azure-monitor-ingestion-java
12
总安装量
12
周安装量
#26254
全站排名
安装命令
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill azure-monitor-ingestion-java
Agent 安装分布
codex
12
openclaw
11
antigravity
11
claude-code
11
gemini-cli
11
cursor
11
Skill 文档
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
DATA_COLLECTION_RULE_ID=dcr-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
STREAM_NAME=Custom-MyTable_CL
Client Creation
Synchronous Client
import com.azure.identity.DefaultAzureCredential;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.monitor.ingestion.LogsIngestionClient;
import com.azure.monitor.ingestion.LogsIngestionClientBuilder;
DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().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(new DefaultAzureCredentialBuilder().build())
.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 â Upload in batches rather than one at a time
- Use concurrency â Set
maxConcurrencyfor large uploads - Handle partial failures â Use error consumer to log failed entries
- Match DCR schema â Log entry fields must match DCR transformation expectations
- Include TimeGenerated â Most tables require a timestamp field
- Reuse client â Create once, reuse throughout application
- Use async for high throughput â
LogsIngestionAsyncClientfor 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
When to Use
This skill is applicable to execute the workflow or actions described in the overview.