Azure Monitor Query Java V2

Azure Monitor Query SDK for Java

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/azure-monitor-query-java from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Azure Monitor Query SDK for Java > DEPRECATION NOTICE: This package is deprecated in favor of: > - azure-monitor-query-logs — For Log Analytics queries > - azure-monitor-query-metrics — For metrics queries > > See migration guides: Logs Migration | Metrics Migration Client library for querying Azure Monitor Logs and Metrics.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Prerequisites, Environment Variables, Client Creation, Key Concepts, Logs Query Operations, Metrics Query Operations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• This skill is applicable to execute the workflow or actions described in the overview.
• Use when the request clearly matches the imported source intent: Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. xml com.azure azure-monitor-query 1.5.9 Or use Azure SDK BOM: xml com.azure azure-sdk-bom {bom_version} pom import com.azure azure-monitor-query
2. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
3. Read the overview and provenance files before loading any copied upstream support files.
4. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
5. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
6. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
7. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.

Imported Workflow Notes

Imported: 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>

Imported: Prerequisites

• Log Analytics workspace (for logs queries)
• Azure resource (for metrics queries)
• TokenCredential with appropriate permissions

Examples

Example 1: Ask for the upstream workflow directly

Use @azure-monitor-query-java-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @azure-monitor-query-java-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @azure-monitor-query-java-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @azure-monitor-query-java-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Use batch queries — Combine multiple queries into a single request
• Set appropriate timeouts — Long queries may need extended server timeout
• Limit result size — Use top or take in 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-logs and azure-monitor-query-metrics

Imported Operating Notes

Imported: Best Practices

1. Use batch queries — Combine multiple queries into a single request
2. Set appropriate timeouts — Long queries may need extended server timeout
3. Limit result size — Use top or take in Kusto queries
4. Use projections — Select only needed columns with project
5. Check query status — Handle PARTIAL_FAILURE results gracefully
6. Cache results — Metrics don't change frequently; cache when appropriate
7. Migrate to new packages — Plan migration to azure-monitor-query-logs and azure-monitor-query-metrics

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/azure-monitor-query-java, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Reference Links

Imported: Environment Variables

LOG_ANALYTICS_WORKSPACE_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
AZURE_RESOURCE_ID=/subscriptions/{sub}/resourceGroups/{rg}/providers/{provider}/{resource}

Imported: 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();

Imported: Key Concepts

Imported: 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
);

Imported: 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()));
    }
}

Imported: 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

Imported: 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());
}

Imported: 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.