En bref
Cette skill couvre le SDK Java Azure Batch. On s’en sert pour lancer des travaux parallèles ou HPC à grande échelle : pools, travaux, tâches et nœuds de calcul, typiquement avec un `BatchClient`. Le compte et l’endpoint se configurent notamment via `AZURE_BATCH_ENDPOINT` et `AZURE_BATCH_ACCOUNT` ; une clé d’accès n’est qu’un des chemins d’authentification possibles, à côté de `AZURE_TOKEN_CREDENTIALS`. Le langage de référence est Java.
Ce que ça fait
- Lancer des travaux parallèles ou HPC à grande échelle : pools, travaux, tâches et nœuds de calcul, typiquement avec un `BatchClient`.
- Le compte et l’endpoint se configurent notamment via `AZURE_BATCH_ENDPOINT` et `AZURE_BATCH_ACCOUNT` ; une clé d’accès n’est qu’un des chemins d’authentification possibles, à côté de `AZURE_TOKEN_CREDENTIALS`.
- Une skill voisine citée est `azure-resourcemanager-batch`.
- Les variables d’environnement typiques comprennent `AZURE_BATCH_ENDPOINT`, `AZURE_BATCH_ACCOUNT`, `AZURE_BATCH_ACCESS_KEY`, `AZURE_TOKEN_CREDENTIALS`.
- Les clients documentés comprennent `BatchClient`, `BatchClientBuilder`, `TokenCredential`, `DefaultAzureCredentialBuilder`, `ManagedIdentityCredentialBuilder`.
- L’authentification typique passe par `DefaultAzureCredential`.
Pour qui, et un exemple
Les développeurs Java qui soumettent des lots de calcul parallèle ou HPC sur Azure Batch, avec des pools et des tâches, plutôt qu’un simple job unique sur une machine.
Exemple de demande : « Crée un pool Batch et un travail de tâches parallèles en Java, en te branchant via AZURE_BATCH_ENDPOINT. »
On l’ouvre pour piloter des pools, travaux et tâches Azure Batch en Java, y compris un calcul HPC. Exemple rédigé par iadujour.fr à partir du SKILL.md, non testé.
Installer
npx skills add microsoft/skills (sélection de la skill dans l’assistant, README).
npx skills add microsoft/skillsFonctionne avec
- GitHub Copilot
- Copilot CLI
Source : README : exemples de « Copilot CLI » et « GitHub Copilot in VS Code » ; l’installation `npx skills add` envoie les fichiers vers le répertoire de l’agent choisi, sans liste exhaustive.
Niveau : Intermédiaire
Suppose un projet de l’éditeur et la maîtrise du SDK ou de la CLI correspondante.
À savoir
Extrait du SKILL.md
La description d’origine, celle que l’agent lit pour décider de charger la skill (en anglais) :
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".
Citée depuis le SKILL.md au commit e7ee58f . Le dossier contient aussi 1 fichier annexe (references/).
Le SKILL.md compte 384 lignes et 41 sections principales :
- 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
Vérifiée le 10 novembre 2026 sur : fichier LICENSE du dépôt . Licence déclarée dans le frontmatter : « MIT ». Titulaire : Copyright (c) Microsoft Corporation..
La licence autorise la reprise : le texte intégral du SKILL.md est reproduit ci-dessous, sans modification, avec sa mention de licence.
Texte intégral du SKILL.md
Reproduit sans modification depuis microsoft/skills (commit e7ee58f) , © Microsoft, sous licence MIT (fichier de licence d’origine ).
Afficher le SKILL.md original (384 lignes, en anglais)
---
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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