dog-breed-classification-ml/Makefile at main · data-max-hq/dog-breed-classification-ml · GitHub

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all-seldon: build-seldon start-seldon load-seldon install-kubeflow helm-seldon
all-tfserve: build-tfserve start-tfserve load-tfserve install-kubeflow

start-seldon:
	minikube start --driver=docker --kubernetes-version=v1.21.6

start-tfserve:
	minikube start

install-kubeflow:
	export PIPELINE_VERSION=1.8.2
	kubectl apply -k "github.com/kubeflow/pipelines/manifests/kustomize/cluster-scoped-resources?ref=$$PIPELINE_VERSION"
	kubectl wait --for condition=established --timeout=60s crd/applications.app.k8s.io
	kubectl apply -k "github.com/kubeflow/pipelines/manifests/kustomize/env/platform-agnostic-pns?ref=$$PIPELINE_VERSION"

port-emissary:
	kubectl port-forward svc/emissary-ingress -n emissary 8080:80

port-kubeflow:
	kubectl port-forward svc/ml-pipeline-ui -n kubeflow 8081:80

port:
	kubectl port-forward svc/ambassador -n ambassador 8080:80

port-admin:
	kubectl port-forward svc/ambassador-admin -n ambassador 8877:8877

helm-seldon:
	helmfile --file helmfile-seldon.yaml sync

helm-tfserve:
	helmfile --file helmfile-tfserve.yaml sync

delete:
	minikube delete --all

deploy-seldon:
	kubectl create ns seldon
	kubectl apply -f ./seldon

deploy-tensorflow:
	kubectl apply -f ./tensorflow

build-tfserve:
	docker pull tensorflow/serving
	docker tag tensorflow/serving tfserve:minikube
	docker build -t trainmodel:minikube --build-arg CONFIG="KUBERNETES" --file Dockerfile.train .
	docker build -t streamlit:minikube --build-arg CONFIG="TENSORFLOW" --file Dockerfile.streamlit .

load-tfserve:
	minikube image load tfserve:minikube
	minikube image load trainmodel:minikube
	minikube image load streamlit:minikube

load-seldon:
	minikube image load dogbreed:minikube
	minikube image load trainmodel:minikube
	minikube image load streamlit:minikube

build-seldon:
	docker build -t dogbreed:minikube .
	docker build -t trainmodel:minikube --build-arg CONFIG="KUBERNETES" --file Dockerfile.train .
	docker build -t streamlit:minikube --file Dockerfile.streamlit .

compose-seldon:
	docker compose -f docker-compose-seldon.yaml up --build

compose-tfserve:
	docker compose -f docker-compose-tfserve.yaml up --build

local-train:
	python3 train_model.py

run:
	python3 kubeflow_pipeline.py

requirements:
	pip install -r requirements.txt

install-emissary:
	helm repo add datawire https://app.getambassador.io
	helm repo update
	kubectl create namespace emissary && \
	kubectl apply -f https://app.getambassador.io/yaml/emissary/3.1.0/emissary-crds.yaml
	kubectl wait --timeout=90s --for=condition=available deployment emissary-apiext -n emissary-system
	helm install emissary-ingress --namespace emissary datawire/emissary-ingress --values=./charts/emissary/values.emissary.local.yaml && \
	kubectl -n emissary wait --for condition=available --timeout=90s deploy -lapp.kubernetes.io/instance=emissary-ingress