Update serving

After the custom serving has deployed，you can use arena serve update to update the serving docker images, replicas.

1. Deploy the serving job

we use the app.py script in project to start restful server,you can use arena to deploy trainted model:

$ arena serve custom \
    --name=fast-style-transfer \
    --gpus=1 \
    --version=alpha \
    --replicas=1 \
    --restful-port=5000 \
    --image=happy365/fast-style-transfer:latest \
    "python app.py"

check the status of TensorFlow Serving Job:

$ arena serve list
NAME                 TYPE    VERSION  DESIRED  AVAILABLE  ADDRESS       PORTS
fast-style-transfer  Custom  alpha    1        0          172.16.113.5  RESTFUL:5000

because the docker image is very large,pulling it requests some time,we can use kubectl to check the pod status:

$ kubectl get pods
NAME                                                       READY   STATUS              RESTARTS   AGE
fast-style-transfer-alpha-custom-serving-6988f57d4-dd6v6   0/1     ContainerCreating   0          34s

2. Scale the serving replicas

if you want to scale the replicas，you can use arena serve update custom to update the serving.

$ arena serve update custom
  --name=fast-style-transfer 
  --replicas=2

check the pod number

$ kubectl get pods
NAME                                                       READY   STATUS    RESTARTS   AGE
fast-style-transfer-alpha-custom-serving-6988f57d4-dd6v6   1/1     Running   0          4m34s
fast-style-transfer-alpha-custom-serving-6988f57d4-tqqlc   1/1     Running   0          59s

2. Update the serving docker image

if you want update the docker image, you can use the command below

$ arena serve update custom
  --name=fast-style-transfer 
  --image=happy365/fast-style-transfer:0.0.1

After you execute the command, the custom serving will do rolling update with the support of kubernetes deployment.