async def startup_event():
logger.info(
"configuration dump",
dumped_config=config.dump_yaml(),
version=mlrun.utils.version.Version().get(),
)
loop = asyncio.get_running_loop()
# Using python 3.8 default instead of 3.7 one - max(1, os.cpu_count()) * 5 cause it's causing to high memory
# consumption - https://bugs.python.org/issue35279
# TODO: remove when moving to python 3.8
max_workers = config.httpdb.max_workers or min(32, os.cpu_count() + 4)
loop.set_default_executor(
concurrent.futures.ThreadPoolExecutor(max_workers=max_workers))
initialize_logs_dir()
initialize_db()
if config.httpdb.state == mlrun.api.schemas.APIStates.online:
await move_api_to_online()
async def _initialize_singletons():
initialize_logs_dir()
initialize_db()
initialize_project_member()
await initialize_scheduler()