k8s_readme.md

Quick readme, not detailed

All-in-one script

You need to preinstall helm, kubectl, docker and minikube (or any other local Kubernetes framework)

Then deploy everything with the following script!

$ git clone --recurse-submodules -j8 git@github.com:wayneweiqiang/QuakeFlow.git
$ sh deploy_local.sh

Prebuilt Kafka

1. Install

helm repo add bitnami https://charts.bitnami.com/bitnami
helm install quakeflow-kafka bitnami/kafka   

2. Create topics

kubectl run --quiet=true -it --rm quakeflow-kafka-client --restart='Never' --image docker.io/bitnami/kafka:2.7.0-debian-10-r68 --restart=Never --command -- bash -c "kafka-topics.sh --create --topic phasenet_picks --bootstrap-server quakeflow-kafka.default.svc.cluster.local:9092 && kafka-topics.sh --create --topic gmma_events --bootstrap-server quakeflow-kafka.default.svc.cluster.local:9092 && kafka-topics.sh --create --topic waveform_raw --bootstrap-server quakeflow-kafka.default.svc.cluster.local:9092"

2. Check status

helm status quakeflow-kafka

Our own containers

1. Switch to minikube environment

eval $(minikube docker-env)     

1.1. Fix metrics-server for auto-scalling (Only for docker) https://stackoverflow.com/questions/54106725/docker-kubernetes-mac-autoscaler-unable-to-find-metrics

kubectl apply -f metrics-server.yaml

2. Build the docker images, see the docs for each container

docker build --tag quakeflow-spark:1.0 .
...

3. Create everything

kubectl apply -f quakeflow-delpoyment.yaml     

3.1 Add autoscaling

kubectl autoscale deployment phasenet-api --cpu-percent=80 --min=1 --max=10
kubectl autoscale deployment gmma-api --cpu-percent=80 --min=1 --max=10

3.2 Expose API

kubectl expose deployment phasenet-api --type=LoadBalancer --name=phasenet-service

4. Check the pods

kubectl get pods

5. Check the logs (an example)

kubectl logs quakeflow-spark-7699cd45d8-mvv6r

6. Delete a single deployment

kubectl delete deploy quakeflow-spark     

7. Delete everything

kubectl delete -f quakeflow-delpoyment.yaml