By default, if a job does not complete successfully (meaning that an
acknowledgement is not received from the handler, then it will be
retried with exponential backoff according to the settings in
RetryConfig.
Attributes
Name
Description
retry_count
int
The number of attempts that the system will make to run a
job using the exponential backoff procedure described by
max_doublings.
The default value of retry_count is zero.
If retry_count is 0, a job attempt will not be retried if it
fails. Instead the Cloud Scheduler system will wait for the
next scheduled execution time. Setting retry_count to 0 does
not prevent failed jobs from running according to schedule
after the failure.
If retry_count is set to a non-zero number then Cloud
Scheduler will retry failed attempts, using exponential
backoff, retry_count times, or until the next scheduled
execution time, whichever comes first.
Values greater than 5 and negative values are not allowed.
max_retry_duration
google.protobuf.duration_pb2.Duration
The time limit for retrying a failed job, measured from time
when an execution was first attempted. If specified with
retry_count,
the job will be retried until both limits are reached.
The default value for max_retry_duration is zero, which
means retry duration is unlimited.
min_backoff_duration
google.protobuf.duration_pb2.Duration
The minimum amount of time to wait before
retrying a job after it fails.
The default value of this field is 5 seconds.
max_backoff_duration
google.protobuf.duration_pb2.Duration
The maximum amount of time to wait before
retrying a job after it fails.
The default value of this field is 1 hour.
max_doublings
int
The time between retries will double max_doublings
times.
A job's retry interval starts at
min_backoff_duration,
then doubles max_doublings times, then increases
linearly, and finally retries at intervals of
max_backoff_duration
up to
retry_count
times.
For example, if
min_backoff_duration
is 10s,
max_backoff_duration
is 300s, and max_doublings is 3, then the job will first
be retried in 10s. The retry interval will double three
times, and then increase linearly by 2^3 \* 10s. Finally,
the job will retry at intervals of
max_backoff_duration
until the job has been attempted
retry_count
times. Thus, the requests will retry at 10s, 20s, 40s, 80s,
160s, 240s, 300s, 300s, ....
The default value of this field is 5.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[],[],null,["# Class RetryConfig (2.16.0)\n\nVersion latestkeyboard_arrow_down\n\n- [2.16.0 (latest)](/python/docs/reference/cloudscheduler/latest/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.15.1](/python/docs/reference/cloudscheduler/2.15.1/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.14.1](/python/docs/reference/cloudscheduler/2.14.1/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.13.5](/python/docs/reference/cloudscheduler/2.13.5/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.12.0](/python/docs/reference/cloudscheduler/2.12.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.11.3](/python/docs/reference/cloudscheduler/2.11.3/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.10.0](/python/docs/reference/cloudscheduler/2.10.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.9.1](/python/docs/reference/cloudscheduler/2.9.1/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.8.0](/python/docs/reference/cloudscheduler/2.8.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.7.3](/python/docs/reference/cloudscheduler/2.7.3/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.6.4](/python/docs/reference/cloudscheduler/2.6.4/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.5.1](/python/docs/reference/cloudscheduler/2.5.1/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.4.0](/python/docs/reference/cloudscheduler/2.4.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.3.4](/python/docs/reference/cloudscheduler/2.3.4/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.2.0](/python/docs/reference/cloudscheduler/2.2.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.1.1](/python/docs/reference/cloudscheduler/2.1.1/google.cloud.scheduler_v1.types.RetryConfig)\n- [2.0.0](/python/docs/reference/cloudscheduler/2.0.0/google.cloud.scheduler_v1.types.RetryConfig)\n- [1.3.2](/python/docs/reference/cloudscheduler/1.3.2/google.cloud.scheduler_v1.types.RetryConfig)\n- [1.2.1](/python/docs/reference/cloudscheduler/1.2.1/google.cloud.scheduler_v1.types.RetryConfig) \n\n RetryConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)\n\nSettings that determine the retry behavior.\n\nBy default, if a job does not complete successfully (meaning that an\nacknowledgement is not received from the handler, then it will be\nretried with exponential backoff according to the settings in\nRetryConfig."]]