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Prepare release 3.0.0rc0
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docs/source/operators/deploy-distributed.md

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@@ -37,12 +37,12 @@ Entries in the remote hosts configuration should be fully qualified domain names
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All the kernel *specifications* configured to use the `DistributedProcessProxy` must be on all nodes to which there's a reference in the remote hosts configuration! With YARN cluster node, only the Python and R kernel _packages_ are required on each node, not the entire kernel specification.
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```
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The following installs the sample `python_distributed` kernel specification relative to the 3.0.0b0 release on the given node. This step must be repeated for each node and each kernel specification.
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The following installs the sample `python_distributed` kernel specification relative to the 3.0.0rc0 release on the given node. This step must be repeated for each node and each kernel specification.
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```Bash
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0b0/jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0rc0/jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz
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KERNELS_FOLDER=/usr/local/share/jupyter/kernels
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz --strip 1 --directory $KERNELS_FOLDER/python_distributed/ python_distributed/
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz --strip 1 --directory $KERNELS_FOLDER/python_distributed/ python_distributed/
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```
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```{tip}

docs/source/operators/deploy-yarn-cluster.md

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@@ -56,9 +56,9 @@ We recommend installing kernel specifications into a shared folder like `/usr/lo
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Considering we would like to enable the IPython kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_python_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list)
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```bash
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0b0/jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0rc0/jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz
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KERNELS_FOLDER=/usr/local/share/jupyter/kernels
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/
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```
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For more information about the IPython kernel, please visit the [IPython kernel](https://ipython.readthedocs.io/en/stable/) page.
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Considering we would like to enable the Scala Kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_scala_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list)
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```bash
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0b0/jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0rc0/jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz
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KERNELS_FOLDER=/usr/local/share/jupyter/kernels
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_cluster/ spark_scala_yarn_cluster/
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_cluster/ spark_scala_yarn_cluster/
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```
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For more information about the Scala kernel, please visit the [Apache Toree](https://toree.apache.org/) page.
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Considering we would like to enable the IRkernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_R_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list)
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```Bash
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0b0/jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz
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wget https://github.com/jupyter-server/enterprise_gateway/releases/download/v3.0.0rc0/jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz
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KERNELS_FOLDER=/usr/local/share/jupyter/kernels
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0b0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_cluster/ spark_R_yarn_cluster/
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tar -zxvf jupyter_enterprise_gateway_kernelspecs-3.0.0rc0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_cluster/ spark_R_yarn_cluster/
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```
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For more information about the iR kernel, please visit the [IRkernel](https://irkernel.github.io/) page.

etc/docker/docker-compose.yml

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# 3. We only use one replica since session affinity is another point of investigation in Swarm
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services:
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enterprise-gateway:
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image: elyra/enterprise-gateway:dev
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image: elyra/enterprise-gateway:3.0.0rc0
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user: root
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volumes:
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- "/var/run/docker.sock:/var/run/docker.sock"

etc/kubernetes/helm/enterprise-gateway/Chart.yaml

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# This is the chart version. This version number should be incremented each time you make changes
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# to the chart and its templates, including the app version.
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# Versions are expected to follow Semantic Versioning (https://semver.org/)
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version: 3.1.0-dev0-b0
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version: 3.0.0-rc0-dev0-b0
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# This is the version number of the application being deployed. This version number should be
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# incremented each time you make changes to the application. Versions are not expected to

etc/kubernetes/helm/enterprise-gateway/values.yaml

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# --set imagePullSecretsCreate.secrets[1].data="UHJvZCBTZWNyZXQgSW5mb3JtYXRpb24K"
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# Enterprise Gateway image name and tag to use.
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image: elyra/enterprise-gateway:dev
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image: elyra/enterprise-gateway:3.0.0rc0
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# Enterprise Gateway image pull policy.
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imagePullPolicy: IfNotPresent
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# K8s Enterprise Gateway Service
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create: false
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annotations: {}
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# Kernel Image Puller image name and tag to use.
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image: elyra/kernel-image-puller:dev
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image: elyra/kernel-image-puller:3.0.0rc0
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# Kernel Image Puller image pull policy.
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imagePullPolicy: IfNotPresent
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# Determines whether the Kernel Image Puller will pull kernel images it has previously pulled

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