Python용 Azure 모니터링 라이브러리Azure Monitoring libraries for python

아티클
07/03/2019

개요Overview

모니터링은 애플리케이션을 유지하고 정상 상태에서 실행할 수 있는 데이터를 제공합니다.Monitoring provides data to ensure that your application stays up and running in a healthy state. 또한 잠재적 문제를 방지하거나 지난 문제를 해결할 수 있습니다.It also helps you to stave off potential problems or troubleshoot past ones. 또한 애플리케이션에 대해 깊이 이해하는 데 모니터링 데이터를 사용할 수 있습니다.In addition, you can use monitoring data to gain deep insights about your application. 이러한 정보를 통해 애플리케이션 성능이나 유지 관리를 개선하거나 그렇지 않으면 수동 개입이 필요한 작업을 자동화하는 데 도움이 될 수 있습니다.That knowledge can help you to improve application performance or maintainability, or automate actions that would otherwise require manual intervention.

Azure Monitor에 대해 여기서 자세히 알아보세요.Learn more about Azure Monitor here.

설치Installation

pip install azure-mgmt-monitor

예 - 메트릭Example - Metrics

이 샘플에서는 Azure에서 리소스(VM 등)의 메트릭을 가져옵니다.This sample obtains the metrics of a resource on Azure (VMs, etc.). 이 샘플은 적어도 0.4.0 버전의 Python 패키지가 필요합니다.This sample requires version 0.4.0 of the Python package at least.

필터에 사용할 수 있는 키워드의 전체 목록은 여기에 있습니다.A complete list of available keywords for filters is available here.

리소스 종류별로 지원되는 메트릭은 여기에 있습니다.Supported metrics per resource type is available here.

import datetime
from azure.mgmt.monitor import MonitorManagementClient

# Get the ARM id of your resource. You might chose to do a "get"
# using the according management or to build the URL directly
# Example for a ARM VM
resource_id = (
    "subscriptions/{}/"
    "resourceGroups/{}/"
    "providers/Microsoft.Compute/virtualMachines/{}"
).format(subscription_id, resource_group_name, vm_name)

# create client
client = MonitorManagementClient(
    credentials,
    subscription_id
)

# You can get the available metrics of this specific resource
for metric in client.metric_definitions.list(resource_id):
    # azure.monitor.models.MetricDefinition
    print("{}: id={}, unit={}".format(
        metric.name.localized_value,
        metric.name.value,
        metric.unit
    ))

# Example of result for a VM:
# Percentage CPU: id=Percentage CPU, unit=Unit.percent
# Network In: id=Network In, unit=Unit.bytes
# Network Out: id=Network Out, unit=Unit.bytes
# Disk Read Bytes: id=Disk Read Bytes, unit=Unit.bytes
# Disk Write Bytes: id=Disk Write Bytes, unit=Unit.bytes
# Disk Read Operations/Sec: id=Disk Read Operations/Sec, unit=Unit.count_per_second
# Disk Write Operations/Sec: id=Disk Write Operations/Sec, unit=Unit.count_per_second

# Get CPU total of yesterday for this VM, by hour

today = datetime.datetime.now().date()
yesterday = today - datetime.timedelta(days=1)

metrics_data = client.metrics.list(
    resource_id,
    timespan="{}/{}".format(yesterday, today),
    interval='PT1H',
    metricnames='Percentage CPU',
    aggregation='Total'
)

for item in metrics_data.value:
    # azure.mgmt.monitor.models.Metric
    print("{} ({})".format(item.name.localized_value, item.unit.name))
    for timeserie in item.timeseries:
        for data in timeserie.data:
            # azure.mgmt.monitor.models.MetricData
            print("{}: {}".format(data.time_stamp, data.total))

# Example of result:
# Percentage CPU (percent)
# 2016-11-16 00:00:00+00:00: 72.0
# 2016-11-16 01:00:00+00:00: 90.59
# 2016-11-16 02:00:00+00:00: 60.58
# 2016-11-16 03:00:00+00:00: 65.78
# 2016-11-16 04:00:00+00:00: 43.96
# 2016-11-16 05:00:00+00:00: 43.96
# 2016-11-16 06:00:00+00:00: 114.9
# 2016-11-16 07:00:00+00:00: 45.4

예 - 경고Example - Alerts

이 예제에서는 모든 리소스가 제대로 모니터링되는지 확인하기 위해 리소스를 만들 때 리소스에 대한 경고를 자동으로 설정하는 방법을 보여 줍니다.This example shows how to automatically set up alerts on your resources when they are created to ensure that all resources are monitored correctly.

VM에 데이터 원본을 만들어 CPU 사용량을 경고합니다.Create a data source on a VM to alert on CPU usage:

from azure.mgmt.monitor import MonitorMgmtClient
from azure.mgmt.monitor.models import RuleMetricDataSource

resource_id = (
    "subscriptions/{}/"
    "resourceGroups/MonitorTestsDoNotDelete/"
    "providers/Microsoft.Compute/virtualMachines/MonitorTest"
).format(self.settings.SUBSCRIPTION_ID)

# create client
client = MonitorMgmtClient(
    credentials,
    subscription_id
)

# I need a subclass of "RuleDataSource"
data_source = RuleMetricDataSource(
    resource_uri = resource_id,
    metric_name = 'Percentage CPU'
)

지난 5분 동안 VM의 평균 CPU 사용량이 90%를 초과하면(이전 데이터 원본 사용) 트리거하는 임계값 조건을 만듭니다.Create a threshold condition that triggers when the average CPU usage of a VM for the last 5 minutes is above 90% (using the preceding data source):

from azure.mgmt.monitor.models import ThresholdRuleCondition

# I need a subclasses of "RuleCondition"
rule_condition = ThresholdRuleCondition(
    data_source = data_source,
    operator = 'GreaterThanOrEqual',
    threshold = 90,
    window_size = 'PT5M',
    time_aggregation = 'Average'
)

전자 메일 작업 만들기:Create an email action:

from azure.mgmt.monitor.models import RuleEmailAction

# I need a subclass of "RuleAction"
rule_action = RuleEmailAction(
    send_to_service_owners = True,
    custom_emails = [
        'monitoringemail@microsoft.com'
    ]
)

경고 만들기:Create the alert:

rule_name = 'MyPyTestAlertRule'
my_alert = client.alert_rules.create_or_update(
    group_name,
    rule_name,
    {
        'location': 'westus',
        'alert_rule_resource_name': rule_name,
        'description': 'Testing Alert rule creation',
        'is_enabled': True,
        'condition': rule_condition,
        'actions': [
            rule_action
        ]
    }
)

관리 API 탐색Explore the Management APIs

Python용 Azure 모니터링 라이브러리Azure Monitoring libraries for python

개요Overview

설치Installation

예 - 메트릭Example - Metrics

예 - 경고Example - Alerts

추가 리소스