What Are Concurrent Runs in Power Automate?
Definition and Core Concepts
Concurrent runs in Microsoft Power Automate give you the ability to execute several instances of a flow or multiple actions at the same time. Rather than handling tasks one after another, as is typical with sequential processing, you can use concurrent configurations to run processes in parallel, which helps cut down processing times and boosts overall workflow efficiency. This feature is especially valuable for businesses that need to automate high-volume, repetitive tasks and want to make the most out of their existing resources.
If you work in an enterprise setting, concurrent runs are a real game-changer. You can process thousands of records or transactions at once—think about bulk data updates, sending out mass notifications, or handling integrations that need to run in real time. By enabling parallel execution, Power Automate empowers organizations to expand their automation capabilities without getting stuck by the slowdowns that come with processing everything one step at a time. For many businesses, this is key to meeting tight service level agreements (SLAs) and staying compliant with industry standards around processing speed.
Default vs Configured Behavior
By default, most flows and actions in Power Automate run one after another. For instance, if you’re processing a list of items, each one gets handled in turn. But Power Automate also gives you the flexibility to adjust this with concurrency control—a set of settings that let you decide how many actions or instances can run in parallel. Tuning these settings can have a dramatic effect on how quickly your flows run and how responsive your automations feel.
That default, step-by-step approach is great when you need to keep things in order or when one action depends on the previous one. But if your tasks are independent, it’s worth considering enabling concurrency to really speed things up. The best part is you’re not locked in—Power Automate lets you fine-tune how your automations behave based on what makes sense for your business and the particular risks or requirements of each process.
Types of Concurrency (Trigger vs Action Level)
Power Automate handles concurrency at two main points: trigger-level and action-level.
- Trigger-level concurrency: Controls how many instances of a flow can start and run at the same time when new events come in. Especially helpful for high-traffic scenarios, like processing messages from a queue that might deliver several items at once.
- Action-level concurrency: Applies to “Apply to Each” loops, controlling how many items can be processed in parallel within a single run of the flow. Ideal for handling large data collections, such as updating dozens of SharePoint items or sending out notifications to a big list.
Knowing when and where to use each type makes all the difference in building flows that are both efficient and reliable.
How Concurrent Runs Work: Technical Overview
Trigger-Level Concurrency Control
With trigger-level concurrency, you can have multiple instances of a flow respond to incoming events at the same time. For example, if your flow is set off by new emails or data updates, enabling concurrency here means several of those events can be handled in parallel, not just one after the other in a queue. You control this by setting the degree of parallelism and the maximum number of waiting runs, making it possible to balance how much work gets done at once with your available resources and any API limits you might face.
If your organization handles lots of incoming events—like customer support tickets or IoT sensor data—you’ll see real benefits from turning up the parallelism at the trigger level. Just keep in mind that you’ll want to watch for service quotas or throttling limits set by connectors like Microsoft Graph API, SharePoint, or other SaaS systems, so you don’t get caught off guard.
Apply to Each Loop Concurrency
Within your flows, the “Apply to Each” action can also be configured for concurrency. Normally, items in a collection are processed in order, one by one. But if you enable concurrency, you can process several items at once, which can save you a ton of time on repetitive tasks like sending notifications, updating records, or making API calls. You get to decide how many items run in parallel, based on what your systems can handle and what your process really needs.
For example, maybe you need to update 500 customer records. If you set the parallelism degree to 25, you could cut processing time down from hours to just a few minutes. Of course, you’ll want to check if your connected data source is up for it—some systems just aren’t built for a lot of simultaneous operations.
Parallel Branch Execution
Power Automate also lets you build parallel branches—these are separate paths in your flow that run independently and at the same time. This is ideal when you have actions that don’t depend on each other and can happen in any order. By distributing the workload across multiple threads, you can make even complex workflows much more efficient.
A good example is onboarding a new employee. One branch might create accounts, another gets equipment ready, and a third sends out welcome emails. Since these steps don’t rely on each other, running them in parallel makes the whole process faster and gives new hires a smoother start.
Queue Management and Waiting Runs
Whenever the number of concurrent runs hits the maximum you’ve set, any extra events or action iterations get placed in a waiting queue. Settings like “maximum waiting runs” help you control how many pending tasks are allowed before new events start getting rejected or delayed. Getting this right is important, especially when your workload spikes—think end-of-month processing or busy seasons. By setting these thresholds according to your priorities, you make sure your most critical processes get handled first and your system doesn’t get overwhelmed.
Configuring Concurrent Runs: Step-by-Step Guide
Enabling Concurrency Control in Triggers
To get started with concurrency control at the trigger level:
- Go to your flow’s trigger settings.
- Find the concurrency control option and turn it on.
- Set the degree of parallelism based on how many events you expect and what your connected systems can handle.
For most businesses, it’s smart to start with a moderate setting and adjust as you see how things go.
Also, don’t forget to check the documentation for each connector you’re using. Some may have their own suggestions or restrictions when it comes to concurrency. And if your industry is regulated, it’s wise to consult your IT governance or compliance team to make sure your approach lines up with company policies.
Setting Up Apply to Each Concurrency
Inside an “Apply to Each” loop, you can enable concurrency by tweaking the settings:
- Decide how many parallel iterations you want, considering your data source’s capabilities and any risk of hitting outside system limits.
- For example, processing a big dataset with a parallelism degree of 10 or 20 can speed things up, but you’ll want to keep an eye on it and adjust as needed.
Testing with sample data before going live is a good idea, especially if you’re dealing with older systems that might not like simultaneous updates. If you’re working with Microsoft Dataverse or SQL Server, you might need to adjust isolation levels or use row-level locking to keep your data safe when concurrency is on.
Creating Parallel Branches
To build parallel branches:
- Set up your flow with multiple action paths that branch off from a single trigger or condition.
- Each branch runs at the same time, so unrelated tasks don’t have to wait for one another.
This is perfect for flows that need to make several API calls or send out notifications that don’t depend on each other.
When you’re designing these branches, use clear names and document your steps so anyone on your team can follow along. For more complex automations, grouping related steps with Scope actions can make error handling and monitoring a lot easier.
Adjusting Degree of Parallelism Settings
Fine-tuning your degree of parallelism is key to getting the best performance:
- Start low, watch how your system responds, and slowly increase until you find the sweet spot between speed and reliability.
- Higher settings let you run more tasks at once, but too high can lead to resource conflicts or API throttling.
Some organizations make use of monitoring tools like Azure Monitor or Power Platform Analytics to keep track of how different parallelism settings impact performance over time. This kind of data-driven approach helps you keep improving and avoid surprises down the line.
Our power platform consulting services are designed to optimize your workflow automation by harnessing the full potential of concurrent runs in Power Automate. By engaging with our experts, you can tailor concurrency settings to match the specific demands of your business, ensuring that automation delivers maximum efficiency and rapid processing, all while maintaining data integrity and compliance.
Performance Benefits and Use Cases
Speed Improvements with Real Examples
When you enable concurrent runs, you can seriously cut down processing times. For example, handling 100 items one by one might take several minutes, but with a parallelism degree of 20, you could finish in under a minute. This kind of improvement really stands out in flows that handle bulk data updates, notifications, or lots of external API calls.
A real-world scenario: a retail business automates daily inventory updates from multiple stores. When they processed everything sequentially, it took over an hour. After they enabled concurrency and set the degree to 25, they got the job done in less than ten minutes, which means they could react to changes almost instantly.
Best Scenarios for Concurrent Processing
Concurrent runs shine when your tasks are independent and safe to run in parallel, such as:
- Sending out batch emails
- Updating a bunch of database records
- Processing customer requests
- Syncing data across different systems
It’s also a great fit for cloud-based integrations, like moving large amounts of data to Microsoft SharePoint Online or managing real-time responses to IoT devices. In these cases, using concurrency can make a huge difference in how quickly you see results.
Industry-Specific Applications
Different industries use concurrent runs in their own ways:
- Finance: Process thousands of transactions at once.
- Marketing: Send out mass communications efficiently.
- Supply Chain: Update inventories and track shipments in real time.
- Healthcare: Process patient records or insurance claims in parallel.
- Manufacturing: Support real-time quality checks or equipment monitoring.
Each situation calls for a careful balance between speed, system limitations, and data integrity.
ROI and Efficiency Gains
Using concurrent runs can deliver a strong return on investment by slashing manual work, reducing processing delays, and making real-time automation possible. Many organizations see efficiency gains of 70% or more on high-volume workflows once they dial in their concurrency settings.
These improvements can mean real savings, happier customers, and better compliance with service agreements. For example, a logistics company might automate shipment notifications for thousands of customers each day, cutting labor costs and giving everyone clearer updates.
Limitations and Considerations
API Rate Limiting and Throttling
A lot of external systems and APIs limit how many requests you can send in a certain time. If you set your concurrency too high, you could blow past those limits and get throttling errors, failed actions, or slower processing. It’s important to know the rules for each connected service so you can avoid surprises.
Microsoft offers detailed documentation on connector limits, and some platforms like Salesforce or Dynamics 365 have their own quotas or burst limits. Going over these can temporarily suspend your access or slow things down, so it’s smart to build in checks or alerts for throttling events.
When NOT to Use Concurrent Runs
There are times when concurrency just isn’t the right fit:
- If your workflow needs to stay in a strict order
- If each action depends on the one before
This is true for processes like financial reconciliations or multi-step approvals, where skipping ahead could cause errors or compliance problems.
Data Integrity Concerns
Running actions in parallel can sometimes lead to data consistency issues, especially if multiple steps try to update the same records at the same time. It’s important to figure out which parts of your workflow are safe for concurrency and which should stay sequential to keep your data accurate and your business compliant.
Some businesses use data locking or unique IDs to avoid conflicts. In regulated industries—like healthcare or finance—you might also need extra audit logs or validation steps to meet standards like HIPAA or SOX.
Resource Management Challenges
Turning up the parallelism can put a strain on your resources, including memory, CPU, and network bandwidth. If you push things too far, you might see slower performance, timeouts, or unexpected errors. Keeping an eye on your system and planning ahead is crucial for stable operations.
Larger organizations often rely on tools like Azure Resource Manager or Power Platform admin analytics to monitor resource use and plan for the future. This helps prevent outages and supports smooth scaling as your automation grows.
Best Practices for Implementation
Starting with Conservative Settings
- Start small—use low parallelism values and increase them as you see what works.
- Document your changes and keep version control on your flows.
That way, if anything goes wrong after increasing parallelism, you can easily roll things back.
Testing and Optimization Strategies
- Always test your flows in a safe environment before rolling out concurrency settings in production.
- Monitor performance, resource usage, and error rates to find the best configuration for your needs.
- Simulate peak loads and use automated monitoring to spot bottlenecks or error patterns.
- Review and adjust your settings regularly as your business evolves.
Error Handling in Concurrent Scenarios
- Build flows that log errors, alert admins, and recover smoothly from temporary issues.
- Use Scope actions with run-after conditions to isolate errors in parallel branches.
- Implement custom logging for detailed troubleshooting.
- For critical flows, integrate with incident management tools like ServiceNow or PagerDuty.
Monitoring and Analytics
Leverage Power Automate’s monitoring and analytics dashboards to track your flows, spot bottlenecks, and see how concurrency changes are affecting performance. Regular reviews help ensure you’re getting the benefits of parallel execution without introducing new issues.
If you need deeper insights, Power Platform Center of Excellence and Azure Log Analytics can offer cross-platform visibility and help you keep everything running smoothly.
Troubleshooting Common Issues
Concurrent Call Limits Exceeded
If you hit errors for exceeding concurrent call limits:
- Lower your parallelism or stagger when flows start.
- Check the API documentation for specific restrictions and adjust your configuration as needed.
- Use tools like exponential backoff or queuing to stay within limits.
Performance Degradation Issues
If things start slowing down unexpectedly:
- Monitor system health.
- Tweak your concurrency settings.
- Break big workflows into smaller, more manageable pieces.
- Offload heavy computation to Azure Functions or spread work across multiple flows.
Data Consistency Problems
When parallel actions update the same records:
- Put checks in place to avoid conflicts.
- Redesign workflows so that important steps stay sequential.
- Use optimistic concurrency control or transactional processing for consistency, especially with databases or ERP systems.
Recovery and Rollback Strategies
Be prepared for partial failures by building rollback or compensation actions into your flows. This way, you can recover from errors without leaving your data or business processes in a messy state.
For example, if something fails halfway through a batch update, set up logic to reverse completed actions or flag records for review. Having clear rollback procedures is essential for compliance and audits.
Advanced Configuration Techniques
Dynamic Concurrency Adjustment
Sometimes, you’ll want to adjust concurrency settings on the fly based on system load, API response times, or business priorities. While this isn’t built into Power Automate by default, you can set it up with custom logic and monitoring.
Flows can check on system health or queue depth and adjust parallelism using environment variables or config files. This approach is especially useful in large enterprises or regulated industries where stability is a top priority.
Nested Concurrency Scenarios
Some workflows call for concurrency inside concurrency—like nested loops or multiple layers of parallel execution. It takes careful planning to manage resources and errors across all those levels.
For example, if you’re processing multiple customer orders, each with several line items, enabling concurrency at both levels can maximize throughput. Just make sure you’re monitoring closely to avoid running out of resources.
Custom Monitoring Solutions
For deeper insights, consider building custom dashboards or integrating third-party monitoring tools. Enhanced logging and analytics can help you spot issues before they become problems and keep your automations healthy.
Solutions like Power BI dashboards or Splunk integrations can give you a visual on flow performance, error rates, and resource use, making it easier to make smart, data-driven decisions.
Integration with External Systems
To get the most out of concurrent runs, you might need to coordinate Power Automate with other automation platforms. Integrating with tools like Azure Logic Apps, Service Bus, or enterprise schedulers lets you manage complex, multi-system workflows while keeping control over concurrency and resources.
This kind of setup is ideal for hybrid cloud strategies and ensures your automation stays aligned with your organization’s IT policies. It helps maintain both performance and compliance as your business and technology landscape evolve.
