[Release] Fix cluster.yaml (#12589)

* Fix cluster.yaml

* Updated to use manylinux2014

release/long_running_tests/run.sh

@@ -62,5 +62,6 @@ pip install --upgrade pip
 pip install -U tensorflow==1.14
 pip install -q -U "$wheel" Click
 pip install -q "ray[all]" "gym[atari]"
-python "workloads/$workload.py"
+cd ..
+python "./workloads/$workload.py"
 

release/stress_tests/cluster.yaml

@@ -7,11 +7,11 @@ cluster_name: ray-stress-tests
 
 # The minimum number of workers nodes to launch in addition to the head
 # node. This number should be >= 0.
-min_workers: 105
+min_workers: 100
 
 # The maximum number of workers nodes to launch in addition to the head
 # node. This takes precedence over min_workers.
-max_workers: 105
+max_workers: 100
 
 # The autoscaler will scale up the cluster to this target fraction of resource
 # usage. For example, if a cluster of 10 nodes is 100% busy and
@@ -44,7 +44,7 @@ auth:
 # http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
 head_node:
     InstanceType: m4.16xlarge
-    ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04
+    ImageId: ami-042d0d6196f494652 # Custom ami
 
     # Set primary volume to 25 GiB
     BlockDeviceMappings:
@@ -60,7 +60,7 @@ head_node:
 # http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
 worker_nodes:
     InstanceType: m4.large
-    ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04
+    ImageId: ami-042d0d6196f494652 # Custom ami
 
     # Set primary volume to 25 GiB
     BlockDeviceMappings:
@@ -77,32 +77,19 @@ worker_nodes:
 
     # Additional options in the boto docs.
 
-# Files or directories to copy to the head and worker nodes. The format is a
-# dictionary from REMOTE_PATH: LOCAL_PATH, e.g.
-file_mounts: {
-#    "/path1/on/remote/machine": "/path1/on/local/machine",
-#    "/path2/on/remote/machine": "/path2/on/local/machine",
-}
-
 # List of shell commands to run to set up nodes.
-setup_commands: []
+setup_commands:
     # Uncomment these if you want to build ray from source.
     # - sudo apt-get -qq update
     # - sudo apt-get install -y build-essential curl unzip
-    # Install Anaconda.
-    - wget --quiet https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh || true
-    - bash Anaconda3-5.0.1-Linux-x86_64.sh -b -p $HOME/anaconda3 || true
-    - echo 'export PATH="$HOME/anaconda3/bin:$PATH"' >> ~/.bashrc
     # # Build Ray.
     # - git clone https://github.com/ray-project/ray || true
     # - ray/ci/travis/install-bazel.sh
-    - pip install -U pip 
-    - conda uninstall -y terminado || true
+    - pip install -U pip
     - pip install terminado
     - pip install boto3==1.4.8 cython==0.29.0
     # - cd ray/python; git checkout master; git pull; pip install -e . --verbose
-    - "pip install https://s3-us-west-2.amazonaws.com/ray-wheels/{{ray_branch}}/{{commit}}/ray-{{ray_version}}-cp36-cp36m-manylinux2014_x86_64.whl"
-
+    - "pip install https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-1.1.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: []
 

release/stress_tests/run.sh

@@ -38,20 +38,4 @@ echo "commit: $commit"
 echo "branch: $ray_branch"
 echo "workload: $workload"
 
-wheel="https://s3-us-west-2.amazonaws.com/ray-wheels/$ray_branch/$commit/ray-$ray_version-cp36-cp36m-manylinux2014_x86_64.whl"
-
-# Install Anaconda.
-wget --quiet https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh || true
-bash Anaconda3-5.0.1-Linux-x86_64.sh -b -p "$HOME/anaconda3" || true
-# shellcheck disable=SC2016
-echo 'export PATH="$HOME/anaconda3/bin:$PATH"' >> ~/.bashrc
-
-conda uninstall -y terminado
-source activate tensorflow_p36 && pip install -U pip
-source activate tensorflow_p36 && pip install -U "$wheel"
-
-pip install -U pip 
-conda uninstall -y terminado || true
-pip install terminado
-pip install boto3==1.4.8 cython==0.29.0
 python "workloads/$workload.py"