When to use Azure Logic Apps


Here, we'll discuss how you can decide whether Azure Logic Apps is the right choice for a workflow. We'll list some criteria that indicate whether Azure Logic Apps will meet your performance and functional goals.

Decision criteria

Azure Logic Apps helps you coordinate the flow of data through disparate systems. The cases where Azure Logic Apps might not be the best option typically involve real-time requirements, complex business rules, or use of non-standard services. Here's some discussion of each of these factors.

Factor Description
Integration The key question to ask when you're considering Azure Logic Apps is "do I need to integrate services?" Azure Logic Apps works well when you need to get multiple applications and systems to work together. That's what they were designed to do. If you're building an app with no external connections, Azure Logic Apps is probably not the best option.
Performance The next consideration is performance. The Azure Logic Apps execution engine scales your apps automatically. Azure Logic Apps can process large data-sets in parallel to let you achieve high throughput. However, they don't guarantee super-fast activation or enforce real-time constraints on execution time. If you're looking for low subsecond response time, then Azure Logic Apps may not be the best fit.
Conditionals Azure Logic Apps provides control constructs like Boolean expressions, switch statements, and loops so your apps can make decisions based on your data. You can build highly complex and deeply nested conditionals into your logic app workflows. There are two reasons you might prefer not to. First, it's often easier to write conditional logic in code rather than using the workflow designer. Second, embedded business rules aren't easily sharable with your other apps. Some people like including complex business rules directly in their logic app workflows. Others think it's simpler to write something like an Azure function to encapsulate the conditional logic and invoke that function from all their apps.
Connectors The last consideration is whether there are pre-built connectors for all the services you need to access. If so, then you're ready to go. If not, then you'll need to create a custom connector. If the service has an existing REST or SOAP API, you can make the custom connector in a few hours without writing any code. If not, then you'll need to create the API first before making the connector.

Apply the criteria

Azure Logic Apps works best when you're integrating multiple services with some added control logic. The decision is often a judgment call though. Let's think about how to apply these criteria to our example processes.

Our fictional shoe company needed to monitor social media, move old videos to archive storage, and sell shoes online. Our goal was to decide whether these tasks were good candidates for Logic Apps. To make our decision, we should analyze each task using the four criteria we developed: integration, performance, conditionals, and connectors. The following table summarizes the results. The highlighted cells are discussed below.

Integration Performance Conditionals Connectors Use Logic Apps?
Social-media monitor Integrates multiple services Doesn't need near-realtime low latency One simple conditional Built-in connectors available for all needed systems Yes
Video archive utility Only needs to access one service, cloud storage Doesn't need near-realtime low latency Two simple conditionals Built-in connectors available for all needed systems Yes
Direct online sales Integrates multiple services Doesn't need near-realtime low latency Multiple complex conditionals Multiple custom connectors needed Maybe

There are a few interesting things to think about in this analysis.

  • The video archive task is a good fit for Logic Apps even though it doesn't integrate multiple systems. Azure Logic Apps has a built-in timer trigger and an Azure blob connector that are perfect to implement this process.

  • The online sales process would likely include complex business logic. For example, we might have different approval processes based on the purchase amount or different shippers based on the destination. Azure Logic Apps can easily handle these conditions. It's up to us whether we want to embed these business rules in our app.

  • The online sales process would probably use a mix of built-in and custom connectors. We could use built-in connectors for email notifications and database access but would probably need a custom connector to talk to our payment processing service.

  • The performance of Azure Logic Apps will work well for all the tasks. Some of them may process large amounts of data, but Azure Logic Apps scales automatically to handle high throughput or spikes in demand. None of these tasks require low latency response time. We'd need to have near-realtime constraints for that to be an issue.

Azure Logic Apps could work for all of these tasks. The online sales process is the only one where we'd want to weigh all our options. Azure Logic Apps would be a good choice if we had the resources to build the custom connectors we'd need.

Guidance summary

The following flowchart summarizes the key questions to ask when you're considering using Azure Logic Apps.

Flowchart of the key questions to ask when evaluating Azure Logic Apps for your work.

A flowchart to help you decide if Azure Logic Apps is appropriate for your work. The flowchart summarizes the key questions to ask when evaluating Azure Logic Apps for your work. First, does your project involve integrating multiple systems? Second, do you need low latency? Third, does your process include complex logic. Fourth, are there connectors for all the systems you need to access.