.github/plugins/azure-sdk-java/skills/azure-monitor-query-java/SKILL.md
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources. Triggers: "LogsQueryClient java", "MetricsQueryClient java", "kusto query java", "log analytics java", "azure monitor query java". Note: This package is deprecated. Migrate to azure-monitor-query-logs and azure-monitor-query-metrics.
npx skillsauth add microsoft/skills azure-monitor-query-javaInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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DEPRECATION NOTICE: This package is deprecated in favor of:
azure-monitor-query-logs— For Log Analytics queriesazure-monitor-query-metrics— For metrics queriesSee migration guides: Logs Migration | Metrics Migration
Client library for querying Azure Monitor Logs and Metrics.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-monitor-query</artifactId>
<version>1.5.9</version>
</dependency>
Or use Azure SDK BOM:
<dependencyManagement>
<dependencies>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-sdk-bom</artifactId>
<version>{bom_version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-monitor-query</artifactId>
</dependency>
</dependencies>
LOG_ANALYTICS_WORKSPACE_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
AZURE_RESOURCE_ID=/subscriptions/{sub}/resourceGroups/{rg}/providers/{provider}/{resource}
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.monitor.query.LogsQueryClient;
import com.azure.monitor.query.LogsQueryClientBuilder;
LogsQueryClient logsClient = new LogsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
import com.azure.monitor.query.LogsQueryAsyncClient;
LogsQueryAsyncClient logsAsyncClient = new LogsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildAsyncClient();
import com.azure.monitor.query.MetricsQueryClient;
import com.azure.monitor.query.MetricsQueryClientBuilder;
MetricsQueryClient metricsClient = new MetricsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
import com.azure.monitor.query.MetricsQueryAsyncClient;
MetricsQueryAsyncClient metricsAsyncClient = new MetricsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildAsyncClient();
// Azure China Cloud - Logs
LogsQueryClient logsClient = new LogsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.endpoint("https://api.loganalytics.azure.cn/v1")
.buildClient();
// Azure China Cloud - Metrics
MetricsQueryClient metricsClient = new MetricsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.endpoint("https://management.chinacloudapi.cn")
.buildClient();
| Concept | Description | |---------|-------------| | Logs | Log and performance data from Azure resources via Kusto Query Language | | Metrics | Numeric time-series data collected at regular intervals | | Workspace ID | Log Analytics workspace identifier | | Resource ID | Azure resource URI for metrics queries | | QueryTimeInterval | Time range for the query |
import com.azure.monitor.query.models.LogsQueryResult;
import com.azure.monitor.query.models.LogsTableRow;
import com.azure.monitor.query.models.QueryTimeInterval;
import java.time.Duration;
LogsQueryResult result = logsClient.queryWorkspace(
"{workspace-id}",
"AzureActivity | summarize count() by ResourceGroup | top 10 by count_",
new QueryTimeInterval(Duration.ofDays(7))
);
for (LogsTableRow row : result.getTable().getRows()) {
System.out.println(row.getColumnValue("ResourceGroup") + ": " + row.getColumnValue("count_"));
}
LogsQueryResult result = logsClient.queryResource(
"{resource-id}",
"AzureMetrics | where TimeGenerated > ago(1h)",
new QueryTimeInterval(Duration.ofDays(1))
);
for (LogsTableRow row : result.getTable().getRows()) {
System.out.println(row.getColumnValue("MetricName") + " " + row.getColumnValue("Average"));
}
// Define model class
public class ActivityLog {
private String resourceGroup;
private String operationName;
public String getResourceGroup() { return resourceGroup; }
public String getOperationName() { return operationName; }
}
// Query with model mapping
List<ActivityLog> logs = logsClient.queryWorkspace(
"{workspace-id}",
"AzureActivity | project ResourceGroup, OperationName | take 100",
new QueryTimeInterval(Duration.ofDays(2)),
ActivityLog.class
);
for (ActivityLog log : logs) {
System.out.println(log.getOperationName() + " - " + log.getResourceGroup());
}
import com.azure.monitor.query.models.LogsBatchQuery;
import com.azure.monitor.query.models.LogsBatchQueryResult;
import com.azure.monitor.query.models.LogsBatchQueryResultCollection;
import com.azure.core.util.Context;
LogsBatchQuery batchQuery = new LogsBatchQuery();
String q1 = batchQuery.addWorkspaceQuery("{workspace-id}", "AzureActivity | count", new QueryTimeInterval(Duration.ofDays(1)));
String q2 = batchQuery.addWorkspaceQuery("{workspace-id}", "Heartbeat | count", new QueryTimeInterval(Duration.ofDays(1)));
String q3 = batchQuery.addWorkspaceQuery("{workspace-id}", "Perf | count", new QueryTimeInterval(Duration.ofDays(1)));
LogsBatchQueryResultCollection results = logsClient
.queryBatchWithResponse(batchQuery, Context.NONE)
.getValue();
LogsBatchQueryResult result1 = results.getResult(q1);
LogsBatchQueryResult result2 = results.getResult(q2);
LogsBatchQueryResult result3 = results.getResult(q3);
// Check for failures
if (result3.getQueryResultStatus() == LogsQueryResultStatus.FAILURE) {
System.err.println("Query failed: " + result3.getError().getMessage());
}
import com.azure.monitor.query.models.LogsQueryOptions;
import com.azure.core.http.rest.Response;
LogsQueryOptions options = new LogsQueryOptions()
.setServerTimeout(Duration.ofMinutes(10))
.setIncludeStatistics(true)
.setIncludeVisualization(true);
Response<LogsQueryResult> response = logsClient.queryWorkspaceWithResponse(
"{workspace-id}",
"AzureActivity | summarize count() by bin(TimeGenerated, 1h)",
new QueryTimeInterval(Duration.ofDays(7)),
options,
Context.NONE
);
LogsQueryResult result = response.getValue();
// Access statistics
BinaryData statistics = result.getStatistics();
// Access visualization data
BinaryData visualization = result.getVisualization();
import java.util.Arrays;
LogsQueryOptions options = new LogsQueryOptions()
.setAdditionalWorkspaces(Arrays.asList("{workspace-id-2}", "{workspace-id-3}"));
Response<LogsQueryResult> response = logsClient.queryWorkspaceWithResponse(
"{workspace-id-1}",
"AzureActivity | summarize count() by TenantId",
new QueryTimeInterval(Duration.ofDays(1)),
options,
Context.NONE
);
import com.azure.monitor.query.models.MetricsQueryResult;
import com.azure.monitor.query.models.MetricResult;
import com.azure.monitor.query.models.TimeSeriesElement;
import com.azure.monitor.query.models.MetricValue;
import java.util.Arrays;
MetricsQueryResult result = metricsClient.queryResource(
"{resource-uri}",
Arrays.asList("SuccessfulCalls", "TotalCalls")
);
for (MetricResult metric : result.getMetrics()) {
System.out.println("Metric: " + metric.getMetricName());
for (TimeSeriesElement ts : metric.getTimeSeries()) {
System.out.println(" Dimensions: " + ts.getMetadata());
for (MetricValue value : ts.getValues()) {
System.out.println(" " + value.getTimeStamp() + ": " + value.getTotal());
}
}
}
import com.azure.monitor.query.models.MetricsQueryOptions;
import com.azure.monitor.query.models.AggregationType;
Response<MetricsQueryResult> response = metricsClient.queryResourceWithResponse(
"{resource-id}",
Arrays.asList("SuccessfulCalls", "TotalCalls"),
new MetricsQueryOptions()
.setGranularity(Duration.ofHours(1))
.setAggregations(Arrays.asList(AggregationType.AVERAGE, AggregationType.COUNT)),
Context.NONE
);
MetricsQueryResult result = response.getValue();
import com.azure.monitor.query.MetricsClient;
import com.azure.monitor.query.MetricsClientBuilder;
import com.azure.monitor.query.models.MetricsQueryResourcesResult;
MetricsClient metricsClient = new MetricsClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.endpoint("{endpoint}")
.buildClient();
MetricsQueryResourcesResult result = metricsClient.queryResources(
Arrays.asList("{resourceId1}", "{resourceId2}"),
Arrays.asList("{metric1}", "{metric2}"),
"{metricNamespace}"
);
for (MetricsQueryResult queryResult : result.getMetricsQueryResults()) {
for (MetricResult metric : queryResult.getMetrics()) {
System.out.println(metric.getMetricName());
metric.getTimeSeries().stream()
.flatMap(ts -> ts.getValues().stream())
.forEach(mv -> System.out.println(
mv.getTimeStamp() + " Count=" + mv.getCount() + " Avg=" + mv.getAverage()));
}
}
LogsQueryResult
├── statistics (BinaryData)
├── visualization (BinaryData)
├── error
└── tables (List<LogsTable>)
├── name
├── columns (List<LogsTableColumn>)
│ ├── name
│ └── type
└── rows (List<LogsTableRow>)
├── rowIndex
└── rowCells (List<LogsTableCell>)
MetricsQueryResult
├── granularity
├── timeInterval
├── namespace
├── resourceRegion
└── metrics (List<MetricResult>)
├── id, name, type, unit
└── timeSeries (List<TimeSeriesElement>)
├── metadata (dimensions)
└── values (List<MetricValue>)
├── timeStamp
├── count, average, total
├── maximum, minimum
import com.azure.core.exception.HttpResponseException;
import com.azure.monitor.query.models.LogsQueryResultStatus;
try {
LogsQueryResult result = logsClient.queryWorkspace(workspaceId, query, timeInterval);
// Check partial failure
if (result.getStatus() == LogsQueryResultStatus.PARTIAL_FAILURE) {
System.err.println("Partial failure: " + result.getError().getMessage());
}
} catch (HttpResponseException e) {
System.err.println("Query failed: " + e.getMessage());
System.err.println("Status: " + e.getResponse().getStatusCode());
}
top or take in Kusto queriesprojectazure-monitor-query-logs and azure-monitor-query-metrics| Resource | URL | |----------|-----| | Maven Package | https://central.sonatype.com/artifact/com.azure/azure-monitor-query | | GitHub | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/monitor/azure-monitor-query | | API Reference | https://learn.microsoft.com/java/api/com.azure.monitor.query | | Kusto Query Language | https://learn.microsoft.com/azure/data-explorer/kusto/query/ | | Log Analytics Limits | https://learn.microsoft.com/azure/azure-monitor/service-limits#la-query-api | | Troubleshooting | https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/monitor/azure-monitor-query/TROUBLESHOOTING.md |
tools
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
development
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
testing
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
testing
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".