# clients
		names.append('connected_clients')
		values.append(items['connected_clients'])
		units.append('Count')

		names.append('blocked_clients')
		values.append(items['blocked_clients'])
		units.append('Count')

		# connection/command totals
		names.append('total_connections_received')
		values.append(items['total_connections_received'])
		units.append('Count')

		names.append('total_commands_processed')
		values.append(items['total_commands_processed'])
		units.append('Count')

		# client input/output
		names.append('client_biggest_input_buf')
		values.append(items['client_biggest_input_buf'])
		units.append('Bytes')

		names.append('client_longest_output_list')
		values.append(items['client_longest_output_list'])
		units.append('Bytes')

		# keys
		names.append('expired_keys')
		values.append(items['expired_keys'])
		units.append('Count')

		names.append('evicted_keys')
		values.append(items['evicted_keys'])
		units.append('Count')

		# last_save
		names.append('changes_since_last_save')
		values.append(items['changes_since_last_save'])
		units.append('Count')

		# keyspace
		names.append('keyspace_misses')
		values.append(items['keyspace_misses'])
		units.append('Count')

		names.append('keyspace_hits')
		values.append(items['keyspace_hits'])
		units.append('Count')

		return [names, values, units, dimensions]

	def put(self):
		# first get all we need
		[names, values, units, dimensions] = self.collect()
		while len(names) > 0:
			names20 = names[:20]
			values20 = values[:20]
			units20 = units[:20]

			# we can't send all at once, only 20 at a time
			# first aggregated over all
			self.__log('put aggregated ReDiS metrics data', 'info')
			result = self.cloudwatch.put_metric_data(self.namespace,
									names20, value=values20, unit=units20)
			for dimension in dimensions:
				self.__log('put ReDiS metrics data for {0}'.format(dimensions[dimension]), 'info')
				dimension = { dimension : dimensions[dimension] }
				result &= self.cloudwatch.put_metric_data(self.namespace,
									names20, value=values20, unit=units20,
									dimensions=dimension)

			del names[:20]
			del values[:20]
			del units[:20]

		return result
	
	def metrics(self):
		return self.cloudwatch.list_metrics()