IssueTracker

Hi,

Currently, the schedule_time field in Cloud Scheduler is marked as "output only", meaning it cannot be directly modified via the API or client libraries. This limitation creates challenges for dynamically managing job schedules, such as postponing or advancing the next job execution programmatically without disabling the entire job.

Request:

I request that the Cloud Scheduler API be enhanced to allow users to directly update the schedule_time of a job. This feature would enable greater flexibility and control in managing scheduled tasks, especially for cases where fine-tuning of job execution timing is critical.

Use Case:

• Dynamically delaying a job execution by a specific interval without pausing or rescheduling the entire job.
• Adjusting job schedules based on external events or conditions in real-time.

This feature would significantly enhance the flexibility of Cloud Scheduler and make it more suitable for dynamic scheduling scenarios.

Thank you for considering this request.

What you would like to accomplish: I would like to have the ability to directly modify the schedule_time field of a job in Cloud Scheduler via the API or client libraries. Currently, this field is marked as "output only," which prevents users from adjusting the next scheduled execution time of a job without rescheduling or pausing it. This enhancement would provide greater flexibility for dynamically managing scheduled tasks in real-time.

How this might work: This feature could be implemented by making the schedule_time field writable, allowing users to set a new execution time directly. The Cloud Scheduler API could expose a method that takes a timestamp as input and updates the schedule_time of the specified job to that timestamp. This method should also ensure that the new time respects the defined recurrence pattern or pause the recurrence pattern for one specific run. Additionally, the API should validate the input to avoid invalid configurations or conflicts.

If applicable, reasons why alternative solutions are not sufficient: Alternative solutions, such as pausing and re-enabling the job or creating a new job with a different schedule, introduce complexity and potential risks. They may result in missing executions or unintended scheduling gaps, especially in environments that rely on precise and timely job executions. The current workaround using PAUSED and ENABLED states can also be cumbersome and error-prone, especially in production environments.

Other information (workarounds you have tried, documentation consulted, etc): Workarounds that involve pausing the job and then re-enabling it after a delay have been attempted, but they do not provide a precise way to adjust the next execution time without impacting subsequent schedules. The official Cloud Scheduler documentation states that the schedule_time field is "output only," which confirms the current limitation.

A more streamlined and user-friendly approach to manage job schedules dynamically is highly desired by users who need more control over their scheduled tasks.