Azure Monitor Query client library for Java - version 1.5.3

The Azure Monitor Query client library is used to execute read-only queries against Azure Monitor's two data platforms:

• Logs - Collects and organizes log and performance data from monitored resources. Data from different sources such as platform logs from Azure services, log and performance data from virtual machines agents, and usage and performance data from apps can be consolidated into a single Azure Log Analytics workspace. The various data types can be analyzed together using the Kusto Query Language.
• Metrics - Collects numeric data from monitored resources into a time series database. Metrics are numerical values that are collected at regular intervals and describe some aspect of a system at a particular time. Metrics are lightweight and capable of supporting near real-time scenarios, making them useful for alerting and fast detection of issues.

Resources:

• Source code
• Package (Maven)
• API reference documentation
• Service documentation
• Samples
• Change log

Getting started

Prerequisites

• A Java Development Kit (JDK), version 8 or later
  • Here are details about Java 8 client compatibility with Azure Certificate Authority.
• An Azure subscription
• A TokenCredential implementation, such as an Azure Identity library credential type.
• To query Logs, you need an Azure Log Analytics workspace or an Azure resource of any kind (Storage Account, Key Vault, Cosmos DB, etc.).
• To query Metrics, you need an Azure resource of any kind (Storage Account, Key Vault, Cosmos DB, etc.).

Include the package

Include the BOM file

Include the azure-sdk-bom to your project to take a dependency on the stable version of the library. In the following snippet, replace the {bom_version_to_target} placeholder with the version number. To learn more about the BOM, see the AZURE SDK BOM README.

<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>com.azure</groupId>
            <artifactId>azure-sdk-bom</artifactId>
            <version>{bom_version_to_target}</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>

Then include the direct dependency in the dependencies section without the version tag:

<dependencies>
  <dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-monitor-query</artifactId>
  </dependency>
</dependencies>

Include direct dependency

If you want to take dependency on a particular version of the library that isn't present in the BOM, add the direct dependency to your project as follows.

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-monitor-query</artifactId>
    <version>1.5.3</version>
</dependency>

Create the client

An authenticated client is required to query Logs or Metrics. The library includes both synchronous and asynchronous forms of the clients. To authenticate, the following examples use DefaultAzureCredentialBuilder from the azure-identity package.

Authenticate using Microsoft Entra ID

You can authenticate with Microsoft Entra ID using the Azure Identity library. Regional endpoints don't support Microsoft Entra authentication. Create a custom subdomain for your resource to use this type of authentication.

To use the DefaultAzureCredential provider shown below, or other credential providers provided with the Azure Identity library, include the azure-identity package:

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-identity</artifactId>
    <version>1.12.2</version>
</dependency>

Set the values of the client ID, tenant ID, and client secret of the Microsoft Entra application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET.

Synchronous clients

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

MetricsQueryClient metricsQueryClient = new MetricsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

MetricsClient metricsClient = new MetricsClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .endpoint("{endpoint}")
    .buildClient();

Asynchronous clients

LogsQueryAsyncClient logsQueryAsyncClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();

MetricsQueryAsyncClient metricsQueryAsyncClient = new MetricsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();

MetricsAsyncClient metricsAsyncClient = new MetricsClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .endpoint("{endpoint}")
    .buildAsyncClient();

Configure client for Azure sovereign cloud

By default, LogsQueryClient, MetricsQueryClient and MetricsClient are configured to connect to the Azure Public Cloud. To use a sovereign cloud instead, set the correct endpoint in the client builders.
Additionally, for creating a MetricsClient instance, the audience should also be set in MetricsClientBuilder as shown in the sample below.

• Creating a LogsQueryClient for Azure China Cloud:

  LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
      .credential(new DefaultAzureCredentialBuilder().build())
      .endpoint("https://api.loganalytics.azure.cn/v1")
      .buildClient();
  

• Creating a MetricsQueryClient for Azure China Cloud:

  MetricsQueryClient metricsQueryClient = new MetricsQueryClientBuilder()
      .credential(new DefaultAzureCredentialBuilder().build())
      .endpoint("https://management.chinacloudapi.cn")
      .buildClient();
  

• Creating a MetricsClient for Azure China Cloud:

  MetricsClient metricsClient = new MetricsClientBuilder()
      .endpoint("<endpoint>")
      .credential(new DefaultAzureCredentialBuilder().build())
      .audience(MetricsAudience.AZURE_CHINA)
      .buildClient();
  

Execute the query

For examples of Logs and Metrics queries, see the Examples section.

Key concepts

Logs query rate limits and throttling

The Log Analytics service applies throttling when the request rate is too high. Limits, such as the maximum number of rows returned, are also applied on the Kusto queries. For more information, see Query API.

Metrics data structure

Each set of metric values is a time series with the following characteristics:

• The time the value was collected
• The resource associated with the value
• A namespace that acts like a category for the metric
• A metric name
• The value itself
• Some metrics have multiple dimensions as described in multi-dimensional metrics. Custom metrics can have up to 10 dimensions.

Examples

• Logs query
  • Map logs query results to a model
  • Handle logs query response
  • Query logs by resource ID
• Batch logs query
• Advanced logs query scenarios
  • Set logs query timeout
  • Query multiple workspaces
  • Include statistics
  • Include visualization
  • Overcome Log Analytics query size limitations
• Metrics query
  • Handle metrics query response
  • Get average and count metrics
• Metrics query resources
  • Handle metrics query resources response

Logs query

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

LogsQueryResult queryResults = logsQueryClient.queryWorkspace("{workspace-id}", "{kusto-query}",
    new QueryTimeInterval(Duration.ofDays(2)));

for (LogsTableRow row : queryResults.getTable().getRows()) {
    System.out.println(row.getColumnValue("OperationName") + " " + row.getColumnValue("ResourceGroup"));
}

Map logs query results to a model

public class CustomLogModel {
    private String resourceGroup;
    private String operationName;

    public String getResourceGroup() {
        return resourceGroup;
    }

    public String getOperationName() {
        return operationName;
    }
}

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

List<CustomLogModel> customLogModels = logsQueryClient.queryWorkspace("{workspace-id}", "{kusto-query}",
    new QueryTimeInterval(Duration.ofDays(2)), CustomLogModel.class);

for (CustomLogModel customLogModel : customLogModels) {
    System.out.println(customLogModel.getOperationName() + " " + customLogModel.getResourceGroup());
}

Handle logs query response

The query API returns the LogsQueryResult, while the queryBatch API returns the LogsBatchQueryResult. Here's a hierarchy of the response:

LogsQueryResult / LogsBatchQueryResult
|---id (this exists in `LogsBatchQueryResult` object only)
|---status (this exists in `LogsBatchQueryResult` object only)
|---statistics
|---visualization
|---error
|---tables (list of `LogsTable` objects)
    |---name
    |---rows (list of `LogsTableRow` objects)
        |--- rowIndex
        |--- rowCells (list of `LogsTableCell` objects)
    |---columns (list of `LogsTableColumn` objects)
        |---name
        |---type

Query logs by resource ID

The LogsQueryClient supports querying logs using a workspace ID (queryWorkspace methods) or a resource ID (queryResource methods). See the following example of querying logs using a resource ID. Similar changes can be applied to all other samples.

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

LogsQueryResult queryResults = logsQueryClient.queryResource("{resource-id}", "{kusto-query}",
    new QueryTimeInterval(Duration.ofDays(2)));

for (LogsTableRow row : queryResults.getTable().getRows()) {
    System.out.println(row.getColumnValue("OperationName") + " " + row.getColumnValue("ResourceGroup"));
}

Batch logs query

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

LogsBatchQuery logsBatchQuery = new LogsBatchQuery();
String query1 = logsBatchQuery.addWorkspaceQuery("{workspace-id}", "{query-1}", new QueryTimeInterval(Duration.ofDays(2)));
String query2 = logsBatchQuery.addWorkspaceQuery("{workspace-id}", "{query-2}", new QueryTimeInterval(Duration.ofDays(30)));
String query3 = logsBatchQuery.addWorkspaceQuery("{workspace-id}", "{query-3}", new QueryTimeInterval(Duration.ofDays(10)));

LogsBatchQueryResultCollection batchResults = logsQueryClient
    .queryBatchWithResponse(logsBatchQuery, Context.NONE).getValue();

LogsBatchQueryResult query1Result = batchResults.getResult(query1);
for (LogsTableRow row : query1Result.getTable().getRows()) {
    System.out.println(row.getColumnValue("OperationName") + " " + row.getColumnValue("ResourceGroup"));
}

List<CustomLogModel> customLogModels = batchResults.getResult(query2, CustomLogModel.class);
for (CustomLogModel customLogModel : customLogModels) {
    System.out.println(customLogModel.getOperationName() + " " + customLogModel.getResourceGroup());
}

LogsBatchQueryResult query3Result = batchResults.getResult(query3);
if (query3Result.getQueryResultStatus() == LogsQueryResultStatus.FAILURE) {
    System.out.println(query3Result.getError().getMessage());
}

Advanced logs query scenarios

Set logs query timeout

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

// set request options: server timeout
LogsQueryOptions options = new LogsQueryOptions()
    .setServerTimeout(Duration.ofMinutes(10));

Response<LogsQueryResult> response = logsQueryClient.queryWorkspaceWithResponse("{workspace-id}",
    "{kusto-query}", new QueryTimeInterval(Duration.ofDays(2)), options, Context.NONE);

Query multiple workspaces

To run the same query against multiple Log Analytics workspaces, use the LogsQueryOptions.setAdditionalWorkspaces method.

When multiple workspaces are included in the query, the logs in the result table aren't grouped according to the workspace from which it was retrieved. To identify the workspace of a row in the result table, you can inspect the "TenantId" column in the result table. If this column isn't in the table, then you may have to update your query string to include this column.

LogsQueryClient logsQueryClient = new LogsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

Response<LogsQueryResult> response = logsQueryClient.queryWorkspaceWithResponse("{workspace-id}", "{kusto-query}",
    new QueryTimeInterval(Duration.ofDays(2)), new LogsQueryOptions()
        .setAdditionalWorkspaces(Arrays.asList("{additional-workspace-identifiers}")),
    Context.NONE);
LogsQueryResult result = response.getValue();

Include statistics

To get logs query execution statistics, such as CPU and memory consumption:

1. Use LogsQueryOptions to request for statistics in the response by setting setIncludeStatistics() to true.
2. Invoke the getStatistics method on the LogsQueryResult object.

The following example prints the query execution time:

LogsQueryClient client = new LogsQueryClientBuilder()
    .credential(credential)
    .buildClient();

LogsQueryOptions options = new LogsQueryOptions()
    .setIncludeStatistics(true);
Response<LogsQueryResult> response = client.queryWorkspaceWithResponse("{workspace-id}",
    "AzureActivity | top 10 by TimeGenerated", QueryTimeInterval.LAST_1_HOUR, options, Context.NONE);
LogsQueryResult result = response.getValue();
BinaryData statistics = result.getStatistics();

ObjectMapper objectMapper = new ObjectMapper();
JsonNode statisticsJson = objectMapper.readTree(statistics.toBytes());
JsonNode queryStatistics = statisticsJson.get("query");
System.out.println("Query execution time = " + queryStatistics.get("executionTime").asDouble());

Because the structure of the statistics payload varies by query, a BinaryData return type is used. It contains the raw JSON response. The statistics are found within the query property of the JSON. For example:

{
  "query": {
    "executionTime": 0.0156478,
    "resourceUsage": {...},
    "inputDatasetStatistics": {...},
    "datasetStatistics": [{...}]
  }
}

Include visualization

To get visualization data for logs queries using the render operator:

1. Use LogsQueryOptions to request for visualization data in the response by setting setIncludeVisualization() to true.
2. Invoke the getVisualization method on the LogsQueryResult object.

For example:

LogsQueryClient client = new LogsQueryClientBuilder()
    .credential(credential)
    .buildClient();

String visualizationQuery = "StormEvents"
    + "| summarize event_count = count() by State"
    + "| where event_count > 10"
    + "| project State, event_count"
    + "| render columnchart";
LogsQueryOptions options = new LogsQueryOptions()
    .setIncludeVisualization(true);
Response<LogsQueryResult> response = client.queryWorkspaceWithResponse("{workspace-id}", visualizationQuery,
    QueryTimeInterval.LAST_7_DAYS, options, Context.NONE);
LogsQueryResult result = response.getValue();
BinaryData visualization = result.getVisualization();

ObjectMapper objectMapper = new ObjectMapper();
JsonNode visualizationJson = objectMapper.readTree(visualization.toBytes());
System.out.println("Visualization graph type = " + visualizationJson.get("visualization").asText());

Because the structure of the visualization payload varies by query, a BinaryData return type is used. It contains the raw JSON response. For example:

{
  "visualization": "columnchart",
  "title": null,
  "accumulate": false,
  "isQuerySorted": false,
  "kind": null,
  "legend": null,
  "series": null,
  "yMin": "",
  "yMax": "",
  "xAxis": null,
  "xColumn": null,
  "xTitle": null,
  "yAxis": null,
  "yColumns": null,
  "ySplit": null,
  "yTitle": null,
  "anomalyColumns": null
}

Overcome Log Analytics query size limitations

If your query exceeds the service limits, see the large log query documentation to learn how to overcome them.

Metrics query

A resource ID, as denoted by the {resource-uri} placeholder in the following sample, is required to query metrics. To find the resource ID:

1. Navigate to your resource's page in the Azure portal.
2. From the Overview blade, select the JSON View link.
3. In the resulting JSON, copy the value of the id property.

MetricsQueryClient metricsQueryClient = new MetricsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

MetricsQueryResult metricsQueryResult = metricsQueryClient.queryResource("{resource-uri}",
    Arrays.asList("SuccessfulCalls", "TotalCalls"));

for (MetricResult metric : metricsQueryResult.getMetrics()) {
    System.out.println("Metric name " + metric.getMetricName());
    for (TimeSeriesElement timeSeriesElement : metric.getTimeSeries()) {
        System.out.println("Dimensions " + timeSeriesElement.getMetadata());
        for (MetricValue metricValue : timeSeriesElement.getValues()) {
            System.out.println(metricValue.getTimeStamp() + " " + metricValue.getTotal());
        }
    }
}

Handle metrics query response

The metrics query API returns a MetricsQueryResult object. The MetricsQueryResult object contains properties such as a list of MetricResult-typed objects, granularity, namespace, and timeInterval. The MetricResult objects list can be accessed using the metrics param. Each MetricResult object in this list contains a list of TimeSeriesElement objects. Each TimeSeriesElement contains data and metadata_values properties. In visual form, the object hierarchy of the response resembles the following structure:

MetricsQueryResult
|---granularity
|---timeInterval
|---cost
|---namespace
|---resourceRegion
|---metrics (list of `MetricResult` objects)
    |---id
    |---type
    |---name
    |---unit
    |---timeSeries (list of `TimeSeriesElement` objects)
        |---metadata (dimensions)
        |---metricValues (list of data points represented by `MetricValue` objects)
             |--- timeStamp
             |--- count
             |--- average
             |--- total
             |--- maximum
             |--- minimum

Get average and count metrics

MetricsQueryClient metricsQueryClient = new MetricsQueryClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

Response<MetricsQueryResult> metricsResponse = metricsQueryClient
    .queryResourceWithResponse("{resource-id}", Arrays.asList("SuccessfulCalls", "TotalCalls"),
        new MetricsQueryOptions()
            .setGranularity(Duration.ofHours(1))
            .setAggregations(Arrays.asList(AggregationType.AVERAGE, AggregationType.COUNT)),
        Context.NONE);

MetricsQueryResult metricsQueryResult = metricsResponse.getValue();

for (MetricResult metric : metricsQueryResult.getMetrics()) {
    System.out.println("Metric name " + metric.getMetricName());
    for (TimeSeriesElement timeSeriesElement : metric.getTimeSeries()) {
        System.out.println("Dimensions " + timeSeriesElement.getMetadata());
        for (MetricValue metricValue : timeSeriesElement.getValues()) {
            System.out.println(metricValue.getTimeStamp() + " " + metricValue.getTotal());
        }
    }
}

Metrics query resources

Handle metrics query resources response

MetricsClient metricsClient = new MetricsClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .endpoint("{endpoint}")
    .buildClient();

MetricsQueryResourcesResult metricsQueryResourcesResult = metricsClient.queryResources(
    Arrays.asList("{resourceId1}", "{resourceId2}"),
    Arrays.asList("{metric1}", "{metric2}"),
    "{metricNamespace}");

for (MetricsQueryResult metricsQueryResult : metricsQueryResourcesResult.getMetricsQueryResults()) {
    // Each MetricsQueryResult corresponds to one of the resourceIds in the batch request.
    List<MetricResult> metrics = metricsQueryResult.getMetrics();
    metrics.forEach(metric -> {
        System.out.println(metric.getMetricName());
        System.out.println(metric.getId());
        System.out.println(metric.getResourceType());
        System.out.println(metric.getUnit());
        System.out.println(metric.getTimeSeries().size());
        System.out.println(metric.getTimeSeries().get(0).getValues().size());
        metric.getTimeSeries()
            .stream()
            .flatMap(ts -> ts.getValues().stream())
            .forEach(mv -> System.out.println(mv.getTimeStamp().toString()
                + "; Count = " + mv.getCount()
                + "; Average = " + mv.getAverage()));
    });
}

Troubleshooting

See our troubleshooting guide for details on how to diagnose various failure scenarios.

Next steps

To learn more about Azure Monitor, see the Azure Monitor service documentation.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information, see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.