我有一些"Python Shell“类型的胶水作业,我希望将作业日志发送到自定义CloudWatch日志组,而不是默认日志组。通过提供如下作业参数,我可以为"Spark“类型的胶水作业实现这一点:
"--enable-continuous-cloudwatch-log" = true
"--continuous-log-logGroup" = "/aws-glue/jobs/glue-job-1"但是相同的参数对Python Shell作业不起作用(日志仍然转到默认日志组/aws-glue/python-job/output和/aws-glue/python-job/error)。对于Python Shell作业,有什么方法可以做到这一点吗?
发布于 2020-07-10 16:21:44
continuous-log-logGroup是AWS Glue Spark作业附带的东西,它不适用于Python Shell作业。您可以做的最接近的事情是配置一个写入CloudWatch的日志处理程序。Watchtower是一个很流行的版本:
import watchtower, logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
logger.addHandler(watchtower.CloudWatchLogHandler(log_group='watchtower', stream_name='bla'))
logger.info("Hi")
logger.info(dict(foo="bar", details={}))您也可以直接使用Cloudwatch Logs API:
logs = boto3.client('logs')
LOG_GROUP='TUTORIAL-DEV2'
LOG_STREAM='stream1'
logs.create_log_group(logGroupName=LOG_GROUP)
logs.create_log_stream(logGroupName=LOG_GROUP, logStreamName=LOG_STREAM)
timestamp = int(round(time.time() * 1000))
response = logs.put_log_events(
logGroupName=LOG_GROUP,
logStreamName=LOG_STREAM,
logEvents=[
{
'timestamp': timestamp,
'message': time.strftime('%Y-%m-%d %H:%M:%S')+'\tHello world, here is our first log message!'
}
]
)这个例子出自下面的要点:https://gist.github.com/olegdulin/fd18906343d75142a487b9a9da9042e0
https://stackoverflow.com/questions/61625190
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