Parallel branching is a concept utilized in various workflow automation systems, including Logic Apps, to enhance the efficiency and flexibility of task execution. It involves splitting a workflow into multiple branches that can execute simultaneously rather than sequentially.
When tasks are executed in parallel branches, they do not wait for each other to complete before proceeding. Instead, they run concurrently, allowing for asynchronous execution. This means that while one branch is processing a task, another branch can simultaneously execute a different task. As a result, the overall execution of the logic app becomes asynchronous, providing faster processing times and improved efficiency, especially in scenarios involving independent tasks or actions.
Parallel execution lets workflows process independent tasks “at the same time“, which reduces overall processing time. This approach works especially well when tasks have no dependencies, such as calling multiple APIs or handling different data streams in parallel.
By using parallel branching, organizations can streamline workflows, improve productivity, and handle complex business processes more quickly and agilely.
📝 One-Minute Brief
Parallel branching in Azure Logic Apps allows workflows to execute multiple actions at the same time instead of sequentially. This Friday Fact explains how parallel branches enable asynchronous execution, helping reduce overall processing time and improve performance. When used correctly, this pattern makes Logic Apps more efficient and responsive in complex integration scenarios.
Let’s consider this straightforward example:
Here, we’ve got a Logic App set up to take in a CSV input structured like so:
Name Surname Age Country Profession
Luis Rigueira 34 Portugal Integration Developer
We use an Azure Function to convert the CSV into JSON (this exercise was implemented using Logic App Consumption), and after this, the branching logic begins. On one branch, we transform the output into a Base64‑encoded string. Then, after a deliberate 20‑second delay, we send that encoded payload to a queue.
At the same time, the other branch initializes a variable to extract the first and last name from the message. From there, it continues by sending the response.
After sending the request, we receive a response from the Logic App almost immediately.
Now, if you observe the logic app’s runs, you’ll see that due to the delay we’ve applied, the logic app continues to run.
However, one branch doesn’t need the other branch to complete to provide us a response.
Finally, the delayed branch ends its task.
You can apply this concept to many scenarios by integrating external services such as APIs and other actions.
By using parallel branching strategically, you can transform a Logic App from a synchronous workflow into an asynchronous one. Keep in mind that parallel branching enables asynchronous execution, which significantly enhances the overall capabilities and performance of your Logic App.
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