Azure Monitor Ingestion Java

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

    com.azure
    azure-monitor-ingestion
    1.2.11

Or use Azure SDK BOM:

    
        
            com.azure
            azure-sdk-bom
            {bom_version}
            pom
            import
        
    

    
        com.azure
        azure-monitor-ingestion
    

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://..ingest.monitor.azure.com  # Required for all auth methods
DATA_COLLECTION_RULE_ID=dcr-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx  # Required for log upload routing
STREAM_NAME=Custom-MyTable_CL  # Required for the target DCR stream
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Client Creation

Synchronous Client

import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;
import com.azure.monitor.ingestion.LogsIngestionClient;
import com.azure.monitor.ingestion.LogsIngestionClientBuilder;

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=
TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

LogsIngestionClient client = new LogsIngestionClientBuilder()
    .endpoint("")
    .credential(credential)
    .buildClient();

Asynchronous Client

import com.azure.monitor.ingestion.LogsIngestionAsyncClient;

LogsIngestionAsyncClient asyncClient = new LogsIngestionClientBuilder()
    .endpoint("")
    .credential(credential)
    .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 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("", "", 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 logs = getLargeLogs(); // Large collection

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

client.upload("", "", 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("", "", logs, options, Context.NONE);

Async Upload with Reactor

import reactor.core.publisher.Mono;

List logs = getLogs();

asyncClient.upload("", "", 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

1. Batch logs — Upload in batches rather than one at a time
2. Use concurrency — Set maxConcurrency for large uploads
3. Handle partial failures — Use error consumer to log failed entries
4. Match DCR schema — Log entry fields must match DCR transformation expectations
5. Include TimeGenerated — Most tables require a timestamp field
6. Reuse client — Create once, reuse throughout application
7. Use async for high throughput — LogsIngestionAsyncClient for reactive patterns

Querying Uploaded Logs

Use [azure-monitor-query](../query/SKILL.md) 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 |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: microsoft
• Source: microsoft/skills
• License: MIT
• Homepage: https://microsoft.github.io/skills/

Install and usage instructions live in the source repository linked above.