Strategy that specifies how clients of Google Service Controller
want to send traffic to use different config versions. This is
generally used by API proxy to split traffic based on your
configured percentage for each config version.
One example of how to gradually rollout a new service configuration
using this strategy: Day 1
MutableMapping[str, float]
Maps service configuration IDs to their
corresponding traffic percentage. Key is the
service configuration ID, Value is the traffic
percentage which must be greater than 0.0 and
the sum must equal to 100.0.
[[["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 TrafficPercentStrategy (1.13.1)\n\nVersion latestkeyboard_arrow_down\n\n- [1.13.1 (latest)](/python/docs/reference/servicemanagement/latest/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.13.0](/python/docs/reference/servicemanagement/1.13.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.12.0](/python/docs/reference/servicemanagement/1.12.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.11.0](/python/docs/reference/servicemanagement/1.11.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.10.1](/python/docs/reference/servicemanagement/1.10.1/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.8.5](/python/docs/reference/servicemanagement/1.8.5/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.7.0](/python/docs/reference/servicemanagement/1.7.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.6.1](/python/docs/reference/servicemanagement/1.6.1/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.5.1](/python/docs/reference/servicemanagement/1.5.1/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.4.0](/python/docs/reference/servicemanagement/1.4.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.3.3](/python/docs/reference/servicemanagement/1.3.3/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.2.3](/python/docs/reference/servicemanagement/1.2.3/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.1.1](/python/docs/reference/servicemanagement/1.1.1/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [1.0.4](/python/docs/reference/servicemanagement/1.0.4/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy)\n- [0.1.0](/python/docs/reference/servicemanagement/0.1.0/google.cloud.servicemanagement_v1.types.Rollout.TrafficPercentStrategy) \n\n TrafficPercentStrategy(mapping=None, *, ignore_unknown_fields=False, **kwargs)\n\nStrategy that specifies how clients of Google Service Controller\nwant to send traffic to use different config versions. This is\ngenerally used by API proxy to split traffic based on your\nconfigured percentage for each config version.\n\nOne example of how to gradually rollout a new service configuration\nusing this strategy: Day 1\n\n:: \n\n Rollout {\n id: \"example.googleapis.com/rollout_20160206\"\n traffic_percent_strategy {\n percentages: {\n \"example.googleapis.com/20160201\": 70.00\n \"example.googleapis.com/20160206\": 30.00\n }\n }\n }\n\nDay 2\n\n:: \n\n Rollout {\n id: \"example.googleapis.com/rollout_20160207\"\n traffic_percent_strategy: {\n percentages: {\n \"example.googleapis.com/20160206\": 100.00\n }\n }\n }\n\nClasses\n-------\n\n### PercentagesEntry\n\n PercentagesEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)\n\nThe abstract base class for a message."]]