Official agent skill

Azure Monitor Ingestion Java

by microsoft in microsoft/skills

Azure Monitor Ingestion SDK for Java. An agent skill from microsoft/skills.

OfficialMITAuto-check passedDevOps & Cloud

Install Azure Monitor Ingestion Java

skills CLI
$ npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/skills azure-monitor-ingestion-java --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-java .claude/skills/azure-monitor-ingestion-java && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-monitor-ingestion-java
GitHub stars
3.1k
Used in
5 other repos
Token cost
~2k tokens
SKILL.md length
235 words
Files
2 (incl. references)
Skills in repo
150
Repo updated
First seen
Licence
MIT

At a glance

Azure Monitor Ingestion SDK for Java. An agent skill from microsoft/skills.

  • Works in 7 steps: Batch logs — Upload in batches rather… → Use concurrency — Set maxConcurrency for… → Handle partial failures — Use error… → …
  • DevOps & Cloud work in your project
  • SKILL.md covers Installation, Prerequisites, Environment Variables and Client Creation, plus 7 more sections
  • Reaches learn.microsoft.com; needs AZURE_TOKEN_CREDENTIALS

What it does

Azure Monitor Ingestion Java is an agent skill from microsoft/skills, published by the product's own GitHub organization. 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".

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/examples.md`).

It sits in DevOps & Cloud. It works with Azure Monitor, Java and Microsoft Azure. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.

When your agent uses it

  • DevOps & Cloud work in your project

Example prompts

  • “LogsIngestionClient java”
  • “azure monitor ingestion java”
  • “custom logs java”
  • “/azure-monitor-ingestion-java”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit d5741a1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are java, xml and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • learn.microsoft.com

    Also links to:

    • github.com
    • central.sonatype.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AZURE_TOKEN_CREDENTIALS

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure Monitor Ingestion Java loads about 2k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 235 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/skills at commit d5741a1, republished under its MIT licence (© microsoft). 235 words, ~2,005 tokens.

Download SKILL.mdSave it as .claude/skills/azure-monitor-ingestion-java/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
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
metadata.version
1.0.0
metadata.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

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

Or use Azure SDK BOM:

xml
<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

bash
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
java
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
java
import com.azure.monitor.ingestion.LogsIngestionAsyncClient;

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

Key Concepts

ConceptDescription
Data Collection Endpoint (DCE)Ingestion endpoint URL for your region
Data Collection Rule (DCR)Defines data transformation and routing to tables
Stream NameTarget stream in the DCR (e.g., Custom-MyTable_CL)
Log Analytics WorkspaceDestination for ingested logs

Core Operations

Upload Custom Logs
java
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:

java
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:

java
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
java
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

java
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

java
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:

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

© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in .github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-java of microsoft/skills.

  • SKILL.md
  • references/examples.md

Open the folder on GitHubat commit d5741a1

Used in 5 other repositories

We found 14 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in microsoft/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Azure Monitor Ingestion Java next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure Monitor Ingestion Java compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Azure Monitor Ingestion Java this skillmicrosoft/skills3.1k5 repos~2kAutomated safety check: PassMIT
Azure Sre AgentMicrosoftDocs/Agent-Skills776—~2.7kAutomated safety check: PassCC-BY-4.0
Azure Anomaly DetectorMicrosoftDocs/Agent-Skills776—~1.1kAutomated safety check: PassCC-BY-4.0
Appinsights Instrumentationmicrosoft/GitHub-Copilot-for-Azure2551 repos~951Automated safety check: PassMIT
Avm Tf TelemetryAzure/terraform-azurerm-avm-ptn-alz135—~2.9kAutomated safety check: PassMIT
Azure Application NetworkMicrosoftDocs/Agent-Skills776—~726Automated safety check: PassCC-BY-4.0

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Categories

Questions about Azure Monitor Ingestion Java

What does Azure Monitor Ingestion Java do?

Azure Monitor Ingestion SDK for Java. An agent skill from microsoft/skills. Azure Monitor Ingestion Java is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Monitor Ingestion SDK for Java.

When should I use Azure Monitor Ingestion Java?

Azure Monitor Ingestion Java fits situations like: devOps & Cloud work in your project.

How do I install Azure Monitor Ingestion Java in Claude Code?

Run `npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-java in microsoft/skills) into .claude/skills/azure-monitor-ingestion-java in your project. Claude Code loads it when a task matches its description.

How do I install Azure Monitor Ingestion Java in Codex?

Run `npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-java in microsoft/skills) into .agents/skills/azure-monitor-ingestion-java in your project. Codex loads it when a task matches its description.

Can I use Azure Monitor Ingestion Java in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-monitor-ingestion-java, .gemini/skills/azure-monitor-ingestion-java, .github/skills/azure-monitor-ingestion-java and .opencode/skills/azure-monitor-ingestion-java in your project.

What does Azure Monitor Ingestion Java need to run?

Going by SKILL.md and its folder, Azure Monitor Ingestion Java needs credentials named AZURE_TOKEN_CREDENTIALS.

Does Azure Monitor Ingestion Java access the network?

SKILL.md names 3 domains. In commands or code: learn.microsoft.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com and central.sonatype.com. This is read from the text; nothing was executed.

Is Azure Monitor Ingestion Java safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Monitor Ingestion Java use?

Azure Monitor Ingestion Java is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure Monitor Ingestion Java use?

About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Azure Monitor Ingestion Java?

Skills that share tags, products or a category with Azure Monitor Ingestion Java: Azure Sre Agent (MicrosoftDocs/Agent-Skills, 776 stars), Azure Anomaly Detector (MicrosoftDocs/Agent-Skills, 776 stars), Appinsights Instrumentation (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Avm Tf Telemetry (Azure/terraform-azurerm-avm-ptn-alz, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Monitor Ingestion Java?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,097 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 9, 2026.

Source: microsoft/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.