Introduction

In today's fast-paced digital landscape, businesses demand agility, scalability, and high performance from their software solutions. Workflow engines play a pivotal role in orchestrating tasks and automating processes, ensuring that everything runs smoothly. But when these processes become more complex and resource-intensive, how can workflow engines scale efficiently and stay responsive? The answer lies in threads. Examples of schemas using subprocesses in different workflows are described in detail in the official documentation of the Workflow Engine.

However, in this article, we will try to explain complex things in simple terms. We'll explore what threads are in the context of the Optimajet Workflow Engine and how they can dramatically enhance efficiency, enabling smoother execution and more responsive workflows.

What is Parallelism in Workflow Subprocesses?

In modern software systems, the need to optimize for both performance and resource efficiency has become a critical challenge. One of the most powerful techniques for achieving this is leveraging parallelism within subprocesses when building workflow schemas. By running multiple subprocesses concurrently, you can unlock higher performance and make full use of your hardware’s processing power. Optimizing workflows in this way can dramatically improve system efficiency, especially when dealing with complex workflows that involve multiple independent tasks. Parallelism refers to the ability to execute multiple independent or semi-independent subprocesses simultaneously.

In the context of workflow automation with Optimajet Workflow Engine, this means that different stages of a workflow can be run in parallel as Subprocesses, rather than waiting for each one to finish before starting the next. This improves efficiency, reduces execution time, and allows your workflows to handle more tasks concurrently.

What Are Threads in a Workflow Engine?

In simple terms, threads are independent sequences of execution within a larger process. In a multi-threaded environment, multiple tasks or operations can run simultaneously, each in its own thread. This allows for parallel processing, where multiple parts of a workflow can be executed at the same time rather than sequentially.

Within the Optimajet Workflow Engine, threads enable you to break down a workflow into parallel paths of execution. These paths can run independently or concurrently, meaning that tasks that don’t depend on each other can proceed without waiting for others to complete. This parallelism can significantly boost performance and efficiency, especially in complex workflows where multiple independent tasks need to be handled simultaneously.

Threads and Their Role in Parallelism

At the core of parallelism is the concept of threads. A thread is a lightweight unit of execution that can run code independently of other threads. In modern multi-core processors, threads allow you to take full advantage of the hardware by distributing work across different cores.

In the Optimajet Workflow Engine, subprocesses within a workflow can be split into multiple threads. However, unlike some systems that automatically handle thread allocation, Optimajet requires developers to configure thread distribution manually when designing the workflow schema. This gives developers full control over how tasks are distributed across threads, ensuring that workflows are tailored to specific use cases and hardware environments.

By using threads, developers gain several important benefits for efficiency, performance, and flexibility, which make thread-based parallelism an essential tool for optimizing workflows.

Benefits of Using Threads in Workflow Schemes

1. Parallelism and Efficiency

Benefit: Threads allow for the parallel execution of tasks that can be performed simultaneously, meaning that workflows can handle multiple operations at once.
Why Use It: If you have tasks that don’t depend on each other—like sending notifications while processing data—threads can significantly speed up the workflow by reducing idle or waiting time.

2. Better Resource Utilization

Benefit: Threads make better use of system resources, particularly in multi-core processors. Instead of running tasks sequentially on a single CPU core, threads can distribute tasks across multiple cores for more efficient processing.
Why Use It: For workflows handling large datasets, high-volume tasks, or I/O operations (like API calls or database queries), threads maximize throughput by fully utilizing your system’s computing power.

3. Concurrency and Responsiveness

Benefit: Threads allow workflows to continue processing while waiting for external events (e.g., user input, network responses). This keeps the workflow responsive instead of stalling.
Why Use It: In complex workflows involving long-running tasks, threads prevent bottlenecks by keeping the rest of the workflow active.

4. Asynchronous Processing

Benefit: Threads enable asynchronous execution, meaning tasks can be initiated and the workflow can move forward without waiting for them to complete, revisiting them once results are ready.
Why Use It: This is particularly useful when interacting with external services or databases. Instead of halting the workflow, other operations can proceed, making the entire process more efficient.

5. Scalability

Benefit: Threads help workflow engines scale by handling large numbers of simultaneous operations. This ensures that as workflows grow in complexity, they can split the workload across multiple threads and execute them concurrently.
Why Use It: For businesses with growing demands, thread-based parallelism ensures that workflows can handle larger volumes of tasks or users without degrading performance.

6. Load Balancing

Benefit: In distributed systems, threads can help balance the load by distributing tasks across multiple systems or servers, preventing any one system from being overloaded.
Why Use It: When scaling workflows to handle multiple users or requests, thread-based processing distributes tasks evenly, avoiding overloads in certain parts of the system.

7. Improved User Experience

Benefit: By performing background operations on separate threads, workflows can maintain a smoother, more responsive interface for users.
Why Use It: For workflows that involve user interaction (e.g., form submissions, approvals), threads allow background processing to occur without affecting the front-end experience.

8. Concurrency Control

Benefit: Workflow engines utilizing threads provide mechanisms to manage concurrent processes, ensuring that shared resources aren’t corrupted due to conflicting operations.
Why Use It: When multiple threads need to access or modify shared data, thread-based concurrency control ensures safe access, avoiding race conditions and data corruption.

How Optimajet Workflow Engine Manages Threads

Unlike some workflow engines that automatically distribute tasks across threads, the Optimajet Workflow Engine requires developers to manually configure thread assignment within the workflow schema for subprocesses.
Here’s how it works:

Manual Thread Assignment

In the Optimajet designer, developers define which subprocesses should run in parallel and manually specify how they will be distributed across threads. This allows for more control over the threading model, making it possible to tailor workflows based on specific system requirements and workloads.

Task Scheduling by Design

The manual assignment of threads ensures that developers have full control over the scheduling of parallel subprocesses. While this requires some upfront design, it allows for more optimized performance as each task can be carefully scheduled based on the system’s capabilities.

Practical Example

Imagine a workflow designed to process a customer order. This workflow may include subprocesses like validating the payment, checking inventory, generating shipping labels, and sending notifications to the customer. In a sequential workflow, each subprocess would run one after the other, increasing the time it takes to complete the order.

By using Optimajet’s parallelism and manually assigning threads:

• Payment validation runs on one thread.
• Simultaneously, inventory checking runs on another thread.
• While these are happening, shipping label generation and notification sending can run on other threads.

The result is a much faster order processing time, as independent tasks are executed in parallel, fully utilizing the CPU cores. In this scenario, the system is able to handle more orders per minute, improving throughput and customer satisfaction.

Conclusion

Parallelism in workflow subprocesses, combined with manual thread assignment in Optimajet Workflow Engine, unlocks the full potential of your hardware. By distributing tasks across multiple threads, you can maximize CPU utilization, reduce latency, and increase throughput. Optimajet’s support for manual threading ensures that developers have the flexibility to optimize workflows for specific use cases and hardware environments.

If your workflows are still running sequentially, it’s time to explore the power of parallelism. With Optimajet, you can build faster, more efficient workflows that scale effortlessly with your system’s needs.