Gearset's Flow error monitoring solution helps teams stay on top of Flow errors in their Salesforce orgs by providing real-time alerts and in-depth analysis. With automated tracking and notifications, you can quickly diagnose and resolve Flow errors, ensuring seamless business processes. To learn more about Gearset's Flow error monitoring capabilities, check out our Flow error monitoring solution page.
This quick start guide walks you through setting up Flow error monitoring jobs, configuring notifications, and leveraging filtering and reporting features to gain useful insights.
Creating your flow error monitoring job
From the main Gearset sidebar menu under Observability category, click on Flow error monitoring.
From the welcome screen, click on
Begin setup. Note: If you've already added a Flow monitoring job, you can create an additional job via theActionsbutton located in the top right of the screen.Choose the Salesforce org you want to monitor for flow errors.
Give a name for the monitoring job.
Click
Finish setup.
Important: we do not recommend monitoring Sandbox orgs. Once a Sandbox org is refreshed a new org id is created which will break the link between your Salesforce org and the Flow error monitoring job. This will cause the org to no longer be monitored for errors by Gearset.
Gearset will automatically configure the monitoring job for you. See our automated setup guide for more information on how this process works.
We recommend adding additional recipients to ensure that Apex Exception emails are still received.
During setup, you will be prompted to update the Apex Exception Email recipient to use the Gearset-generated email address if one is already not present. Both Flow and Apex error emails will be sent to the Gearset inbox.
Adding Slack and MS Teams notifications
Once a job has been created you can add Slack and MS Teams notifications to receive a channel alert when a Flow error occurs. See our adding Slack and MS Teams notifications documentation for step-by-step instructions.
Flow error results
Gearset will automatically begin to monitor the inbox for any flow error emails.
Timeline functionality
Gearset monitors and records Flow errors from the point of the job being created and first error being received. Errors are plotted for the selected time range enabling you to spot trends or spikes in Flow errors to investigate further.
Flows with errors can also be filtered by date range with a number of presets or choosing your own custom date range. You can click and drag over the time range for easier selection of a time frame you want to inspect in more detail.
Deployments you've performed with Gearset, either manually or via CI job runs, are also plotted on the timeline.
Free text filtering can search for any Flow name, element or error type within the results currently displayed in the selected time range. The timeline will update based on the search results.
Total Flow errors are plotted on the timeline or individually if filtering by Flow name is applied.
Flow error results
Errors are grouped by the Flow name which can be expanded to show the breakdown of error types and instance details.
First seen shows the first time a Flow error report received within the selected time range. Note: If the monitoring job was created after the selected time range it'll only display the first seen date since the job was created within that range.
Last seen shows the last time an error report was received in the selected time range with job creation date also taken into account when applicable.
Users displays the number of users who triggered the error (current user from the Flow interview).
Error count is the total number of times an error was received.
Expanding a Flow row shows a breakdown for that Flow of the different problem types and Flow elements with date, error count, users impacted metrics. Clicking on View errors provides access to the error reports for those errors. The numbers and percentages for errors are in relation to the Flow.
Creating notification rules
From the Error details page, click on Add notification rule. You can then add rules to match based on:
Content from the error notification content such as the Flow name, error type, and error content.
Threshold/volume based criterion such as the number of errors within a chosen timeframe.
Content or volume based rules can be used in combination or individually.
