HW/HW10/Week_10-Kubernetes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Homework\n",
    "\n",
    "In this homework, we'll deploy Credit Card prediction model from the homework 5.\n",
    "We already have a docker image for this model - we'll use it for \n",
    "deploying the model to Kubernetes.\n",
    "\n",
    "\n",
    "## Building the image\n",
    "\n",
    "Clone the course repo if you haven't:\n",
    "\n",
    "```\n",
    "git clone https://github.com/alexeygrigorev/mlbookcamp-code.git\n",
    "```\n",
    "\n",
    "Go to the `course-zoomcamp/cohorts/2022/05-deployment/homework` folder and \n",
    "execute the following:\n",
    "\n",
    "\n",
    "```bash\n",
    "docker build -t zoomcamp-model:v001 .\n",
    "```\n",
    "\n",
    "> **Note:** If you have troubles building the image, you can \n",
    "> use the image we built and published to docker hub:\n",
    "> `svizor42/zoomcamp-model:v001 `\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "v001: Pulling from svizor42/zoomcamp-model\n",
      "\n",
      "\u001b[1Ba5fb9032: Pulling fs layer \n",
      "\u001b[1B81b69b9a: Pulling fs layer \n",
      "\u001b[1Ba0a62ab5: Pulling fs layer \n",
      "\u001b[1B28511179: Pulling fs layer \n",
      "\u001b[1B79bc1c47: Pulling fs layer \n",
      "\u001b[1Bc3f7336a: Pulling fs layer \n",
      "\u001b[1B56631b9d: Pulling fs layer \n",
      "\u001b[1Bf65bff9f: Pulling fs layer \n",
      "\u001b[3B56631b9d: Waiting fs layer \n",
      "\u001b[1B8ef822c9: Pulling fs layer \n",
      "\u001b[1BDigest: 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      "Status: Downloaded newer image for svizor42/zoomcamp-model:v001\n",
      "docker.io/svizor42/zoomcamp-model:v001\n"
     ]
    }
   ],
   "source": [
    "!docker pull svizor42/zoomcamp-model:v001 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "REPOSITORY                                                                         TAG       IMAGE ID       CREATED      SIZE\n",
      "221112323543.dkr.ecr.ap-northeast-1.amazonaws.com/memoona-dino-or-dragon-private   latest    db9c145fd096   5 days ago   735MB\n",
      "dino-vs-dragon-v2                                                                  latest    db9c145fd096   5 days ago   735MB\n",
      "svizor42/zoomcamp-model                                                            v001      951a2ef903b8   9 days ago   544MB\n"
     ]
    }
   ],
   "source": [
    "!docker images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 1\n",
    "\n",
    "Run it to test that it's working locally:\n",
    "\n",
    "```bash\n",
    "docker run -it --rm -p 9696:9696 zoomcamp-model:v001\n",
    "```\n",
    "\n",
    "And in another terminal, execute `q6_test.py` file:\n",
    "\n",
    "```bash\n",
    "python q6_test.py\n",
    "```\n",
    "\n",
    "You should see this:\n",
    "\n",
    "```\n",
    "{'get_card': True, 'get_card_probability': <value>}\n",
    "```\n",
    "\n",
    "Here `<value>` is the probability of getting a credit card. You need to choose the right one.\n",
    "\n",
    "* 0.289\n",
    "* 0.502\n",
    "* 0.769\n",
    "* 0.972\n",
    "\n",
    "Now you can stop the container running in Docker.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'get_card': False, 'get_card_probability': 0.21312682711608702}\n"
     ]
    }
   ],
   "source": [
    "!python q6_test.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installing `kubectl` and `kind`\n",
    "\n",
    "You need to install:\n",
    "\n",
    "* `kubectl` - https://kubernetes.io/docs/tasks/tools/ (you might already have it - check before installing)\n",
    "* `kind` - https://kind.sigs.k8s.io/docs/user/quick-start/\n",
    "\n",
    "(used install using apt for kubectl, and install from repo for kind)\n",
    "\n",
    "## Question 2\n",
    "\n",
    "What's the version of `kind` that you have? \n",
    "\n",
    "Use `kind --version` to find out.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kind version 0.17.0\n"
     ]
    }
   ],
   "source": [
    "!kind --version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a cluster\n",
    "\n",
    "Now let's create a cluster with `kind`:\n",
    "\n",
    "```bash\n",
    "kind create cluster\n",
    "```\n",
    "\n",
    "And check with `kubectl` that it was successfully created:\n",
    "\n",
    "```bash\n",
    "kubectl cluster-info\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0;32mKubernetes control plane\u001b[0m is running at \u001b[0;33mhttps://127.0.0.1:39879\u001b[0m\n",
      "\u001b[0;32mCoreDNS\u001b[0m is running at \u001b[0;33mhttps://127.0.0.1:39879/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy\u001b[0m\n",
      "\n",
      "To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.\n"
     ]
    }
   ],
   "source": [
    "!kubectl cluster-info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 3\n",
    "\n",
    "What's the smallest deployable computing unit that we can create and manage \n",
    "in Kubernetes (`kind` in our case)?\n",
    "\n",
    "* Node\n",
    "* Pod\n",
    "* Deployment\n",
    "* Service"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer: Pod**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 4\n",
    "\n",
    "Now let's test if everything works. Use `kubectl` to get the list of running services.\n",
    "\n",
    "What's the `Type` of the service that is already running there?\n",
    "\n",
    "* ClusterIP\n",
    "* NodePort\n",
    "* LoadBalancer\n",
    "* ExternalName\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME         TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)   AGE\n",
      "kubernetes   ClusterIP   10.96.0.1    <none>        443/TCP   4m55s\n"
     ]
    }
   ],
   "source": [
    "!kubectl get services"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer is: The service already running is ClusterIP**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 5\n",
    "\n",
    "To be able to use the docker image we previously created (`zoomcamp-model:v001`),\n",
    "we need to register it with `kind`.\n",
    "\n",
    "What's the command we need to run for that?\n",
    "\n",
    "* `kind create cluster`\n",
    "* `kind build node-image`\n",
    "* `kind load docker-image`\n",
    "* `kubectl apply`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Image: \"\" with ID \"sha256:951a2ef903b849d0ed069942d05aa2edd5e50cb7f91ceb9a7301068d0910a18c\" not yet present on node \"kind-control-plane\", loading...\n"
     ]
    }
   ],
   "source": [
    "!kind load docker-image svizor42/zoomcamp-model:v001\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer: kind load docker-image**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 6\n",
    "\n",
    "Now let's create a deployment config (e.g. `deployment.yaml`):\n",
    "\n",
    "```yaml\n",
    "apiVersion: apps/v1\n",
    "kind: Deployment\n",
    "metadata:\n",
    "  name: credit-card\n",
    "spec:\n",
    "  selector:\n",
    "    matchLabels:\n",
    "      app: credit-card\n",
    "  replicas: 1\n",
    "  template:\n",
    "    metadata:\n",
    "      labels:\n",
    "        app: credit-card\n",
    "    spec:\n",
    "      containers:\n",
    "      - name: credit-card\n",
    "        image: <Image>\n",
    "        resources:\n",
    "          requests:\n",
    "            memory: \"64Mi\"\n",
    "            cpu: \"100m\"            \n",
    "          limits:\n",
    "            memory: <Memory>\n",
    "            cpu: <CPU>\n",
    "        ports:\n",
    "        - containerPort: <Port>\n",
    "```\n",
    "\n",
    "Replace `<Image>`, `<Memory>`, `<CPU>`, `<Port>` with the correct values.\n",
    "\n",
    "What is the value for `<Port>`?\n",
    "\n",
    "\n",
    "Apply this deployment using the appropriate command and get a list of running Pods. \n",
    "You can see one running Pod."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "image: svizor42/zoomcamp-model:v001\n",
    "        resources:\n",
    "          requests:\n",
    "            memory: \"64Mi\"\n",
    "            cpu: \"100m\"            \n",
    "          limits:\n",
    "            memory: \"128Mi\"\n",
    "            cpu: \"500m\"\n",
    "         ports:\n",
    "        - containerPort: 9696\n",
    "```\n",
    "\n",
    "**Answer: The value for port is 9696**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deployment.apps/credit-card created\n"
     ]
    }
   ],
   "source": [
    "# !kubectl get pods --all-namespaces\n",
    "!kubectl apply -f deployment.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME          READY   UP-TO-DATE   AVAILABLE   AGE\n",
      "credit-card   1/1     1            1           22s\n"
     ]
    }
   ],
   "source": [
    "!kubectl get deployment"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yes there is one running pod as expected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME                           READY   STATUS    RESTARTS   AGE\n",
      "credit-card-56b8f7f4d8-qffv8   1/1     Running   0          2m35s\n"
     ]
    }
   ],
   "source": [
    "!kubectl get pod"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 7\n",
    "\n",
    "Let's create a service for this deployment (`service.yaml`):\n",
    "\n",
    "```yaml\n",
    "apiVersion: v1\n",
    "kind: Service\n",
    "metadata:\n",
    "  name: <Service name>\n",
    "spec:\n",
    "  type: LoadBalancer\n",
    "  selector:\n",
    "    app: <???>\n",
    "  ports:\n",
    "  - port: 80\n",
    "    targetPort: <PORT>\n",
    "```\n",
    "\n",
    "Fill it in. What do we need to write instead of `<???>`?\n",
    "\n",
    "**Answer: credit-card**\n",
    "\n",
    "Apply this config file."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "my service.yaml:\n",
    "\n",
    "```\n",
    "apiVersion: v1\n",
    "kind: Service\n",
    "metadata:\n",
    "  name: credit-card\n",
    "spec:\n",
    "  type: LoadBalancer\n",
    "  selector:\n",
    "    app: credit-card\n",
    "  ports:\n",
    "  - port: 80\n",
    "  targetPort: 9696\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "service/credit-card created\n"
     ]
    }
   ],
   "source": [
    "!kubectl apply -f service.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME          TYPE           CLUSTER-IP     EXTERNAL-IP   PORT(S)        AGE\n",
      "credit-card   LoadBalancer   10.96.15.137   <pending>     80:31883/TCP   25s\n",
      "kubernetes    ClusterIP      10.96.0.1      <none>        443/TCP        144m\n"
     ]
    }
   ],
   "source": [
    "!kubectl get service"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the service\n",
    "\n",
    "We can test our service locally by forwarding the port 9696 on our computer \n",
    "to the port 80 on the service:\n",
    "\n",
    "```bash\n",
    "kubectl port-forward service/<Service name> 9696:80\n",
    "```\n",
    "\n",
    "Run `q6_test.py` (from the homework 5) once again to verify that everything is working. \n",
    "You should get the same result as in Question 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'get_card': False, 'get_card_probability': 0.21312682711608702}\n"
     ]
    }
   ],
   "source": [
    "!python q6_test.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Autoscaling\n",
    "\n",
    "Now we're going to use a[HorizontalPodAutoscaler](https: // kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/)\n",
    "(HPA for short) that automatically updates a workload resource(such as our deployment),\n",
    "with the aim of automatically scaling the workload to match demand.\n",
    "\n",
    "Use the following command to create the HPA:\n",
    "\n",
    "```bash\n",
    "kubectl autoscale deployment credit-card - -name credit-card-hpa - -cpu-percent = 20 - -min = 1 - -max = 3\n",
    "```\n",
    "\n",
    "You can check the current status of the new HPA by running:\n",
    "\n",
    "```bash\n",
    "kubectl get hpa\n",
    "```\n",
    "\n",
    "The output should be similar to the next:\n",
    "\n",
    "```bash\n",
    "NAME              REFERENCE                TARGETS   MINPODS   MAXPODS   REPLICAS   AGE\n",
    "credit-card-hpa   Deployment/credit-card   1 % /20 % 1         3         1          27s\n",
    "```\n",
    "\n",
    "`TARGET` column shows the average CPU consumption across all the Pods controlled by the corresponding deployment.\n",
    "Current CPU consumption is about 0 % as there are no clients sending requests to the server.\n",
    ">\n",
    ">Note: In case the HPA instance doesn't run properly, try to install the latest Metrics Server release\n",
    "> from the `components.yaml` manifest:\n",
    "> ```bash\n",
    "> kubectl apply - f https: // github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml\n",
    ">```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME              REFERENCE                TARGETS         MINPODS   MAXPODS   REPLICAS   AGE\n",
      "credit-card-hpa   Deployment/credit-card   <unknown>/20%   1         3         0          5s\n"
     ]
    }
   ],
   "source": [
    "!kubectl get hpa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Increase the load\n",
    "\n",
    "Let's see how the autoscaler reacts to increasing the load. To do this, we can slightly modify the existing\n",
    "`q6_test.py` script by putting the operator that sends the request to the credit-card service into a loop.\n",
    "\n",
    "```python\n",
    "while True:\n",
    "    sleep(0.1)\n",
    "    response = requests.post(url, json=client).json()\n",
    "    print(response)\n",
    "```\n",
    "\n",
    "Now you can run this script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python q6_test.py"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observation: It returns the output in a loop.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 8 (optional)\n",
    "\n",
    "Run `kubectl get hpa credit-card-hpa --watch` command to monitor how the autoscaler performs. \n",
    "Within a minute or so, you should see the higher CPU load; and then - more replicas. \n",
    "What was the maximum amount of the replicas during this test?\n",
    "\n",
    "\n",
    "* 1\n",
    "* 2\n",
    "* 3\n",
    "* 4\n",
    "\n",
    ">Note: It may take a few minutes to stabilize the number of replicas. Since the amount of load is not controlled \n",
    "> in any way it may happen that the final number of replicas will differ from initial.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Submit the results\n",
    "\n",
    "* Submit your results here: https://forms.gle/TqVbjFD1jRZ874nS9\n",
    "* You can submit your solution multiple times. In this case, only the last submission will be used \n",
    "* If your answer doesn't match options exactly, select the closest one\n",
    "\n",
    "\n",
    "## Deadline\n",
    "\n",
    "The deadline for submitting is **5 December 2022 (Monday), 23:00 CEST (Berlin time)**. \n",
    "\n",
    "After that, the form will be closed.\n"
   ]
  }
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