Azure Monitor Ingestion Java — Agent Skill by Microsoft

From the author

Azure Monitor Ingestion SDK for Java. Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE). Triggers: "LogsIngestionClient java", "azure monitor ingestion java", "custom logs java", "DCR java", "data collection rule java".

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Azure Monitor Ingestion SDK for Java provides a client library for developers to send custom log data to Azure Monitor. It utilizes Data Collection Rules (DCR) and Data Collection Endpoints (DCE) to route and ingest logs into Log Analytics workspaces. The library supports both synchronous and asynchronous operations, allowing for flexible integration into Java applications.

What it does

Provides a client for interacting with the Azure Monitor Logs Ingestion API.
Supports uploading custom log entries to specified DCR streams.
Offers both synchronous and asynchronous client implementations.
Enables configuration of concurrent uploads for log collections.
Includes error handling mechanisms for partial upload failures.
Integrates with Azure Identity for authentication.

When to use it

When you need to send custom application logs to Azure Monitor.
When your architecture requires routing logs through Data Collection Rules.
When building Java applications that need to ingest data into Log Analytics workspaces.
When you need to manage log ingestion programmatically within a Java environment.

Advantages

Native Java support for the Azure Monitor Logs Ingestion API.
Flexible authentication options via Azure Identity.
Built-in support for batching and concurrency.
Provides structured error handling for log upload operations.

Usage examples

“How do I initialize the LogsIngestionClient in Java?”: You use the LogsIngestionClientBuilder, providing the data collection endpoint and a credential object, such as DefaultAzureCredential.
“How can I upload a list of custom logs to Azure Monitor?”: You call the upload method on the client, passing the DCR ID, the target stream name, and the list of log objects.
“How do I handle errors during log ingestion?”: You can use LogsUploadOptions to set a logsUploadErrorConsumer, which allows you to process failed log entries during the upload process.
“Can I perform log uploads asynchronously?”: Yes, by using the LogsIngestionAsyncClient, which supports reactive patterns for non-blocking log ingestion.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-monitor-ingestion-java/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip azure-monitor-ingestion-java.zip -d .agents/skills

Documentation by Microsoft

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  # 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=<specific_credential>
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("<data-collection-endpoint>")
    .credential(credential)
    .buildClient();

Asynchronous Client

import com.azure.monitor.ingestion.LogsIngestionAsyncClient;

LogsIngestionAsyncClient asyncClient = new LogsIngestionClientBuilder()
    .endpoint("<data-collection-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<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

Files

ATTRIBUTION.mdAdded by AutoGineer991 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md7.8 KiB
references/examples.md7.9 KiB

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Security

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-monitor-ingestion-java.zip