
Azure Monitor Query SDK
FreeExecute Kusto queries on Azure resources.
Free · Opens the source repo
What Azure Monitor Query SDK does
The Azure Monitor Query SDK for Java provides developers with a client library to execute Kusto queries against Azure Log Analytics workspaces and to query metrics from Azure resources. This SDK allows for both synchronous and asynchronous operations, enabling users to efficiently retrieve log and metric data from their Azure environments. Developers can leverage this SDK to integrate Azure monitoring capabilities directly into their Java applications, facilitating better observability and performance tracking.
To use the SDK, you need to have an Azure Log Analytics workspace for log queries and an Azure resource for metrics queries. The SDK requires appropriate permissions through a TokenCredential, ensuring secure access to the Azure resources. The setup process is straightforward, with dependencies easily added to your Java project through Maven.
The SDK supports various query operations, including basic queries, resource-specific queries, and batch queries. Users can also map query results to custom Java models, allowing for enhanced data manipulation and presentation. This flexibility makes it suitable for a range of applications, from simple logging to complex monitoring solutions.
However, it's important to note that this package is deprecated and has been replaced by two separate packages: azure-monitor-query-logs for log queries and azure-monitor-query-metrics for metrics queries. Users are encouraged to migrate to these newer packages for continued support and updates.
When to use it
Use this SDK when you need to integrate Azure Monitor queries into your Java applications for log and metric analysis.
When not to use it
Avoid using this SDK as it is deprecated; consider migrating to the newer packages for better support.
What you can build with it
Integrating Monitoring into Java Applications
Use the SDK to embed Azure Monitor capabilities directly into your Java applications, allowing for real-time monitoring and logging.
Batch Processing of Logs
Leverage the batch query functionality to efficiently retrieve and process multiple log queries in a single request.
Custom Data Models for Query Results
Map query results to custom Java models for better data handling and presentation in your application.
How to install Azure Monitor Query SDK
View source1. Install with the skills CLI
npx skills add sickn33/agentic-awesome-skills/azure-monitor-query-java --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by sickn33Azure Monitor Query SDK for Java
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.
Installation
<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>
Prerequisites
- Log Analytics workspace (for logs queries)
- Azure resource (for metrics queries)
- TokenCredential with appropriate permissions
Environment Variables
LOG_ANALYTICS_WORKSPACE_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
AZURE_RESOURCE_ID=/subscriptions/{sub}/resourceGroups/{rg}/providers/{provider}/{resource}
Client Creation
LogsQueryClient (Sync)
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();
LogsQueryAsyncClient
import com.azure.monitor.query.LogsQueryAsyncClient;
LogsQueryAsyncClient logsAsyncClient = new LogsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildAsyncClient();
MetricsQueryClient (Sync)
import com.azure.monitor.query.MetricsQueryClient;
import com.azure.monitor.query.MetricsQueryClientBuilder;
MetricsQueryClient metricsClient = new MetricsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
MetricsQueryAsyncClient
import com.azure.monitor.query.MetricsQueryAsyncClient;
MetricsQueryAsyncClient metricsAsyncClient = new MetricsQueryClientBuilder()
.credential(new DefaultAzureCredentialBuilder().build())
.buildAsyncClient();
Sovereign Cloud Configuration
// 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();
Key Concepts
| 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 |
Logs Query Operations
Basic 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_"));
}
Query by Resource ID
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"));
}
Map Results to Custom Model
// 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());
}
Batch Query
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());
}
Query with Options
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();
Query Multiple Workspaces
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
);
Metrics Query Operations
Basic Metrics Query
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());
}
}
}
Metrics with Aggregations
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();
Query Multiple Resources (MetricsClient)
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()));
}
}
Response Structure
Logs Response Hierarchy
LogsQueryResult
├── statistics (BinaryData)
├── visualization (BinaryData)
├── error
└── tables (List<LogsTable>)
├── name
├── columns (List<LogsTableColumn>)
│ ├── name
│ └── type
└── rows (List<LogsTableRow>)
├── rowIndex
└── rowCells (List<LogsTableCell>)
Metrics Response Hierarchy
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
Error Handling
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());
}
Best Practices
- Use batch queries — Combine multiple queries into a single request
- Set appropriate timeouts — Long queries may need extended server timeout
- Limit result size — Use
toportakein Kusto queries - Use projections — Select only needed columns with
project - Check query status — Handle PARTIAL_FAILURE results gracefully
- Cache results — Metrics don't change frequently; cache when appropriate
- Migrate to new packages — Plan migration to
azure-monitor-query-logsandazure-monitor-query-metrics
Reference Links
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Frequently asked questions about Azure Monitor Query SDK
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