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May 5, 2023
Merged

Added guided demos to SDK repo #97

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3502f03
Added guided demos to SDK repo
Maxusmusti May 5, 2023
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Maxusmusti May 5, 2023
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205 changes: 205 additions & 0 deletions demo-notebooks/guided-demos/0_basic_ray.ipynb
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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"id": "8d4a42f6",
"metadata": {},
"source": [
"In this first notebook, we will go through the basics of using the SDK to:\n",
" - Spin up a Ray cluster with our desired resources\n",
" - View the status and specs of our Ray cluster\n",
" - Take down the Ray cluster when finished"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b55bc3ea-4ce3-49bf-bb1f-e209de8ca47a",
"metadata": {},
"outputs": [],
"source": [
"# Import pieces from codeflare-sdk\n",
"from codeflare_sdk.cluster.cluster import Cluster, ClusterConfiguration\n",
"from codeflare_sdk.cluster.auth import TokenAuthentication"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "614daa0c",
"metadata": {},
"outputs": [],
"source": [
"# Create authentication object for oc user permissions\n",
"auth = TokenAuthentication(\n",
" token = \"XXXXX\",\n",
" server = \"XXXXX\",\n",
" skip_tls=False\n",
")\n",
"auth.login()"
]
},
{
"cell_type": "markdown",
"id": "bc27f84c",
"metadata": {},
"source": [
"Here, we want to define our cluster by specifying the resources we require for our batch workload. Below, we define our cluster object (which generates a corresponding AppWrapper)."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0f4bc870-091f-4e11-9642-cba145710159",
"metadata": {},
"outputs": [],
"source": [
"# Create and configure our cluster object (and appwrapper)\n",
"cluster = Cluster(ClusterConfiguration(\n",
" name='raytest',\n",
" namespace='default',\n",
" min_worker=2,\n",
" max_worker=2,\n",
" min_cpus=1,\n",
" max_cpus=1,\n",
" min_memory=4,\n",
" max_memory=4,\n",
" gpu=0,\n",
" instascale=False\n",
"))"
]
},
{
"cell_type": "markdown",
"id": "12eef53c",
"metadata": {},
"source": [
"Next, we want to bring our cluster up, so we call the `up()` function below to submit our cluster AppWrapper yaml onto the MCAD queue, and begin the process of obtaining our resource cluster."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0884bbc-c224-4ca0-98a0-02dfa09c2200",
"metadata": {},
"outputs": [],
"source": [
"# Bring up the cluster\n",
"cluster.up()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "657ebdfb",
"metadata": {},
"source": [
"Now, we want to check on the status of our resource cluster, and wait until it is finally ready for use."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3c1b4311-2e61-44c9-8225-87c2db11363d",
"metadata": {},
"outputs": [],
"source": [
"cluster.status()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a99d5aff",
"metadata": {},
"outputs": [],
"source": [
"cluster.wait_ready()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "df71c1ed",
"metadata": {},
"outputs": [],
"source": [
"cluster.status()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "b3a55fe4",
"metadata": {},
"source": [
"Let's quickly verify that the specs of the cluster are as expected."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7fd45bc5-03c0-4ae5-9ec5-dd1c30f1a084",
"metadata": {},
"outputs": [],
"source": [
"cluster.details()"
]
},
{
"cell_type": "markdown",
"id": "5af8cd32",
"metadata": {},
"source": [
"Finally, we bring our resource cluster down and release/terminate the associated resources, bringing everything back to the way it was before our cluster was brought up."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5f36db0f-31f6-4373-9503-dc3c1c4c3f57",
"metadata": {},
"outputs": [],
"source": [
"cluster.down()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0d41b90e",
"metadata": {},
"outputs": [],
"source": [
"auth.logout()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
},
"vscode": {
"interpreter": {
"hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
178 changes: 178 additions & 0 deletions demo-notebooks/guided-demos/1_basic_instascale.ipynb
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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"id": "9865ee8c",
"metadata": {},
"source": [
"In this second notebook, we will go over the basics of using InstaScale to scale up/down necessary resources that are not currently available on your OpenShift Cluster (in cloud environments)."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b55bc3ea-4ce3-49bf-bb1f-e209de8ca47a",
"metadata": {},
"outputs": [],
"source": [
"# Import pieces from codeflare-sdk\n",
"from codeflare_sdk.cluster.cluster import Cluster, ClusterConfiguration\n",
"from codeflare_sdk.cluster.auth import TokenAuthentication"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "614daa0c",
"metadata": {},
"outputs": [],
"source": [
"# Create authentication object for oc user permissions\n",
"auth = TokenAuthentication(\n",
" token = \"XXXXX\",\n",
" server = \"XXXXX\",\n",
" skip_tls=False\n",
")\n",
"auth.login()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "bc27f84c",
"metadata": {},
"source": [
"This time, we are working in a cloud environment, and our OpenShift cluster does not have the resources needed for our desired workloads. We will use InstaScale to dynamically scale-up guaranteed resources based on our request (that will also automatically scale-down when we are finished working):"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0f4bc870-091f-4e11-9642-cba145710159",
"metadata": {},
"outputs": [],
"source": [
"# Create and configure our cluster object (and appwrapper)\n",
"cluster = Cluster(ClusterConfiguration(\n",
" name='instascaletest',\n",
" namespace='default',\n",
" min_worker=2,\n",
" max_worker=2,\n",
" min_cpus=2,\n",
" max_cpus=2,\n",
" min_memory=8,\n",
" max_memory=8,\n",
" gpu=1,\n",
" instascale=True, # InstaScale now enabled, will scale OCP cluster to guarantee resource request\n",
" machine_types=[\"m5.xlarge\", \"g4dn.xlarge\"] # Head, worker AWS machine types desired\n",
"))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "12eef53c",
"metadata": {},
"source": [
"Same as last time, we will bring the cluster up, wait for it to be ready, and confirm that the specs are as-requested:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0884bbc-c224-4ca0-98a0-02dfa09c2200",
"metadata": {},
"outputs": [],
"source": [
"# Bring up the cluster\n",
"cluster.up()\n",
"cluster.wait_ready()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "6abfe904",
"metadata": {},
"source": [
"While the resources are being scaled, we can also go into the console and take a look at the InstaScale logs, as well as the new machines/nodes spinning up.\n",
"\n",
"Once the cluster is ready, we can confirm the specs:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7fd45bc5-03c0-4ae5-9ec5-dd1c30f1a084",
"metadata": {},
"outputs": [],
"source": [
"cluster.details()"
]
},
{
"cell_type": "markdown",
"id": "5af8cd32",
"metadata": {},
"source": [
"Finally, we bring our resource cluster down and release/terminate the associated resources, bringing everything back to the way it was before our cluster was brought up."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5f36db0f-31f6-4373-9503-dc3c1c4c3f57",
"metadata": {},
"outputs": [],
"source": [
"cluster.down()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "c883caea",
"metadata": {},
"source": [
"Once again, we can look at the machines/nodes and see that everything has been successfully scaled down!"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0d41b90e",
"metadata": {},
"outputs": [],
"source": [
"auth.logout()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
},
"vscode": {
"interpreter": {
"hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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