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azure-monitor-ingestion-java

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".

Install / Use

npx skills add microsoft/skills --skill azure-monitor-ingestion-java

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

93/100

Category

Operations

Supported Platforms

Universal

Our assessment of azure-monitor-ingestion-java

azure-monitor-ingestion-java scores 93/100 on our quality scale, 132nd of 503 Operations skills we index (top 27%).

Its SKILL.md is 7.8 KB long, well organised into 18 sections with 12 code examples: a thorough specification that gives an agent plenty to work with.

With 3,051 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so azure-monitor-ingestion-java is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-29. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

azure-monitor-ingestion-java compared with similar skills

All 4 of these similar skills score higher than azure-monitor-ingestion-java; compare them before choosing.

SkillScoreStarsUpdatedFormat
azure-monitor-ingestion-java (this skill)by microsoft933.1k5d agoSKILL.md
Agent-Reachby Panniantong10086.1k13d agoCLAUDE.md
headroomby headroomlabs-ai10074.1ktodayCLAUDE.md
crawl4aiby unclecode10084.4k4d agoMCP Server
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Frequently asked questions

How do I install azure-monitor-ingestion-java?
Run npx skills add microsoft/skills --skill azure-monitor-ingestion-java. The install tabs above show the steps for each supported agent.
Which AI agents does azure-monitor-ingestion-java work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is azure-monitor-ingestion-java safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is azure-monitor-ingestion-java still maintained?
The repository was last updated 5 days ago, so azure-monitor-ingestion-java is actively maintained.

name: azure-monitor-ingestion-java description: | 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". license: MIT metadata: author: Microsoft version: "1.0.0" package: com.azure:azure-monitor-ingestion

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

  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 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 |

Related Skills

View on GitHub
GitHub Stars3.1k
CategoryOperations
Updated5d ago
Forks349

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions