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One of the AWS Data Scientists suggested this post to me about using the load balancer to monitor:- https://aws.amazon.com/blogs/machine-learning/machine-learning-on-distributed-dask-using-amazon-sagemaker-and-aws-fargate/
Ive tried this as well. The cloud formation template doesnt work either. I essentially need to get my python instance into a the same VPC that the dask fargate cluster is in, or conversely, to use a proxy server.
@jacobtomlinson if we already have a fargate cluster set up, how are we able to connect to it in this step
c = distributed.Client('tcp://{}:8786'.format(scheduler_public_ip))
following the above steps returns a timeout error
Hi @ks233ever and @adair-kovac
Any resolution of this Client timeout issue?
To reiterate
All current work is being done in dask-cloudprovider and things here are definitely not supported.
Yeah, an AWS issue there, had the same problem.