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Launch parallel batch or HPC work with Azure Batch in Java

azure-compute-batch-java

In brief

This skill covers the SDK Java Azure Batch. It is used to launch parallel or large-scale HPC work: pools, work, tasks and computation nodes, typically with a `BatchClient`. The account and endpoint are set up via `AZURE_BATCH_ENDPOINT` and `AZURE_BATCH_ACCOUNT`; an access key is just one of the possible authentication paths, next to `AZURE_TOKEN_CREDENTIALS`. The reference language is Java.

What it does

  • Launch parallel or large-scale HPC work: pools, work, tasks and calculation nodes, typically with a `BatchClient`.
  • The account and the endpoint are set up via `AZURE_BATCH_ENDPOINT` and `AZURE_BATCH_ACCOUNT`; an access key is just one of the possible authentication paths, next to `AZURE_TOKEN_CREDENTIALS`.
  • A nearby skill cited is `azure-resourcemanager-batch`.
  • Typical environment variables include `AZURE_BATCH_ENDPOINT`, `AZURE_BATCH_ACCOUNT`, `AZURE_BATCH_ACCESS_KEY`, `AZURE_TOKEN_CREDENTIALS`.
  • Documented customers include `BatchClient`, `BatchClientBuilder`, `TokenCredential`, `DefaultAzureCredentialBuilder`, `ManagedIdentityCredentialBuilder`.
  • Typical authentication goes through

Who it is for, and an example

Java developers submitting parallel or HPC computing lots on Azure Batch, with pools and tasks, rather than a single job on a machine.

Example request: "Creates a Batch pool and parallel tasks in Java, plug-in via AZURE BATCH ENDPOINT. »

It is opened to pilot pools, works and tasks Azure Batch in Java, including an HPC calculation. Example written by iadujour.fr from the SKILL.md, not tested.

Install

npx skills add microsoft/skills (selection of the skill in the assistant, README).

npx skills add microsoft/skills

Works with

  • GitHub Copilot
  • Copilot CLI

Source: README: examples of Copilot CLI and GitHub Copilot in VS Code; installation `npx skills add` sends files to the chosen agent directory, without an exhaustive list.

Level: Intermediate

Suppose a publisher's project and mastery of the corresponding SDK or CLI.

Good to know

Official Microsoft deposit; README presents it as an ongoing work (skills and tests still enriched).

SKILL.md excerpt

The original description, which the agent reads to decide whether to load the skill (in English):

Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes. Triggers: "BatchClient java", "azure batch java", "batch pool java", "batch job java", "HPC java", "parallel computing java".

Quoted from SKILL.md at commit e7ee58f . The folder also contains 1 extra file (references/).

The SKILL.md has 384 lines and 41 main sections:

  • Installation
  • Prerequisites
  • Environment Variables
  • Client Creation
  • With Microsoft Entra ID (Recommended)
  • Async Client
  • With Shared Key Credentials
  • Key Concepts
  • Pool Operations
  • Create Pool
  • Get Pool
  • List Pools
  • Resize Pool
  • Enable AutoScale
  • Delete Pool
  • Job Operations
  • Create Job
  • Get Job
  • List Jobs
  • Get Task Counts
  • Terminate Job
  • Delete Job
  • Task Operations
  • Create Single Task
  • Create Task with Exit Conditions
  • Create Task Collection (up to 100)
  • Create Many Tasks (no limit)
  • Get Task
  • List Tasks
  • Get Task Output
  • Terminate Task
  • Node Operations
  • List Nodes
  • Reboot Node
  • Get Remote Login Settings
  • Job Schedule Operations
  • Create Job Schedule
  • Get Job Schedule
  • Error Handling
  • Best Practices
  • Reference Links

Licence: MIT

Checked on 10 November 2026 : repository LICENSE file . Licence declared in the frontmatter: “MIT”. Rights holder: Copyright (c) Microsoft Corporation..

The licence allows reuse: the full SKILL.md text is reproduced below, unmodified, with its licence notice.

Full SKILL.md text

Reproduced unmodified from microsoft/skills (commit e7ee58f) , © Microsoft, under licence MIT (original licence file ).

Show the original SKILL.md (384 lines, in English)
---
name: azure-compute-batch-java
description: |-
  Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.
  Triggers: "BatchClient java", "azure batch java", "batch pool java", "batch job java", "HPC java", "parallel computing java".
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
---

# Azure Batch SDK for Java

Client library for running large-scale parallel and high-performance computing (HPC) batch jobs in Azure.

## Installation

```xml
<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-compute-batch</artifactId>
    <version>1.0.0-beta.5</version>
</dependency>
```

## Prerequisites

- Azure Batch account
- Pool configured with compute nodes
- Azure subscription

## Environment Variables

```bash
AZURE_BATCH_ENDPOINT=https://<account>.<region>.batch.azure.com  # Required for all auth methods
AZURE_BATCH_ACCOUNT=<account-name>  # Only required for shared key auth
AZURE_BATCH_ACCESS_KEY=<account-key>  # Only required for shared key auth
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production
```

## Client Creation

### With Microsoft Entra ID (Recommended)

```java
import com.azure.compute.batch.BatchClient;
import com.azure.compute.batch.BatchClientBuilder;
import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

// 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();

BatchClient batchClient = new BatchClientBuilder()
    .credential(credential)
    .endpoint(System.getenv("AZURE_BATCH_ENDPOINT"))
    .buildClient();
```

### Async Client

```java
import com.azure.compute.batch.BatchAsyncClient;

BatchAsyncClient batchAsyncClient = new BatchClientBuilder()
    .credential(credential)
    .endpoint(System.getenv("AZURE_BATCH_ENDPOINT"))
    .buildAsyncClient();
```

### With Shared Key Credentials

```java
import com.azure.core.credential.AzureNamedKeyCredential;

String accountName = System.getenv("AZURE_BATCH_ACCOUNT");
String accountKey = System.getenv("AZURE_BATCH_ACCESS_KEY");
AzureNamedKeyCredential sharedKeyCreds = new AzureNamedKeyCredential(accountName, accountKey);

BatchClient batchClient = new BatchClientBuilder()
    .credential(sharedKeyCreds)
    .endpoint(System.getenv("AZURE_BATCH_ENDPOINT"))
    .buildClient();
```

## Key Concepts

| Concept | Description |
|---------|-------------|
| Pool | Collection of compute nodes that run tasks |
| Job | Logical grouping of tasks |
| Task | Unit of computation (command/script) |
| Node | VM that executes tasks |
| Job Schedule | Recurring job creation |

## Pool Operations

### Create Pool

```java
import com.azure.compute.batch.models.*;

batchClient.createPool(new BatchPoolCreateParameters("myPoolId", "STANDARD_DC2s_V2")
    .setVirtualMachineConfiguration(
        new VirtualMachineConfiguration(
            new BatchVmImageReference()
                .setPublisher("Canonical")
                .setOffer("UbuntuServer")
                .setSku("22_04-lts")
                .setVersion("latest"),
            "batch.node.ubuntu 22.04"))
    .setTargetDedicatedNodes(2)
    .setTargetLowPriorityNodes(0), null);
```

### Get Pool

```java
BatchPool pool = batchClient.getPool("myPoolId");
System.out.println("Pool state: " + pool.getState());
System.out.println("Current dedicated nodes: " + pool.getCurrentDedicatedNodes());
```

### List Pools

```java
import com.azure.core.http.rest.PagedIterable;

PagedIterable<BatchPool> pools = batchClient.listPools();
for (BatchPool pool : pools) {
    System.out.println("Pool: " + pool.getId() + ", State: " + pool.getState());
}
```

### Resize Pool

```java
import com.azure.core.util.polling.SyncPoller;

BatchPoolResizeParameters resizeParams = new BatchPoolResizeParameters()
    .setTargetDedicatedNodes(4)
    .setTargetLowPriorityNodes(2);

SyncPoller<BatchPool, BatchPool> poller = batchClient.beginResizePool("myPoolId", resizeParams);
poller.waitForCompletion();
BatchPool resizedPool = poller.getFinalResult();
```

### Enable AutoScale

```java
BatchPoolEnableAutoScaleParameters autoScaleParams = new BatchPoolEnableAutoScaleParameters()
    .setAutoScaleEvaluationInterval(Duration.ofMinutes(5))
    .setAutoScaleFormula("$TargetDedicatedNodes = min(10, $PendingTasks.GetSample(TimeInterval_Minute * 5));");

batchClient.enablePoolAutoScale("myPoolId", autoScaleParams);
```

### Delete Pool

```java
SyncPoller<BatchPool, Void> deletePoller = batchClient.beginDeletePool("myPoolId");
deletePoller.waitForCompletion();
```

## Job Operations

### Create Job

```java
batchClient.createJob(
    new BatchJobCreateParameters("myJobId", new BatchPoolInfo().setPoolId("myPoolId"))
        .setPriority(100)
        .setConstraints(new BatchJobConstraints()
            .setMaxWallClockTime(Duration.ofHours(24))
            .setMaxTaskRetryCount(3)),
    null);
```

### Get Job

```java
BatchJob job = batchClient.getJob("myJobId", null, null);
System.out.println("Job state: " + job.getState());
```

### List Jobs

```java
PagedIterable<BatchJob> jobs = batchClient.listJobs(new BatchJobsListOptions());
for (BatchJob job : jobs) {
    System.out.println("Job: " + job.getId() + ", State: " + job.getState());
}
```

### Get Task Counts

```java
BatchTaskCountsResult counts = batchClient.getJobTaskCounts("myJobId");
System.out.println("Active: " + counts.getTaskCounts().getActive());
System.out.println("Running: " + counts.getTaskCounts().getRunning());
System.out.println("Completed: " + counts.getTaskCounts().getCompleted());
```

### Terminate Job

```java
BatchJobTerminateParameters terminateParams = new BatchJobTerminateParameters()
    .setTerminationReason("Manual termination");
BatchJobTerminateOptions options = new BatchJobTerminateOptions().setParameters(terminateParams);

SyncPoller<BatchJob, BatchJob> poller = batchClient.beginTerminateJob("myJobId", options, null);
poller.waitForCompletion();
```

### Delete Job

```java
SyncPoller<BatchJob, Void> deletePoller = batchClient.beginDeleteJob("myJobId");
deletePoller.waitForCompletion();
```

## Task Operations

### Create Single Task

```java
BatchTaskCreateParameters task = new BatchTaskCreateParameters("task1", "echo 'Hello World'");
batchClient.createTask("myJobId", task);
```

### Create Task with Exit Conditions

```java
batchClient.createTask("myJobId", new BatchTaskCreateParameters("task2", "cmd /c exit 3")
    .setExitConditions(new ExitConditions()
        .setExitCodeRanges(Arrays.asList(
            new ExitCodeRangeMapping(2, 4, 
                new ExitOptions().setJobAction(BatchJobActionKind.TERMINATE)))))
    .setUserIdentity(new UserIdentity()
        .setAutoUser(new AutoUserSpecification()
            .setScope(AutoUserScope.TASK)
            .setElevationLevel(ElevationLevel.NON_ADMIN))),
    null);
```

### Create Task Collection (up to 100)

```java
List<BatchTaskCreateParameters> taskList = Arrays.asList(
    new BatchTaskCreateParameters("task1", "echo Task 1"),
    new BatchTaskCreateParameters("task2", "echo Task 2"),
    new BatchTaskCreateParameters("task3", "echo Task 3")
);
BatchTaskGroup taskGroup = new BatchTaskGroup(taskList);
BatchCreateTaskCollectionResult result = batchClient.createTaskCollection("myJobId", taskGroup);
```

### Create Many Tasks (no limit)

```java
List<BatchTaskCreateParameters> tasks = new ArrayList<>();
for (int i = 0; i < 1000; i++) {
    tasks.add(new BatchTaskCreateParameters("task" + i, "echo Task " + i));
}
batchClient.createTasks("myJobId", tasks);
```

### Get Task

```java
BatchTask task = batchClient.getTask("myJobId", "task1");
System.out.println("Task state: " + task.getState());
System.out.println("Exit code: " + task.getExecutionInfo().getExitCode());
```

### List Tasks

```java
PagedIterable<BatchTask> tasks = batchClient.listTasks("myJobId");
for (BatchTask task : tasks) {
    System.out.println("Task: " + task.getId() + ", State: " + task.getState());
}
```

### Get Task Output

```java
import com.azure.core.util.BinaryData;
import java.nio.charset.StandardCharsets;

BinaryData stdout = batchClient.getTaskFile("myJobId", "task1", "stdout.txt");
System.out.println(new String(stdout.toBytes(), StandardCharsets.UTF_8));
```

### Terminate Task

```java
batchClient.terminateTask("myJobId", "task1", null, null);
```

## Node Operations

### List Nodes

```java
PagedIterable<BatchNode> nodes = batchClient.listNodes("myPoolId", new BatchNodesListOptions());
for (BatchNode node : nodes) {
    System.out.println("Node: " + node.getId() + ", State: " + node.getState());
}
```

### Reboot Node

```java
SyncPoller<BatchNode, BatchNode> rebootPoller = batchClient.beginRebootNode("myPoolId", "nodeId");
rebootPoller.waitForCompletion();
```

### Get Remote Login Settings

```java
BatchNodeRemoteLoginSettings settings = batchClient.getNodeRemoteLoginSettings("myPoolId", "nodeId");
System.out.println("IP: " + settings.getRemoteLoginIpAddress());
System.out.println("Port: " + settings.getRemoteLoginPort());
```

## Job Schedule Operations

### Create Job Schedule

```java
batchClient.createJobSchedule(new BatchJobScheduleCreateParameters("myScheduleId",
    new BatchJobScheduleConfiguration()
        .setRecurrenceInterval(Duration.ofHours(6))
        .setDoNotRunUntil(OffsetDateTime.now().plusDays(1)),
    new BatchJobSpecification(new BatchPoolInfo().setPoolId("myPoolId"))
        .setPriority(50)),
    null);
```

### Get Job Schedule

```java
BatchJobSchedule schedule = batchClient.getJobSchedule("myScheduleId");
System.out.println("Schedule state: " + schedule.getState());
```

## Error Handling

```java
import com.azure.compute.batch.models.BatchErrorException;
import com.azure.compute.batch.models.BatchError;

try {
    batchClient.getPool("nonexistent-pool");
} catch (BatchErrorException e) {
    BatchError error = e.getValue();
    System.err.println("Error code: " + error.getCode());
    System.err.println("Message: " + error.getMessage().getValue());
    
    if ("PoolNotFound".equals(error.getCode())) {
        System.err.println("The specified pool does not exist.");
    }
}
```

## Best Practices

1. **Use Entra ID** — Preferred over shared key for authentication
2. **Use management SDK for pools** — `azure-resourcemanager-batch` supports managed identities
3. **Batch task creation** — Use `createTaskCollection` or `createTasks` for multiple tasks
4. **Handle LRO properly** — Pool resize, delete operations are long-running
5. **Monitor task counts** — Use `getJobTaskCounts` to track progress
6. **Set constraints** — Configure `maxWallClockTime` and `maxTaskRetryCount`
7. **Use low-priority nodes** — Cost savings for fault-tolerant workloads
8. **Enable autoscale** — Dynamically adjust pool size based on workload

## Reference Links

| Resource | URL |
|----------|-----|
| Maven Package | https://central.sonatype.com/artifact/com.azure/azure-compute-batch |
| GitHub | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/batch/azure-compute-batch |
| API Documentation | https://learn.microsoft.com/java/api/com.azure.compute.batch |
| Product Docs | https://learn.microsoft.com/azure/batch/ |
| REST API | https://learn.microsoft.com/rest/api/batchservice/ |
| Samples | https://github.com/azure/azure-batch-samples |
Source. Card written by iadujour.fr from: Frontmatter, sections and body of the deposit. Checked on 10 November 2026. microsoft/skills .

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