How to dynamic deploy for standalone Spring batch using Spring Cloud Task

Question

We are planning to retire the existing legacy java batch applications and recreate it with the latest available batch framework. Given that we have a large number of batch jobs to be modernised, we are looking for a framework or architecture that would allow us to

1. Develop a batch solution that would allow us to dynamically deploy a new batch as and when they are created, without disturbing the existing deployed applications. - Does Spring cloud Task provide any of this feature. Note: We are looking only to deploy the apps to our local server, and has nothing to do with cloud.
2. If Spring Batch/Boot can provide us the feature we typically expect from a batch application, what is the special value add to go for Spring Cloud Task? - I wasn't able to completely understand this from the Spring documentation available online.
3. From the documentation of the Spring Cloud Task, I was able to understand that it allows an application to have many tasks within it. What should I do if each of the tasks have their own library dependencies, which might contradict with the dependencies of other Tasks? So in that case, should each of these tasks moved to a new application or this there a work around for that?

Answer 1

To answer your questions:

1. Does Spring Cloud Task handle orchestration - No. Spring Cloud Task does not handle orchestration of tasks or jobs. The component in this ecosystem that handles the deployment/orchestration of tasks or jobs is really Spring Cloud Data Flow (which is why I asked if you use any type of cloud platform including YARN, Cloud Foundry, Kubernetes, or Mesos...the environments supported by Spring Cloud Data Flow).
2. What added value does Spring Cloud Task provide over Spring Boot/Spring Batch - Spring Cloud Task is designed to provide a few things:
   1. Similar abilities to Spring Batch with regards to state management without needing to create a batch job. When running a Boot application on a cloud environment, there is no standard way of getting the results from environment to environment (YARN handles job results differently from tasks on Cloud Foundry which is different from jobs on Kubernetes, etc). Spring Batch provides this but now all short lived processes need the overhead of the Batch API so Spring Cloud Task provides a lighter touch to those use cases.
   2. Automatically adds informational listeners. With Spring XD, when you ran a job in an XD container, the XD container automatically added a number of informational listeners that broadcast events that you could listen for. Spring Cloud Task brings the same functionality without the need for the XD container.
   3. Integration with Spring Cloud Stream. Spring Cloud Task provides the ability to launch tasks from messages received from Spring Cloud Stream. Also, the informational messages previously mentioned (both Batch events as well as Task events) are sent via Spring Cloud Stream channels.
   4. The DeployerPartitionHandler. When working in a cloud environment, this PartitionHandler implementation allows you to launch workers for a partitioned batch job as tasks. This allows for the dynamic scaling of partitioned batch jobs instead of the traditional option of pre-deploying workers that listen for work which wastes resources in a modern cloud environment.
3. How does the packaging of multiple tasks work with dependencies - In short, this is not recommended. The idea of a Spring Cloud Task is that the execution of the Spring Boot application is the Task. While you could package up multiple tasks and using different methods, have them execute based on different stimulus, that goes against the 12 factor application concepts which are essential for correct use of Spring Cloud Task.

My two cents
For the best option for a modern batch platform, you really need to look into some from of platform first and that begins at the Cloud Foundry/Kubernetes/Mesos/YARN layer. Without that, you end up building a large part of the infrastructure yourself. That is why Spring XD evolved into Spring Cloud Data Flow. The added complexity that lived in the containers of Spring XD is removed by requiring a modern platform to run on (since they all handle those guarantees themselves). Without that piece, you're going to spend a lot of time managing the deployment and orchestration of applications that most modern platforms handle for you.

From there, the choice becomes pretty easy IMHO with Spring Cloud Task for simple tasks, Spring Batch for batch jobs, and Spring Cloud Data Flow for orchestration.