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.