azure-compute-batch-java

Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.

Quality

46%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/azure-compute-batch-java/SKILL.md

Azure Batch SDK for Java

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

Installation

<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

AZURE_BATCH_ENDPOINT=https://<account>.<region>.batch.azure.com
AZURE_BATCH_ACCOUNT=<account-name>
AZURE_BATCH_ACCESS_KEY=<account-key>

Client Creation

With Microsoft Entra ID (Recommended)

import com.azure.compute.batch.BatchClient;
import com.azure.compute.batch.BatchClientBuilder;
import com.azure.identity.DefaultAzureCredentialBuilder;

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

Async Client

import com.azure.compute.batch.BatchAsyncClient;

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

With Shared Key Credentials

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

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

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

List Pools

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

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

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

batchClient.enablePoolAutoScale("myPoolId", autoScaleParams);

Delete Pool

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

Job Operations

Create Job

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

Get Job

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

List Jobs

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

Get Task Counts

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

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

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

Task Operations

Create Single Task

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

Create Task with Exit Conditions

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)

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)

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

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

List Tasks

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

Get Task Output

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

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

Node Operations

List Nodes

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

Reboot Node

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

Get Remote Login Settings

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

Job Schedule Operations

Create Job Schedule

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

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

Error Handling

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

Use Entra ID — Preferred over shared key for authentication
Use management SDK for pools — azure-resourcemanager-batch supports managed identities
Batch task creation — Use createTaskCollection or createTasks for multiple tasks
Handle LRO properly — Pool resize, delete operations are long-running
Monitor task counts — Use getJobTaskCounts to track progress
Set constraints — Configure maxWallClockTime and maxTaskRetryCount
Use low-priority nodes — Cost savings for fault-tolerant workloads
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

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Repository: sickn33/antigravity-awesome-skills
Commit: 76cbde3

Last updated: 3 days ago
Created: 3 days ago

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.