Azure Monitor Ingestion SDK for Java

Client library for sending custom logs to Azure Monitor using the Logs Ingestion API via Data Collection Rules.

Installation

<dependency> <groupId>com.azure</groupId> <artifactId>azure-monitor-ingestion</artifactId> <version>1.2.11</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-ingestion</artifactId> </dependency> </dependencies>

Prerequisites

• Data Collection Endpoint (DCE)

• Data Collection Rule (DCR)

• Log Analytics workspace

• Target table (custom or built-in: CommonSecurityLog, SecurityEvents, Syslog, WindowsEvents)

Environment Variables

DATA_COLLECTION_ENDPOINT=https://<dce-name>.<region>.ingest.monitor.azure.com DATA_COLLECTION_RULE_ID=dcr-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx STREAM_NAME=Custom-MyTable_CL

Client Creation

Synchronous Client

import com.azure.identity.DefaultAzureCredential; import com.azure.identity.DefaultAzureCredentialBuilder; import com.azure.monitor.ingestion.LogsIngestionClient; import com.azure.monitor.ingestion.LogsIngestionClientBuilder;

DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();

LogsIngestionClient client = new LogsIngestionClientBuilder() .endpoint("<data-collection-endpoint>") .credential(credential) .buildClient();

Asynchronous Client

import com.azure.monitor.ingestion.LogsIngestionAsyncClient;

LogsIngestionAsyncClient asyncClient = new LogsIngestionClientBuilder() .endpoint("<data-collection-endpoint>") .credential(new DefaultAzureCredentialBuilder().build()) .buildAsyncClient();

Key Concepts

Concept Description

Data Collection Endpoint (DCE) Ingestion endpoint URL for your region

Data Collection Rule (DCR) Defines data transformation and routing to tables

Stream Name Target stream in the DCR (e.g., Custom-MyTable_CL )

Log Analytics Workspace Destination for ingested logs

Core Operations

Upload Custom Logs

import java.util.List; import java.util.ArrayList;

List<Object> logs = new ArrayList<>(); logs.add(new MyLogEntry("2024-01-15T10:30:00Z", "INFO", "Application started")); logs.add(new MyLogEntry("2024-01-15T10:30:05Z", "DEBUG", "Processing request"));

client.upload("<data-collection-rule-id>", "<stream-name>", logs); System.out.println("Logs uploaded successfully");

Upload with Concurrency

For large log collections, enable concurrent uploads:

import com.azure.monitor.ingestion.models.LogsUploadOptions; import com.azure.core.util.Context;

List<Object> logs = getLargeLogs(); // Large collection

LogsUploadOptions options = new LogsUploadOptions() .setMaxConcurrency(3);

client.upload("<data-collection-rule-id>", "<stream-name>", logs, options, Context.NONE);

Upload with Error Handling

Handle partial upload failures gracefully:

LogsUploadOptions options = new LogsUploadOptions() .setLogsUploadErrorConsumer(uploadError -> { System.err.println("Upload error: " + uploadError.getResponseException().getMessage()); System.err.println("Failed logs count: " + uploadError.getFailedLogs().size());

    // Option 1: Log and continue
    // Option 2: Throw to abort remaining uploads
    // throw uploadError.getResponseException();
});

client.upload("<data-collection-rule-id>", "<stream-name>", logs, options, Context.NONE);

Async Upload with Reactor

import reactor.core.publisher.Mono;

List<Object> logs = getLogs();

asyncClient.upload("<data-collection-rule-id>", "<stream-name>", logs) .doOnSuccess(v -> System.out.println("Upload completed")) .doOnError(e -> System.err.println("Upload failed: " + e.getMessage())) .subscribe();

Log Entry Model Example

public class MyLogEntry { private String timeGenerated; private String level; private String message;

public MyLogEntry(String timeGenerated, String level, String message) {
    this.timeGenerated = timeGenerated;
    this.level = level;
    this.message = message;
}

// Getters required for JSON serialization
public String getTimeGenerated() { return timeGenerated; }
public String getLevel() { return level; }
public String getMessage() { return message; }

}

Error Handling

import com.azure.core.exception.HttpResponseException;

try { client.upload(ruleId, streamName, logs); } catch (HttpResponseException e) { System.err.println("HTTP Status: " + e.getResponse().getStatusCode()); System.err.println("Error: " + e.getMessage());

if (e.getResponse().getStatusCode() == 403) {
    System.err.println("Check DCR permissions and managed identity");
} else if (e.getResponse().getStatusCode() == 404) {
    System.err.println("Verify DCE endpoint and DCR ID");
}

}

Best Practices

• Batch logs — Upload in batches rather than one at a time

• Use concurrency — Set maxConcurrency for large uploads

• Handle partial failures — Use error consumer to log failed entries

• Match DCR schema — Log entry fields must match DCR transformation expectations

• Include TimeGenerated — Most tables require a timestamp field

• Reuse client — Create once, reuse throughout application

• Use async for high throughput — LogsIngestionAsyncClient for reactive patterns

Querying Uploaded Logs

Use azure-monitor-query to query ingested logs:

// See azure-monitor-query skill for LogsQueryClient usage String query = "MyTable_CL | where TimeGenerated > ago(1h) | limit 10";

Reference Links

Resource URL

Maven Package https://central.sonatype.com/artifact/com.azure/azure-monitor-ingestion

GitHub https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/monitor/azure-monitor-ingestion

Product Docs https://learn.microsoft.com/azure/azure-monitor/logs/logs-ingestion-api-overview

DCE Overview https://learn.microsoft.com/azure/azure-monitor/essentials/data-collection-endpoint-overview

DCR Overview https://learn.microsoft.com/azure/azure-monitor/essentials/data-collection-rule-overview

Troubleshooting https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/monitor/azure-monitor-ingestion/TROUBLESHOOTING.md