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/skillsWorks 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
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 |
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