Playbook Runs

as a turbine orchestrator, you can monitor the execution of playbooks within your organization by accessing the runs page in the operational health section this page provides valuable insights into the performance and success of your automated workflows overview the runs page displays a playbook runs history graph alongside a detailed run table this combination allows quick identification of execution trends and operational efficiency the graph shows overall playbook activity trends over time by default, it is collapsed; click the expand icon to open it the table lists individual playbook runs, grouped by playbook flow, with status indicators (green for success, red for failure) playbook runs overview on this page, a graph and table display showing you the playbooks that have run recently by default, the graph titled playbook runs history is collapsed click the > icon to expand and view it the table beneath the graph shows individual playbook run records, grouped by playbook flow for each entry, the following details are shown status execution result name unique identifier of the playbook flow start / end time timestamps showing when the run began and completed duration total run time in seconds and milliseconds trigger by subsystem or module that initiated the run trigger type mechanism that started the run a successful playbook run is indicated by a green dot, while a failed playbook run is indicated by a red dot you can click the expand arrow in the left column for more details about any run filtering playbook runs to help you efficiently locate specific playbook executions, the playbook runs interface includes multiple filtering options filter by date range – select a custom time period to view runs that occurred within a specific time window filter by playbook name – narrow results to run from a particular playbook filter by trigger type – choose between triggers such as playbook button, record create, record update or others to refine your view filter by status – view runs based on their outcome, such as successful or failed filter by date range feature the time range filter lets you narrow down playbook runs within a custom period using a date time picker in this example, the calendar allows selecting start and end dates—here, from july 14 to july 17, 2025, with precise time granularity down to the minute once the desired range is selected, clicking apply updates the results to display only the relevant runs within that timeframe filter by playbook feature the playbook filter enables you to narrow down the playbook run history based on specific playbook name by clicking the dropdown next to "playbook all," you can view a list of all available playbooks and select one or more to focus the results a built in search bar allows for quick lookup of playbook names, and a select all option is also provided for broader filtering this feature helps you easily isolate and monitor the execution history of individual or multiple playbooks within the defined timeframe filter by trigger type feature the trigger type filter allows you to refine playbook run results based on how the playbook was initiated from the dropdown menu "trigger type all," you can choose from various trigger methods such as flow event, playbook button, record create, record update, schedule , and more a select all option is available for broader views, and a search bar makes it easy to find specific trigger types this filtering capability is useful for analyzing runs triggered by specific actions, helping you troubleshoot or audit automation flows more effectively filter by status feature the status filter allows you to view playbook runs based on their execution outcome accessible through the "status all" dropdown, this filter provides options such as success, fail, and timeout, enabling you to quickly isolate specific run results you can also use the select all option or type in keywords to locate a desired status type key benefits of monitoring playbook runs track workflow efficiency analyze the success rate of playbook runs to ensure automation workflows are operating efficiently identify issues early quickly spot any failed playbook runs and investigate potential issues, preventing bottlenecks in your processes optimize performance use the run history to identify patterns and optimize playbooks that may be taking too long or failing under certain conditions expanding playbook run details clicking the expand arrow next to a specific playbook run provides a deeper insight into the run detailed execution logs error messages (if applicable) execution path and time taken for each step input/output data for the actions within the playbook by reviewing these details, you can troubleshoot issues, refine your playbook logic, and ensure smoother future runs tips for effective monitoring regular reviews frequently check the playbook runs page to stay updated on the performance and health of your workflows focus on patterns look for recurring issues or patterns in failed runs to proactively address potential problems utilize logs leverage detailed logs to understand the context of any issues and refine your playbooks accordingly