awwvision

Awwvision

Awwvision is a Kubernetes and Cloud Vision API sample that uses the Vision API to classify (label) images from Reddit's /r/aww subreddit, and display the labelled results in a web app.

Awwvision has three components:

1. A simple Redis instance.
2. A webapp that displays the labels and associated images.
3. A worker that handles scraping Reddit for images and classifying them using the Vision API. Cloud Pub/Sub is used to coordinate tasks between multiple worker instances.

Prerequisites

1. Create a project in the Google Cloud Platform Console.

2. Enable billing for your project.

3. Enable the Vision and Pub/Sub APIs. See the "Getting Started" page in the Vision API documentation for more information on using the Vision API.

4. Install the Google Cloud SDK:

    $ curl https://sdk.cloud.google.com | bash
    $ gcloud init
   

5. Install and start up Docker.

Create a Container Engine cluster

This example uses Container Engine to set up the Kubernetes cluster.

1. Create a cluster using gcloud. You can specify as many nodes as you want, but you need at least one. The cloud-platform scope is needed to allow access to the Pub/Sub and Vision APIs.

    gcloud container clusters create awwvision \
        --num-nodes 2 \
        --scopes cloud-platform
   

2. Set up the kubectl command-line tool to use the container's credentials.

    gcloud container clusters get-credentials awwvision
   

3. Verify that everything is working:

    kubectl cluster-info
   

Deploy the sample

From the awwvision directory, use make all to build and deploy everything. Make sure Docker is running first.

    make all

As part of the process, a Docker image will be built and uploaded to the GCR private container registry. In addition, .yaml files will be generated from templates— filled in with information specific to your project— and used to deploy the 'redis', 'webapp', and 'worker' Kubernetes resources for the example.

Check the Kubernetes resources on the cluster

After you've deployed, check that the Kubernetes resources are up and running. First, list the [pods](https://github.com/kubernetes/kubernetes/blob/master/docs /user-guide/pods.md). You should see something like the following, though your pod names will be different.

$ kubectl get pods
NAME                     READY     STATUS    RESTARTS   AGE
awwvision-webapp-vwmr1   1/1       Running   0          1m
awwvision-worker-oz6xn   1/1       Running   0          1m
awwvision-worker-qc0b0   1/1       Running   0          1m
awwvision-worker-xpe53   1/1       Running   0          1m
redis-master-rpap8       1/1       Running   0          2m

List the replication controllers. You can see the number of replicas specified for each, and the images used.

$ kubectl get rc
CONTROLLER         CONTAINER(S)       IMAGE(S)                              SELECTOR                      REPLICAS   AGE
awwvision-webapp   awwvision-webapp   gcr.io/your-project/awwvision-webapp   app=awwvision,role=frontend   1          4m
awwvision-worker   awwvision-worker   gcr.io/your-project/awwvision-worker   app=awwvision,role=worker     3          3m
redis-master       redis-master       redis                                  app=redis,role=master         1          5m

Once deployed, get the external IP address of the webapp [service](https://github.com/kubernetes/kubernetes/blob/master/docs/user- guide/services.md). It may take a few minutes for the assigned external IP to be listed in the output. After a short wait, you should see something like the following, though your IPs will be different.

$ kubectl get svc awwvision-webapp
NAME               CLUSTER_IP      EXTERNAL_IP    PORT(S)   SELECTOR                      AGE
awwvision-webapp   10.163.250.49   23.236.61.91   80/TCP    app=awwvision,role=frontend   13m

Visit your new webapp and start its crawler

Visit the external IP of the awwvision-webapp service to open the webapp in your browser, and click the Start the Crawler button.

Next, click go back, and you should start to see images from the /r/aww subreddit classified by the labels provided by the Vision API. You will see some of the images classified multiple times. (You can reload in a bit, in case you brought up the page before the crawler was finished).

Cleanup

To delete your Kubernetes pods, replication controllers, and services, and to remove your auto-generated .yaml files, do:

    make delete

Note: this won't delete your Container Engine cluster itself. If you are no longer using the cluster, you may want to take it down. You can do this through the Google Cloud Platform Console.