k8s_example

From a Jupyter notebook to a scalable service in cloud

Run the single pod of containers

To run the service as a single local pod of containers:

• Run the containers:
  • docker-compose up -d
• Test the responsiveness of the service:
  • telnet localhost 80
• Remove the allocated docker resources (containers & network):
  • docker-compose down

Run the k8s cluster

The prototype can be deployed using minikube to create a Kubernetes cluster running on VMs. See https://kubernetes.io/docs/setup/minikube/ for further details about how to install/configure it.

Follow the below steps in order to create an autoscalable service (NOTE the service listen to port 30000):

• Create the Kubernetes cluster:
  • minikube start --memory=1024 --extra-config=controller-manager.horizontal-pod-autoscaler-upscale-delay=1m --extra-config=controller-manager.horizontal-pod-autoscaler-downscale-delay=2m --extra-config=controller-manager.horizontal-pod-autoscaler-sync-period=10s
• Build the image locally and configure Minikube in order to pull it:
  • eval $(minikube docker-env)
  • docker build -t anomaly_app:latest .
• Deploy the autoscaled (basing on CPU usage) service:
  • kubectl create -f k8s/deploys.yml,k8s/services.yml,k8s/hpas.yml
• Test the responsiveness of the service:
  • telnet $(minikube ip) 30000
• Clean the environment, destroy the kubernetes cluster:
  • kubectl delete hpa app && kubectl delete svc app redis && kubectl delete deployment app redis
  • minikube stop && minikube delete

Wait few minutes (1-2) in order to have the autoscaler working.

In order to submit requests, consider the url http://$(minikube ip):30000.

A sample for requests

Consider to use the sample in data/ for requests, e.g.:

$ curl -X POST \
-H "Content-Type: application/x-www-form-urlencoded" \
-d "@./data/sample.body" \
http://$(minikube ip):30000/get_anomalous_data
submitted
$ curl -X GET http://$(minikube ip):30000/get_anomalous_data
[["18:27:26.352", 2.449], ["18:27:26.411", 2.554]]