Let us first understand about the AWS Batch, before moving on to AWS Batch plug-in and how it is benefits to our workload automation users.

The AWS Batch is available on Automation Hub, download it to empower your Workload Automation environment.

AWS Batch

AWS Batch enables developers, scientists, and engineers to run hundreds of thousands of batch computing jobs easily and efficiently on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analysing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features.

Now let us see how easy it is to start and monitor AWS Batch job.

Create a new job and select “AWS Batch” in the Cloud section.

AWS Batch

Figure 1: Job Definition page


First, establish a connection to the AWS server by entering the required details.

Then, you can test the connection to AWS server by clicking on Test Connection.

AWS Batch

Figure 2: Connection page

AWS Batch

Figure 3: Connection page > Test Connection


After having successfully tested the connection, you can go to the Action tab and specify the details about the job queue and define what actions you want to perform.

  • Job Name: Specify the name of the job, it must be unique among the running jobs.
  • Job Queue: Jobs are submitted to a job queue where they reside until they can be scheduled to run in a compute environment. If you do not have any job queue, create one. You can choose job queue with scheduling priority or without scheduling priority.
  • Job Definition: It specifies how the jobs should run. You can create/use (if exist) single node job definition or multiple job definition. Select any one of the job definition.
  • Share identifier: Use any text as share identifier if you use only job queue with scheduling priority. Do not enter any text on share identifier field if you use job queue without scheduling priority.


AWS Batch

Figure 4: Action page

Job Configurations: 

VCPUs: Choose the number of vCPUs that your compute environment should launch with. As your job queue demand increases, AWS Batch can increase the desired number of vCPUs in your compute environment. The minimum vcpu you can use is 1.

Memory: Specify the memory hard limit (in MiB) present to the container.

GPUs: There are different types of GPU available, specify the GPUs value. This is an optional field.

AWS Batch

Figure 5: Action page > Job Configurations


User can use different commands for AWS batch to display in job logs for Ex:

User can write “echo” in first field

Click on + button

Then write any text like “Job Success”

This message should display in job logs after job success

Environment Variable:

AWS Batch automatically sets specific environment variables in container jobs. These environment variables provide introspection for the containers inside jobs, and you can use the values of these variables in the logic of your applications. All variables that are set by AWS Batch begin with the prefix, AWS_BATCH_.

For Ex:

Name: AWS_BATCH_JQ_NAME Value :Job queue name

AWS Batch

Figure 6: Action page > Environment


When you submit a job, you can specify parameters that should replace the placeholders or override the default job definition parameters. Parameters in job submission requests take precedence over the defaults in a job definition.

For Ex:

Name: command Value: [“abc” , “data”]

AWS Batch

Figure 7: Action page > Parameters

Submitting your job

Submit your job into the current plan. You can add your job to the job stream that automates your business process flow. Select the action menu in the top-left corner of the job definition panel and click on Submit Job into Current Plan. A confirmation message is displayed, and you can switch to the Monitoring view to see what is going on.

AWS Batch

Figure 8: Submitting job

Monitor Page:

AWS Batch


Figure 9: Monitor page

If Job is success in backend AWS Batch then status should be changed to successful.

AWS Batch

Figure 10: Monitor page contd.

You can cancel the running job by clicking kill option.

AWS Batch

Figure 11: Monitor page contd.

Job Log Details :

AWS Batch

AWS Batch

Figure 11: Job log


Comment wrap
Further Reading
Automation | September 28, 2022
See your scheduling metrics on Prometheus and Grafana
Recent versions of Workload Automation product are capable of seamless integrating with observability products such as Dynatrace, Instana, Datadog, Splunk and others. This is useful specially for companies that have large operations teams which are already monitoring applications on those observability solutions.
Automation | September 26, 2022
Easy Websphere’s Liberty Management for the Workload Automation Administrator
HWA main components (MDM / DWC) since version 9.5 are deployed on WebSphere liberty, which is a modern Java EE runtime that was designed to be highly efficient and optimized for modern cloud technologies.From an HWA administrator point of view, one of the main noticeable things after upgrading or installing 9.5 /10.1 is the missing WebSphere console, which helped HWA administrators that are not WebSphere experts on configuring WebSphere settings using the friendly UI.
Automation | September 8, 2022
CASE STUDY : Retail SuperMarket UseCases over Self Service Catalogue
In this Blog , we are looking at a Retail Outlet who provide home delivery of Orders by segregating Orders into Vans and segregating Vans into Waves where each Wave would comprise of Several Vans and each Van would comprise of several orders and how the Retail Outlet manages Order Cancellations , Van Closures etc on Stores front through Self Service Catalogue thereby avoiding direct interaction of Store Personnel with the Background DBs or the underlying APIs exposed by the Application.
Filters result by