適用於 Python 的 Azure 監視器程式庫Azure Monitoring libraries for python

概觀Overview

監視會提供資料，以確保應用程式持續運作並以健全的狀態執行。Monitoring provides data to ensure that your application stays up and running in a healthy state. 它也可協助您預防潛在問題，或是針對過去所發生的問題進行疑難排解。It also helps you to stave off potential problems or troubleshoot past ones. 除此之外，您還可以使用監視資料來取得應用程式的深入解析。In addition, you can use monitoring data to gain deep insights about your application. 這些知識可協助您提升應用程式效能或維護性，或是將原本需要手動介入的動作自動化。That knowledge can help you to improve application performance or maintainability, or automate actions that would otherwise require manual intervention.

在這裡深入了解 Azure 監視器。Learn more about Azure Monitor here.

安裝Installation

pip install azure-mgmt-monitor

範例 - 計量Example - Metrics

這個範例會取得 Azure 上的資源計量 (VM 等)。This sample obtains the metrics of a resource on Azure (VMs, etc.). 這個範例需要至少 0.4.0 版的 Python 套件。This sample requires version 0.4.0 of the Python package at least.

這裡提供篩選條件的可用關鍵字完整清單。A complete list of available keywords for filters is available here.

這裡提供每個資源類型支援的計量。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

範例 - 警示Example - Alerts

這個範例示範如何在建立警示以確保正確監視所有資源時，自動在您的資源上設定警示。This example shows how to automatically set up alerts on your resources when they are created to ensure that all resources are monitored correctly.

在 VM 上建立資料來源，以警示 CPU 使用量：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'
)

建立 VM 在最後 5 分鐘的平均 CPU 使用率高於 90% (使用上述的資料來源) 時會加以觸發的臨界值條件：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'
)

建立電子郵件動作：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'
    ]
)

建立警示：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
        ]
    }
)

探索管理 APIExplore the Management APIs