feat: 蓝鲸插件框架集成蓝鲸可编程网关调整 && 插件部署优化功能#117
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #117 +/- ##
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Coverage ? 90.97%
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Files ? 38
Lines ? 1330
Branches ? 0
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Hits ? 1210
Misses ? 120
Partials ? 0
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| port: 80 | ||
| - name: schedule | ||
| procCommand: celery worker -A blueapps.core.celery -P threads -n schedule_worker@%h -c 500 -Q plugin_schedule,plugin_callback,schedule_delete -l INFO | ||
| procCommand: celery worker -A blueapps.core.celery -P prefork -n schedule_worker@%h -c 50 -Q plugin_schedule,plugin_callback,schedule_delete -l INFO --max-tasks-per-child=1000 --time-limit=300 |
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这里为啥需要改成prefork模式,这个应该跟celery重启的问题没关系吧?
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这个应该我之前测试没cherry-pick 过来,已经更正
| procCommand: celery worker -A blueapps.core.celery -P prefork -n schedule_worker@%h -c 50 -Q plugin_schedule,plugin_callback,schedule_delete -l INFO --max-tasks-per-child=1000 --time-limit=300 | ||
| - name: beat | ||
| procCommand: celery beat -A blueapps.core.celery -l INFO | ||
| procCommand: celery beat -A blueapps.core.celery -l INFO --pidfile=/tmp/celerybeat.pid --schedule=/tmp/celerybeat-schedule |
| # while deploy app on staging env, it would sync to the stage=stag of the gateway | ||
| # while deploy app on production env, it would sync to the stage=prod of the gateway | ||
| BK_APIGW_STAGE_NAME = bkpaas_environment | ||
| BK_APIGW_STAGE_DESCRIPTION = "生产环境" if bkpaas_environment == "prod" else "预发布环境" |
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这里最好参考blueapps里的方式,把不同环境下同一个环境变量,用prod.py、stag.py的方式来动态引入
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