azure-monitor-ingestion-java — Claude Code skill: logs to Azure
Tells the agent how to ship custom logs to Azure Monitor from Java using the Logs Ingestion API, DCR and DCE.
npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a claude-codeWhat azure-monitor-ingestion-java does
The skill covers the com.azure:azure-monitor-ingestion client library for Java. Your agent gets ready-made patterns: building LogsIngestionClient and LogsIngestionAsyncClient, calling upload with a data collection rule ID and stream name, and a log entry model with getters for JSON serialization.
It also documents concurrent uploads with LogsUploadOptions.setMaxConcurrency, partial failure handling through setLogsUploadErrorConsumer, and sorting HttpResponseException by status code 403 or 404. The async path uses Reactor with doOnSuccess and doOnError.
You need a Data Collection Endpoint, a Data Collection Rule, a Log Analytics workspace and a target table before any of this runs. Without DATA_COLLECTION_ENDPOINT and DATA_COLLECTION_RULE_ID the client cannot be built, so check the environment first. Log entry fields must match the DCR transformation schema or the upload fails.
What it helps with
- send application logs to Azure Monitor from Java code
- route logs through a Data Collection Rule and stream
- speed up large log batches with concurrency
- handle partial upload failures without losing the rest
- tell a 403 apart from a 404 when hitting the DCE
Example prompts for the agent
- Show me how to build a LogsIngestionClient with DefaultAzureCredential and upload a list of logs to the Custom-MyTable_CL stream
- Add concurrent log upload with LogsUploadOptions and maxConcurrency 3
- Catch HttpResponseException on upload and explain what to check on a 403
How to install azure-monitor-ingestion-java
1Skills CLI (Vercel)
npx skills add microsoft/skills --skill azure-monitor-ingestion-java -a claude-code2Manually: put the files in place
~/.claude/skills/azure-monitor-ingestion-java/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/azure-monitor-ingestion-java/
Manually: put the files in place
.agents/skills/azure-monitor-ingestion-java/SKILL.mdFor all projects use ~/.agents/skills/
Manually: put the files in place
.cursor/skills/azure-monitor-ingestion-java/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install microsoft/skills azure-monitor-ingestion-java2Manually: put the files in place
.github/skills/azure-monitor-ingestion-java/SKILL.mdPlatform CLI
gemini skills install https://github.com/microsoft/skills --path .github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-javaManually: put the files in place
.devin/skills/azure-monitor-ingestion-java/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about azure-monitor-ingestion-java
How do I install azure-monitor-ingestion-java in GitHub Copilot?
Run gh skill install microsoft/skills azure-monitor-ingestion-java. The skill lands in .github/skills/azure-monitor-ingestion-java/SKILL.md.
What does azure-monitor-ingestion-java do?
It gives the agent a reference for the Java SDK that sends custom logs to Azure Monitor. Client setup, upload calls, concurrency and error handling are all covered.
What do I need before using the skill?
A Data Collection Endpoint, a Data Collection Rule, a Log Analytics workspace and a target table. Set DATA_COLLECTION_ENDPOINT, DATA_COLLECTION_RULE_ID and STREAM_NAME as well.
Source text
SKILL.md · MIT
---
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
```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
| 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
```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](../query/SKILL.md) to query ingested logs:
```java
// 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 |
© Microsoft · MIT · microsoft/skills