Azure Monitor Query Py Agent Skill

pip install azure-monitor-query

# Log Analytics
AZURE_LOG_ANALYTICS_WORKSPACE_ID=<workspace-id>  # Required for log queries

# Metrics
AZURE_METRICS_RESOURCE_URI=/subscriptions/<sub>/resourceGroups/<rg>/providers/<provider>/<type>/<name>  # Required for metric queries
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

from azure.identity import DefaultAzureCredential, ManagedIdentityCredential

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()

from azure.monitor.query import LogsQueryClient
from datetime import timedelta

query = """
AppRequests
| where TimeGenerated > ago(1h)
| summarize count() by bin(TimeGenerated, 5m), ResultCode
| order by TimeGenerated desc
"""

with LogsQueryClient(credential) as client:
    response = client.query_workspace(
        workspace_id=os.environ["AZURE_LOG_ANALYTICS_WORKSPACE_ID"],
        query=query,
        timespan=timedelta(hours=1)
    )

    for table in response.tables:
        for row in table.rows:
            print(row)

from datetime import datetime, timezone

response = client.query_workspace(
    workspace_id=workspace_id,
    query="AppRequests | take 10",
    timespan=(
        datetime(2024, 1, 1, tzinfo=timezone.utc),
        datetime(2024, 1, 2, tzinfo=timezone.utc)
    )
)

import pandas as pd

response = client.query_workspace(workspace_id, query, timespan=timedelta(hours=1))

if response.tables:
    table = response.tables[0]
    df = pd.DataFrame(data=table.rows, columns=[col.name for col in table.columns])
    print(df.head())

from azure.monitor.query import LogsBatchQuery

queries = [
    LogsBatchQuery(workspace_id=workspace_id, query="AppRequests | take 5", timespan=timedelta(hours=1)),
    LogsBatchQuery(workspace_id=workspace_id, query="AppExceptions | take 5", timespan=timedelta(hours=1))
]

responses = client.query_batch(queries)

for response in responses:
    if response.tables:
        print(f"Rows: {len(response.tables[0].rows)}")

from azure.monitor.query import LogsQueryStatus

response = client.query_workspace(workspace_id, query, timespan=timedelta(hours=24))

if response.status == LogsQueryStatus.PARTIAL:
    print(f"Partial results: {response.partial_error}")
elif response.status == LogsQueryStatus.FAILURE:
    print(f"Query failed: {response.partial_error}")

from azure.monitor.query import MetricsQueryClient
from datetime import timedelta

with MetricsQueryClient(credential) as metrics_client:
    response = metrics_client.query_resource(
        resource_uri=os.environ["AZURE_METRICS_RESOURCE_URI"],
        metric_names=["Percentage CPU", "Network In Total"],
        timespan=timedelta(hours=1),
        granularity=timedelta(minutes=5)
    )

    for metric in response.metrics:
        print(f"{metric.name}:")
        for time_series in metric.timeseries:
            for data in time_series.data:
                print(f"  {data.timestamp}: {data.average}")

from azure.monitor.query import MetricAggregationType

response = metrics_client.query_resource(
    resource_uri=resource_uri,
    metric_names=["Requests"],
    timespan=timedelta(hours=1),
    aggregations=[
        MetricAggregationType.AVERAGE,
        MetricAggregationType.MAXIMUM,
        MetricAggregationType.MINIMUM,
        MetricAggregationType.COUNT
    ]
)

response = metrics_client.query_resource(
    resource_uri=resource_uri,
    metric_names=["Requests"],
    timespan=timedelta(hours=1),
    filter="ApiName eq 'GetBlob'"
)

definitions = metrics_client.list_metric_definitions(resource_uri)
for definition in definitions:
    print(f"{definition.name}: {definition.unit}")

namespaces = metrics_client.list_metric_namespaces(resource_uri)
for ns in namespaces:
    print(ns.fully_qualified_namespace)

from azure.monitor.query.aio import LogsQueryClient, MetricsQueryClient
from azure.identity.aio import DefaultAzureCredential

async def query_logs():
    async with DefaultAzureCredential() as credential:
        async with LogsQueryClient(credential) as client:
            response = await client.query_workspace(
                workspace_id=workspace_id,
                query="AppRequests | take 10",
                timespan=timedelta(hours=1)
            )
            return response

// Requests by status code
AppRequests
| summarize count() by ResultCode
| order by count_ desc

// Exceptions over time
AppExceptions
| summarize count() by bin(TimeGenerated, 1h)

// Slow requests
AppRequests
| where DurationMs > 1000
| project TimeGenerated, Name, DurationMs
| order by DurationMs desc

// Top errors
AppExceptions
| summarize count() by ExceptionType
| top 10 by count_