As automation usage grows more widespread, companies are building increasingly complex workflows with more points of failure. A survey by Automation Anywhere found that 76% of organizations experienced workflow failures from automation errors. Without vigilant error handling, these failures can grind your automations to a halt. According to research by WorkFusion, automations with no error handling see a failure rate over 60%, while automations with advanced error handling achieve failure rates under 5%.

Clearly, flawless automation requires proactive error handling. In this guide, we’ll explore’s robust error handling capabilities so you can build resilient workflows that power through problems. By mastering these techniques, you can achieve the automation reliability needed to scale your initiatives and realize the full benefits of automation.

Implement Fallback Scenarios

One key strategy for error handling in is to set up fallback scenarios using the Router module. The Router allows you to define conditional logic and branching paths to gracefully handle failures.

For example, you can set the main success route for normal operation, and then a fallback route to direct the workflow in case of errors. The fallback route might send notifications, trigger corrective actions, or activate an alternative process.

According to’s documentation, “A fallback route processes data that doesn’t fit the condition of all other routes. You can mark a route as a fallback if you want it to be executed last.” [1]

By anticipating potential failure points and mapping out fallback scenarios, you can ensure your automations have a robust response to errors. Make’s branching capabilities allow you to elegantly handle problems and keep things moving forward.

It’s a best practice to design your automations with error handling in mind from the start. Thinking through possible failure modes and defining fallback routes will lead to more resilient workflows.

Leverage the Error Handling Module provides a dedicated Error Handling module that allows you to catch and manage errors with ease. By connecting the Error Handler to critical junctures in your automation, you can log error details, send notifications to your team, or trigger corrective actions to get things back on track quickly.

The Error Handling module has built-in functionality to log errors, including the error message, stack trace, and other contextual data. You can configure it to write these error logs to a file, database, or analytics platform like Datadog for easy access and analysis. This helps you identify patterns and troubleshoot problems.

In addition, the Error Handler enables you to send alerts and trigger workflows in response to failures. You can use webhooks to post error notifications to team chat apps like Slack or Microsoft Teams. Or leverage Make’s integration with services like PagerDuty or OpsGenie to notify the right individuals and escalate issues. The Error Handler also allows you to kick off recovery workflows to automatically roll back changes, retry failed steps, or take other corrective actions.

By leveraging these capabilities of the Error Handling module, you can maintain visibility into errors and automatically respond to failures in your automations. As Make’s documentation states, “Don’t let errors slip through the cracks – put the Error Handler to work and maintain the integrity of your automations!”

Validate and Sanitize Your Inputs

Many automation errors arise from unexpected or malformed input data. Nip these issues in the bud by thoroughly validating and sanitizing the information entering your workflow. Use built-in tools like the Data Validator and Formatter modules to ensure your automations receive clean, consistent inputs that won’t cause downstream problems, thus preserving the quality of your data throughout the automation process.

For example, you can validate email addresses entered into a form using Make’s built-in regex validation to check for proper formatting. This avoids scenarios where invalid data gets passed deeper into your workflow and triggers cryptic errors later on. Likewise, standardizing phone numbers into a consistent format with the Formatter module right when they enter your system prevents subtle mismatches and parsing issues further down the line.

By thoroughly inspecting inputs early in your automations and normalizing them into the expected types and formats, you can eliminate a huge class of errors caused by faulty data. This proactive data hygiene approach pays dividends across your entire workflow, making your automation logic simpler and more resilient.

Implement Retry Logic

One of the most common causes of errors in automations is temporary failures from third-party APIs and services. Even the most stable APIs can experience occasional outages or latency spikes. Rather than letting these transient issues bring your automations to a halt, implement intelligent retry logic using Make’s built-in tools.

The Retry module in Make allows you to automatically re-attempt failed steps a configurable number of times. You can set increasing intervals between retries to gracefully back off in case an outage lasts more than a few seconds. By wrapping API calls and external service integrations in a Retry block, you can ride out most temporary glitches.

For example, if your workflow uses the Mailchimp API to add subscribers to a list, occasional timeouts or 500 errors are likely. By placing the API action in a Retry block set to re-attempt up to 5 times with increasing intervals, you can ensure the step succeeds even if the first few attempts fail.

Pro tip: Make sure to set reasonable limits on retries to avoid overloading APIs. And use the optional “Incomplete Executions” setting to process partially completed bundles while retrying failures.

With intelligent retry logic, your automations will become much more resilient to the inevitable API hiccups and transient service issues that occur. Limit disruptions and keep things flowing smoothly.

For more guidance, refer to Make’s documentation on implementing retry logic:

Monitor and Alert on Critical Errors

Despite your best error handling efforts, some issues warrant immediate attention from a human. Leverage’s integration with monitoring and alerting tools like PagerDuty and Slack to notify your team when critical errors occur. By setting up real-time alerts, you can swiftly respond to urgent problems and minimize the impact on your automated processes, keeping your operations running at peak performance.

Anticipate Failure Points

One key strategy in error handling is trying to anticipate potential failure points in your automation workflows. There are certain parts of workflows that tend to be more prone to errors or breaking, and it’s important to identify these areas upfront. For example, integrations with external APIs or services can often run into availability issues or unexpected response formats that disrupt workflows.

Additionally, any workflow steps involving complex logic, data transformations, or multiple branching paths can also introduce more opportunities for something to go wrong. Take time to think through each step of your automation and ask “what could go wrong here?” Brainstorming error scenarios in advance allows you to build in proactive measures to handle them gracefully.

As this community thread discusses, integrations with external forms and user inputs are common sources of errors: Is there a way to stop a scenario deactivating for an error on one execution?’s documentation also provides examples of common automation failure points like service availability issues and validation failures: Error processing.

By identifying parts of your workflows prone to breaking, you can focus your error handling efforts on the areas that need it most. Proactively anticipating errors will make your automations much more robust.

Debug Failed Automations

One of the most effective ways to handle errors in is to leverage the platform’s built-in debugging and logging tools to diagnose what went wrong. Make provides several powerful options to inspect your scenarios when things don’t go as planned:

The Make DevTool Chrome extension allows you to step through your scenario execution line by line to pinpoint failures. You can view variable values, inspect API responses, and gain visibility into each step of your workflow.

Make’s scenario debugger within the app gives you similar debugging capabilities without needing an external tool. Set breakpoints, watch variables, and analyze the logic flow to uncover bugs.

Robust logging and execution history within each scenario provides visibility into errors and exceptions. Inspect the logs to understand what went wrong during a failed run.

By leveraging these tools to methodically debug errors, you can diagnosis the root cause and iteratively improve your error handling approach. Proper logging enables you to learn from mistakes and build more resilient automations over time.

Handle Errors Gracefully

One of the keys to robust error handling is to fail gracefully – that is, handling errors in a way that avoids disruptive failures and maintains a positive user experience. When errors occur, the goal should be to handle them smoothly without derailing the entire application.

Graceful error handling involves catching errors early, at the lowest level possible, and preventing them from bubbling up and crashing the whole system. For example, validating user inputs and sanitizing data on the front-end helps catch problems before they reach your application logic. Wrapping risky code in try/catch blocks catches errors at the method level before they bubble up further.

It’s also important to maintain consistency in how errors are handled. Extract error handling logic into reusable modules, helper classes, or middleware so the same approach is applied consistently throughout your app. Hide the technical details from users and return friendly error messages they can understand.

Well-designed error handling should be as frictionless as possible for users. If a specific operation fails, retry it or provide an alternative experience. Gracefully degrade non-essential functionality if needed while keeping the core app running. The key is to anticipate problems and build in resilience up front, making failure points as smooth as possible.

For more on graceful error handling best practices, check out this helpful guide: Graceful Degradation: Handling Errors Without Disrupting User Experience

Document Error Scenarios

Cataloging common errors and their solutions in a knowledge base is a great way to refer back to fixes when similar issues crop up. Document things like:

  • The specific error message
  • What part of the automation the error occurred in
  • The conditions that led to the error
  • The ultimate root cause of the failure
  • The steps taken to resolve the problem

Having this information handy in a searchable knowledge base or wiki makes troubleshooting much faster when you encounter a familiar error. You don’t have to reinvent the wheel each time – just look up the error details and apply the proven solution. Some helpful practices include:

  • Log errors with detailed messages during testing to uncover scenarios.
  • Perform root cause analysis on errors to understand origins.
  • Document error details in a shared team resource.
  • Tag common error patterns for easy lookup.
  • Search documentation before asking for help.
  • Update existing errors with new solutions.

With a living document of known errors and fixes, you can tap into your team’s collective experience rather than repeating lessons already learned. This saves time, surfaces insights, and continually improves the knowledge available for troubleshooting automation errors.

Consider Error Cases Up Front

When designing automations, it’s critical to plan for potential errors upfront rather than waiting until they occur. As the old adage goes, “an ounce of prevention is worth a pound of cure.” By taking a proactive approach and considering error scenarios during the planning stages, you can build resilience into your workflows from the start.

During the design process, conduct a failure mode analysis to methodically evaluate everything that could go wrong at each step of the automation. Brainstorm error cases like invalid data formats, API failures, exceptions, timeouts, edge cases, and more. Catalog these potential issues and think through how your automation will handle them gracefully.

With these possible failure points in mind, implement preventative measures like input validation, sanity checks, retries, circuit breakers, and fallback logic. Set up error handling routines to catch expected errors and route to corrective steps. Document all of this so your automation has a built-in plan for when errors occur.

Building in contingency plans for errors up front is much easier than trying to retrofit error handling after the fact. Get ahead of problems by baking resilience into your initial design. As experts note, blending proactive and reactive error handling produces optimal results. So be proactive about considering errors in the planning stages, and you’ll build automations that can power through problems with ease.

Refine Error Handling Over Time

One of the best practices for error handling is to continuously refine and improve your strategies over time. When launching a new automation, it’s impossible to predict every potential error scenario upfront. As you run your workflows in production, new edge cases and exceptions will inevitably crop up.

Treat error handling as an iterative process. As problems occur, dig into the root cause, document the issue, and implement fixes to prevent it from happening again. Over time, you’ll build up an error handling playbook tailored to your specific environment and use cases.

For example, you may discover that malformed product IDs from your ecommerce platform are causing order import failures. You can update the workflow to sanitize inputs and add validation checks. This incremental improvement hardens your automation against that error in the future.

Regularly review error logs and metrics to identify patterns. Look for opportunities to generalize error handling logic you’ve created for specific cases. The more robust your error handling, the more resilient your automations will be.

According to Asana, the iterative process of “failing fast” and learning from mistakes leads to higher quality outcomes. Treat errors as feedback to fuel ongoing enhancement of your automations.[1]


Set Error Severity Levels

Classifying errors by severity level allows you to handle them appropriately based on their impact. enables you to designate errors as warnings or failures using conditional logic.

Warnings indicate non-critical issues that allow the workflow to continue, while failures halt the automation. For example, you may classify a timeout connecting to an API as a warning, but an authentication failure as a critical error.

You can configure the Error Handling module in to raise different severity levels. Critical failures can notify your team via Slack or PagerDuty, while warnings simply log the issue.

Setting severity levels provides flexibility in handling problems. Non-blocking warnings keep your workflow moving while urgent failures trigger alerts. Tuning severity over time helps optimize error handling.


By mastering advanced error handling techniques in, you can create resilient automations that power through problems with ease. In this guide, we covered several key strategies including:

  • Implementing fallback scenarios to route around failures
  • Leveraging the dedicated Error Handling module to catch and log issues
  • Validating and sanitizing inputs to prevent bad data from causing errors
  • Using retry logic to gracefully handle transient API and service outages
  • Setting up monitoring and alerts to get immediate notification of critical errors

With these robust practices in place, you can build automation workflows that are impervious to common pitfalls. Errors that would previously grind your processes to a halt can now be anticipated and overcome automatically. The result is more seamless, uninterrupted automation with less manual oversight needed.

By mastering advanced error handling on, you can operate your automations with confidence. Rather than living in fear of the next inevitable failure, your workflows will power through problems automatically. The benefit is more efficient processes, less downtime, and the ability to focus your energy on high-value tasks rather than being stuck in reactive mode. So embrace error handling as a critical automation skill – with robust strategies in place, you’ll be primed for automation success!

About the Author

Justin Adamski is an automation expert with over 10 years of experience creating advanced workflows on He is passionate about helping companies maximize efficiency through flawless automation processes. Justin offers integration and consulting services to implement robust, real-time solutions tailored to your business needs. Contact Justin to get started on leveraging to its fullest potential.

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