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533 × Eureka!you want to see its contents?
cluster.routing.allocation.disk.watermark.low:
How did it come to this? I didn't configure anything, I'm using the trains AMI, with the suggested instance type
it will return a Config
object right?
the worst part of debugging this is waiting for the docker to install tensorflow each time over and over again 😞
I only have like 40 tasks including the example ones
It's kind of random, it works sometimes and sometimes it doesn't
Yes, I'll prepare something and send
I suspect that it has something to do with remote execution / local execution of pipelines, because we play with this , so sometimes the pipeline task itself executes on the client, and sometimes on the host (where the agent is also)
I don't htink I can, this is private IP and to create a dummy example of a pipeline and execution will take me more time than I can dedicate to this
I was here, but I can't find info for the questions I mentioned
In standard docker TimelyPenguin76 this quoting you mentioned is wrong, since the whole argument is being passed - hence the double tricky quotation I posted above
This is a part of a bigger process which times quite some time and resources, I hope I can try this soon if this will help get to the bottom of this
SuccessfulKoala55 this actually doesn't work
` apiserver_conf = ConfigFactory.parse_file(API_SERVER_CONF_PATH)
POINT 1
conf_content = HOCONConverter.to_hocon(config=ConfigFactory.from_dict(apiserver_conf.as_plain_ordered_dict()),
compact=False,
level=0, indent=2)
apiserver_conf['auth']['fixed_users']['users'].append(
ConfigFactory.from_dict({'username': username, 'password': password, 'name': name}))
##...
This error just keeps coming back... I already made the watermarks like 0.5gb