From 5de7ec0937b6366b7c522ab781f545e87e9e326e Mon Sep 17 00:00:00 2001 From: Cyy92 Date: Mon, 31 Aug 2020 17:27:56 +0900 Subject: [PATCH 1/3] #25 OpenFx Manual --- docs/source/2_setup/1_cli_setup/index.md | 62 +- docs/source/2_setup/2_openfx_setup/index.md | 729 +++++++++++++++++- .../5_components/5_grpc_http/Gateway.png | Bin 0 -> 50801 bytes docs/source/5_components/5_grpc_http/index.md | 40 +- .../5_components/6_logger/gpu-grafana.png | Bin 0 -> 855900 bytes docs/source/5_components/6_logger/grafana.PNG | Bin 0 -> 229569 bytes docs/source/5_components/6_logger/index.md | 47 +- .../5_components/6_logger/prometheus.PNG | Bin 0 -> 35601 bytes docs/source/5_components/7_gpu/index.md | 129 +++- docs/source/5_components/7_gpu/openfx-gpu.png | Bin 0 -> 191955 bytes 10 files changed, 991 insertions(+), 16 deletions(-) create mode 100644 docs/source/5_components/5_grpc_http/Gateway.png create mode 100644 docs/source/5_components/6_logger/gpu-grafana.png create mode 100644 docs/source/5_components/6_logger/grafana.PNG create mode 100644 docs/source/5_components/6_logger/prometheus.PNG create mode 100644 docs/source/5_components/7_gpu/openfx-gpu.png diff --git a/docs/source/2_setup/1_cli_setup/index.md b/docs/source/2_setup/1_cli_setup/index.md index 3ed6e7b..163ecb1 100644 --- a/docs/source/2_setup/1_cli_setup/index.md +++ b/docs/source/2_setup/1_cli_setup/index.md @@ -1,4 +1,64 @@ CLI Setup ==================================== -- OpenFx CLI를 설치하는 방법 \ No newline at end of file +OpenFx-cli는 OpenFx를 사용하기 위한 Command Line Interface 도구이다. 이를 통해 OpenFx 프레임워크 위 서비스들을 배포하여 사용할 수 있다. CLI 설치 방법은 다음의 과정을 통해 진행하면 된다. + + + +# Requirements + +- [go version >= 1.12]() + +- [docker version >= 18.06]() + + > Note + + > OS에 맞게 설치 요망 + +- [OpenFx-Gateway & Executor 구동]() + + + +# Get Started + +### Setting insecure registries + +도커 레지스트리는 SSL 인증서 없이 이용할 수 없다. SSL 인증서 없이 도커 레지스트리를 사용하기 위해서는 `insecure-registries`에 대한 설정이 필요하다. `insecure-registries` 에 대한 설정은 아래와 같이 진행한다. + +```bash +$ sudo vim /etc/docker/daemon.json +>> +{"insecure-registries": ["YOUR PRIVATE REGISTRY SERVER IP:PORT"]} + +$ systemctl daemon-reload +$ service docker restart +``` + + + +### Compile OpenFx-CLI + +- `openfx-cli`를 __keti-openfx__ 디렉토리 밑에 클론하여 컴파일을 진행한다. + + ```bash + $ cd $GOPATH/src/github.com/keti-openfx + $ git clone https://github.com/keti-openfx/openfx-cli.git + $ cd openfx-cli + ``` + +- `make` 명령을 실행하여 컴파일을 진행한다. + + ```bash + $ make build + >> + go build + go install + ``` + +- `$GOPATH/bin`을 확인해보면 `openfx-cli`가 컴파일 되어 있는 것을 확인할 수 있다. + + ```bash + $ cd $GOPATH/bin + $ ls + openfx-cli + ``` diff --git a/docs/source/2_setup/2_openfx_setup/index.md b/docs/source/2_setup/2_openfx_setup/index.md index 1781421..51a8d05 100644 --- a/docs/source/2_setup/2_openfx_setup/index.md +++ b/docs/source/2_setup/2_openfx_setup/index.md @@ -1,4 +1,731 @@ OpenFx Setup ==================================== -On-premise / Kubernetes & Minikube 설치방법 / OpenFx 설치방법 \ No newline at end of file +다음은 OpenFx 프레임워크를 구성하기 위해 쿠버네티스 클러스터(Kubernetes Cluster) 설치부터 OpenFx 설치까지의 가이드이다. + + + +## Configuration + +쿠버네티스 클러스터(Kubernetes Cluster) 위에서 OpenFx 코어를 동작시키기 위해서는 기본적으로 다음과 같은 최소 사양이 만족되어야 한다. + +- `프로세서 코어` >= 2 +- `메모리` >= 8GB +- `하드디스크` >= 100GB +- `네트워크` 지원 가능 + + + +## Kubernetes Cluster 구축 + +쿠버네티스 클러스터는 다음의 두 가지 방식으로 구축할 수 있다. + +- 하나 혹은 다수의 물리 서버(가상 머신)를 묶어 `ansible playbook`으로 구축 +- 미니쿠베(Minikube)를 통해 구축 + +다음은 위의 두 가지 방식을 통해 쿠버네티스 클러스터를 구축하는 방법에 대한 가이드이다. + + + +### Ansible을 통한 쿠버네티스 클러스터 구축 + +`Ansible`은 파이썬 기반의 IaC(Infrastructure as Code)를 지향하는 자동화 관리 도구이다. yaml 포맷을 기반으로 플레이북을 실행시켜서 여러 머신에 동시에 소프트웨어 패키지를 설치함으로써 인프라 시스템 구축을 자동화 할 수 있다. 그 외에도 에드혹 모드로 모듈을 실행하여 여러 머신의 상태를 조회해 볼 수 있다. 본 가이드에서는 쿠버네티스를 인프라 시스템에 손쉽게 설치할 수 있도록 하는 ansible 기반의 `kubespray`를 활용하여 쿠버네티스 클러스터를 구축하는 방법을 안내한다. 아래는 kubespray를 통해 yaml 파일에 정의된 각각의 롤(role)들을 기반으로 쿠버네티스 클러스터를 구축하는 방법에 대해 설명한다. + + + +#### Copy ssh key + +Ansible을 통해 다수의 물리 서버(가상 머신)를 묶어 쿠버네티스 클러스터를 구축하고자 하는 경우, 하나의 물리 서버에서만 ansible 플레이북을 실행하여 구축할 수 있다. 이는 마스터 노드가 될 물리 서버에서 워커 노드가 될 물리 서버들로의 ssh 접속을 통해 이루어진다. 이를 위해 클러스터를 구성할 물리 서버들에 ssh key를 복사한다. + +```bash +$ ssh-keygen -t rsa +$ ssh-copy-id -i ~/.ssh/id_rsa.pub root@ +$ ssh-copy-id -i ~/.ssh/id_rsa.pub root@ +``` + + + +#### Clone kubespray + + + +#### Install required packages + +- CentOS + + ```bash + $ yum --enablerepo=extras install epel-release + $ yum install python3 python-pip + $ cd kubespray + $ sudo pip install --upgrage setuptools + $ sudo pip3 install -r requirements.txt + ``` + +- Ubuntu + + ```bash + $ apt-get update + $ apt-get install python-pip python3-pip + $ cd kubespray + $ sudo pip install --upgrage setuptools + $ sudo pip3 install -r requirements.txt + ``` + + + +#### Configuration + +마스터 노드가 될 물리 서버에서 다른 물리 서버로 ssh 접속하기 위해서는 해당 서버의 ip를 알아야 한다. kubespray에서는 이를 `hosts.ini` 파일에 정의하고 있다. 이는 다음과 같이 할 수 있다. + +```bash +$ sudo vi inventory/mycluster/hosts.ini +>> +[all] +node1 ansible_host= ip= +node2 ansible_host= ip= +node3 ansible_host= ip= +node4 ansible_host= ip= + +[kube-master] +node1 +node2 + +[etcd] +node1 + +[kube-node] +node2 +node3 + +[k8s-cluster:children] +kube-master +kube-node + +[calico-rr] +``` + +> Note +> +> `etcd` 항목에 기재될 노드의 갯수는 반드시 홀수 개가 되어야 하며, `kube-master` 항목에 기재될 마스터 노드의 갯수는 최소 1개 이상이다. 또한 마스터 노드는 동시에 워커 노드가 될 수 있다. + + + +도커 이미지 개인 저장소(Docker private registry)를 구축한 경우 다음의 경로에 있는 설정 파일을 수정하면 된다. + +```bash +$ sudo vi inventory/mycluster/group_vars/all/docker.yml +>> +# Add here +docker_insecure_registries: + - +``` + + + +#### Setup cluster + +다음의 명령어를 실행하여 쿠버네티스 클러스터를 구축한다. + +```bash +$ ansible-playbook -i inventory/mycluster/hosts.ini --become --become-user=root cluster.yml -e kube_version=v1.15.2 +``` + + + +#### Verify + +클러스터 구축이 완료되었으면, 다음의 명령어를 통해 정상적으로 구축이 되었는지를 확인한다. + +```bash +$ kubectl get pods --all-namespaces +kube-system calico-kube-controllers-b784f96cc-bjzsh 1/1 Running 1 41d +kube-system calico-node-mhkp8 1/1 Running 2 41d +kube-system calico-node-p49md 1/1 Running 3 41d +kube-system coredns-74c9d4d795-p74lb 1/1 Running 1 41d +kube-system coredns-74c9d4d795-qms9s 1/1 Running 1 41d +kube-system dns-autoscaler-576b576b74-95rmk 1/1 Running 1 41d +kube-system kube-apiserver-node1 1/1 Running 1 41d +kube-system kube-controller-manager-node1 1/1 Running 1 41d +kube-system kube-proxy-hq6zl 1/1 Running 1 41d +kube-system kube-proxy-qhkrc 1/1 Running 1 41d +kube-system kube-scheduler-node1 1/1 Running 1 41d +kube-system kubernetes-dashboard-7c547b4c64-d7ghs 1/1 Running 1 41d +kube-system local-volume-provisioner-dgftl 1/1 Running 1 41d +kube-system local-volume-provisioner-dhljn 1/1 Running 1 41d +kube-system metrics-server-c779857d6-4ss6t 1/1 Running 0 35d +kube-system nginx-proxy-node2 1/1 Running 1 41d +``` + + + +### Minikube + +`미니쿠베`는 쿠버네티스처럼 클러스터를 구성하지 않고 단일 컴퓨팅 환경(노트북, 데스크탑 등)에서 쿠버네티스 환경을 만들어준다. 로컬 환경에서 단일 클러스터를 구동시킬 수 있는 도구인 미니쿠베는 단일 노드에 쿠버네티스 클러스터 환경을 구축하기 때문에 접근성이 뛰어나 클러스터를 관리하기가 수월하다. 이로 인해 더욱 용이해진 디버깅 환경을 사용자에게 제공하여 편의성을 높여준다. 다음은 미니쿠베 설치 방법 및 미니쿠베 환경 위에서 쿠버네티스를 사용할 수 있게 해주는 명령 줄 인터페이스인 `kubectl` 설치 방법이다. + + + +#### Install Virtual Machine + +미니쿠베를 시작하기 전, 미니쿠베를 통해 쿠버네티스 컴포넌트를 가상 머신(Virtual Machine) 위에서 동작시키기 위해 [버츄얼박스]()를 설치한다. + +> Note +> +> 가상 머신이 아닌 호스트 OS 환경(리눅스)이라면, 가상 머신 설치를 생략한다. + + + +#### Install Minikube + +클러스터를 구축할 가상 머신 혹은 호스트 OS 환경이 준비되었다면, 본격적으로 쿠버네티스 클러스터를 로컬 환경에서 구축하기 위한 미니쿠베 설치를 진행하여야 한다. + +- Linux + + ```bash + $ wget minikube https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 && chmod +x minikube-linux-amd64 + $ sudo mv minikube-linux-amd64 minikube + $ sudo mv minikube /usr/local/bin + ``` + + + + + +#### Start Minikube + +미니쿠베를 시작하기 전, 미니쿠베는 기본적으로 하이퍼바이저(hypervisor)를 지원하고 있으며 다음의 [링크]()를 통해 지원하고 있는 하이퍼바이저를 확인 후, 이를 설치하여 사용할 수 있다. 하이퍼바이저란 virtualbox, vmware 같이 물리적 호스트에서 다수의 가상머신을 실행할 수 있도록 하여 컴퓨팅 자원을 효과적으로 사용할 수 있게 하는 도구이다. 미니쿠베를 실행하기 위해선 가상 머신이 필요하며, 가상 머신에서 실행하지 않으려면 리눅스 시스템과 도커가 필요하다. 하이퍼바이저 설치까지 완료되었으면, `--driver=` 플래그를 추가해서 미니쿠베를 시작할 수 있다. 뿐만 아니라 쿠버네티스 버전을 명시하여 미니쿠베를 실행할 수 있는데, 현재 OpenFx 코어는 쿠버네티스 버전 `1.15.2`까지 지원하기 때문에 다음과 같이 버전을 지정하여 미니쿠베를 시작해야 한다. + +```bash +$ echo export CHANGE_MINIKUBE_NONE_USER=true >> ~/.bashrc +$ sudo minikube start --driver= --kubernetes-version v1.15.2 --insecure-registry=":" +``` + + + +하이퍼바이저 설치를 하지 않았다면 `--driver=none` 플래그를 통해 미니쿠베를 시작할 수도 있다. + +```bash +$ echo export CHANGE_MINIKUBE_NONE_USER=true >> ~/.bashrc +$ sudo minikube start --driver=none --kubernetes-version v1.15.2 --insecure-registry=":" +``` + +> Note +> +> `:` 는 도커 레지스트리 서버의 주소와 포트번호를 적어주어야 한다. 도커 이미지 개인 저장소(Docker private registry)를 구축하는 방법은 다음의 [링크]()를 통해 진행하면 된다. + + + +추가로 `minikube start`의 다양한 플래그가 궁금하다면 다음의 명령어를 입력하여 원하는 정보를 얻을 수 있다. + +```bash +$ sudo minikube start --help +>> +Starts a local kubernetes cluster + +Options: +... + --apiserver-port=8443: The apiserver listening port + --cpus=2: Number of CPUs allocated to the minikube VM + --docker-opt=[]: Specify arbitrary flags to pass to the Docker daemon. (format: key=value) + --insecure-registry=[]: Insecure Docker registries to pass to the Docker daemon. The default service CIDR range +will automatically be added. + --memory='2000mb': Amount of RAM allocated to the minikube VM (format: [], where unit = b, k, m or +g) + --vm-driver='virtualbox': VM driver is one of: [virtualbox parallels vmwarefusion kvm2 vmware none] + --wait=true: Wait until Kubernetes core services are healthy before exiting + +Usage: + minikube start [flags] [options] + +Use "minikube start options" for a list of global command-line options (applies to all commands). +``` + + + +#### Further progress + +미니쿠베를 시작한 후, 다음의 명령어를 통해 `~/.kube`, `~/.minikube` 디렉토리의 권한을 `$USER`로 변경해야 한다. 이는 현재 사용자가 쿠버네티스 및 미니쿠베 관련 설정 파일들을 수정할 수 있게 하기 위함이다. + +```bash +$ sudo chown -R $USER ~/.kube ~/.minikube +``` + + + +쿠버네티스에서 자동 스케일링을 하기 위해서는 각 노드의 자원 사용량 정보를 알아야 한다. 이를 위해 쿠버네티스에서는 각 노드 별 메트릭 데이터를 수집하는 `heapster`와 `metrics-server`를 제공하고 있다. 쿠버네티스에서 기본적으로 설정된 도구는 `heapster`인데 `metrics-server`가 조금 더 나은 성능을 보이고 있다. 이 두 개의 도구를 동시에 실행하면 충돌이 일어나기 때문에 미니쿠베에서는 수동으로 `heapster`를 종료하고 `merics-server`를 실행해주어야 한다. + +```bash +$ sudo minikube addons disable heapster +$ sudo minikube addons enable metrics-server +``` + + + +#### Install kubectl + +`kubectl `은 쿠버네티스를 제어하기 위한 명령 줄 인터페이스이다. 미니쿠베를 통해 구축된 로컬 환경에서의 쿠버네티스 클러스터를 사용하기 위해선 설치해야만 하는 필수 요소이다. 이는 아래와 같은 명령어로 설치를 진행할 수 있다. + +- Linux + + ```bash + $ curl -LO https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl + $ curl -LO https://storage.googleapis.com/kubernetes-release/release/v1.14.0/bin/linux/amd64/kubectl + $ chmod +x ./kubectl + $ sudo mv ./kubectl /usr/local/bin/kubectl + $ kubectl version + ``` + + + + +#### Verify installed minikube + +가상 머신, 미니쿠베, 그리고 kubectl 설치까지 모두 완료하였으면, 쿠버네티스 클러스터가 정상적으로 동작하는지를 확인하여야 한다. 이는 아래와 같은 명령어를 통해 확인할 수 있다. + +```bash +$ kubectl get pods --all-namespaces +``` + + + +#### Troble Shooting (CrashLoopBackOff Error) + +호스트 OS 혹은 가상 머신에서 미니쿠베를 실행할 경우, 아래와 같은 에러가 발생할 수 있다. + +```bash +$ kubectl get pods --all-namespaces +>> +NAMESPACE NAME READY STATUS RESTARTS AGE +kube-system coredns-fb8b8dccf-mtn7d 0/1 CrashLoopBackOff 5 3m54s +kube-system coredns-fb8b8dccf-t584j 0/1 CrashLoopBackOff 5 3m54s +kube-system etcd-minikube 1/1 Running 0 2m46s +kube-system kube-addon-manager-minikube 1/1 Running 0 4m1s +kube-system kube-apiserver-minikube 1/1 Running 0 2m51s +kube-system kube-controller-manager-minikube 1/1 Running 0 2m52s +kube-system kube-proxy-rtswf 1/1 Running 0 3m54s +kube-system kube-scheduler-minikube 1/1 Running 0 2m51s +kube-system storage-provisioner 1/1 Running 0 3m53s +``` + +CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플러그인이란 임의의 probe query를 자신에게 보내고 이를 몇번 반환받게 되는지를 추적한다. 위와 같은 에러는 loop 감지 플러그인이 업스트림 dns 서버 중 하나에서 무한 전달 루프를 감지해서 발생하는 에러이다. 이는 다음과 같이 해결할 수 있다. + +- Solution #1 + + **CoreDns configmap**을 수정한다. 이는 아래와 같은 명령어를 실행 후, `loop`이라는 단어를 삭제한다. + + ```bash + $ kubectl -n kube-system edit configmap coredns + ``` + + `loop`이라는 단어를 삭제한 후, 새로운 설정이 적용된 Pod를 생성하기 위해 기존의 Pod를 삭제한다. + + ```bash + $ kubectl -n kube-system delete pod -l k8s-app=kube-dns + ``` + +- Solution #2 + + **Solution #1**의 방법으로 에러가 해결이 안되면 이는 방화벽 규칙의 문제일 수 있다. 쿠버네티스 클러스터 구동 시, 기본적으로 추가되는 방화벽 규칙들이 있다. 하지만 쿠버네티스 클러스터 구동 중, 방화벽 규칙이 제대로 추가되지 않거나 기존의 규칙들과 충돌이 일어날 수 있다. 이와 같은 경우, 기존의 규칙들을 모두 제거하고 쿠버네티스 및 도커 관련 방화벽 규칙들을 재정의 해주어야 하며, 이는 아래와 같은 명령어로 실행할 수 있다. + + ```bash + $ iptables -t nat -F + $ iptables -t mangle -F + $ iptables -F + $ iptables -X + $ iptables -P INPUT ACCEPT + $ iptables -P FORWARD ACCEPT + $ iptables -P OUTPUT ACCEPT + $ iptables -N DOCKER + $ iptables -N DOCKER-ISOLATION + ``` + + > Note + > + > **Solution #1** 의 방법으로 에러 해결 시, **Solution #2** 는 진행하지 않아도 된다. + + + +## OpenFx 설치 + +쿠버네티스 클러스터가 구동 중이고, 도커 이미지를 담을 개인 저장소를 구축하여 로그인까지 완료하였으면 본격적으로 OpenFx를 배포하여야 한다. 이를 위해 먼저 소스들을 컴파일하여 도커 이미지로 빌드하여 저장소에 저장하여야 한다. + + + +### Requirements + +- [go version >= 1.12]() +- [docker version >= 18.06]() + + + +### Package dependencies + +OpenFx API 게이트웨이를 사용하기 위한 의존 패키지들은 다음과 같다. + + + +- **google.golang.org/grpc** +- **github.com/protocolbuffers/protobuf** +- **github.com/golang/protobuf/protoc-gen-go** +- **github.com/grpc-ecosystem/grpc-gateway** +- **grpcio-tools** + +OpenFx API 게이트웨이는 본 가이드에 명시된 버전의 의존 패키지들로 최적화 되어있다. 아래는 각각의 의존 패키지들에 대한 설치 방법이다. + +#### google.golang.org/grpc + +```bash +$ go get -u google.golang.org/grpc +$ go get -u golang.org/x/sys/unix +``` + +#### github.com/protocolbuffers/protobuf + +```bash +$ curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v3.7.1/protoc-3.7.1-linux-x86_64.zip +$ unzip protoc-3.7.1-linux-x86_64.zip -d protoc3 + +$ sudo mv protoc3/bin/* /usr/local/bin/ +$ sudo mv protoc3/include/* /usr/local/include/ + +$ sudo chown $USER /usr/local/bin/protoc +$ sudo chown -R $USER /usr/local/include/google + +$ export PATH=$PATH:/usr/local/bin +``` + +#### github.com/golang/protobuf/protoc-gen-go + +```bash +$ go get -u github.com/golang/protobuf/protoc-gen-go +$ cd $GOPATH/src/github.com/golang/protobuf/protoc-gen-go +$ git checkout tags/v1.2.0 -b v1.2.0 +$ go install +``` + +#### github.com/grpc-ecosystem/grpc-gateway + +```bash +$ cd $GOPATH/src/github.com +$ git clone https://github.com/grpc-ecosystem/grpc-gateway.git +$ cd grpc-ecosystem/grpc-gateway +$ git checkout v1.4.1 + +// Install protoc-gen-grpc-gateway +$ cd protoc-gen-grpc-gateway +$ go get -u github.com/golang/glog +$ go install + +// Install protoc-gen-swagger +$ cd ../protoc-gen-swagger +$ go install +``` + +#### grpcio-tools + +```bash +$ pip install grpcio-tools +$ pip3 install grpcio-tools +``` + + + +#### Troubleshooting + +Mac 사용자들은 다음과 같은 오류가 발생할 수 있다. + +```bash +Traceback (most recent call last): + File "/usr/bin/pip", line 11, in + sys.exit(main()) + File "/usr/lib/python2.7/dist-packages/pip/__init__.py", line 215, in main + locale.setlocale(locale.LC_ALL, '') + File "/usr/lib/python2.7/locale.py", line 581, in setlocale + return _setlocale(category, locale) +locale.Error: unsupported locale setting +``` + +이는 지역 및 언어 선택이 정상적을 설정이 되어 있지 않아서 발생하는 오류이다. 이는 다음과 같이 해결할 수 있다. + +```bash +$ export LC_ALL="en_US.UTF-8" +$ export LC_CTYPE="en_US.UTF-8" +$ sudo dpkg-reconfigure locales +``` + +locales를 재설정하게 되면 `Configuring locales`라는 화면이 표시되고, `en_US.UTF-8 UTF-8`이 체크되어 있는지 확인한 후 OK를 눌러 설정을 마치면 된다. + + + +### Compile OpenFx + +먼저 아래와 같이 `keti-openfx`라는 폴더를 생성하여 OpenFx 소스코드를 복제할 위치를 지정한다. + +```bash +$ mkdir $GOPATH/src/github.com/keti-openfx +$ cd $GOPATH/src/github.com/keti-openfx +``` + +다음은 OpenFx 프레임워크 위 서비스들을 관리하는 gateway의 이미지를 생성하는 방법에 대한 가이드이다. 먼저, `openfx` 저장소를 클론하여 openfx 디렉토리로 이동한다. + +```bash +$ git clone https://github.com/keti-openfx/openfx.git +$ cd openfx +``` + +openfx 디렉토리 내의 `Makefile`에 `REGISTRY`란을 도커 레지스트리 서버에 맞춰 변경한다. + +```bash +$ sudo vim Makefile +REGISTRY= : +... +``` + +`make` 명령어를 이용해서 `openfx-gateway`를 컴파일하고, 이미지를 생성한 뒤, 개인 도커 레지스트리에 저장한다. + +```bash +$ make build +$ make push +``` + +다음은 OpenFx 프레임워크 위 서비스들을 실행하기 위한 gRPC 서버인 executor의 이미지를 생성하는 방법에 대한 가이드이다. 앞서 클론한 openfx 디렉토리 내의 executor 디렉토리로 이동한다. + +```bash +$ cd executor +``` + +OpenFx executor는 다음과 같이 총 7개의 runtime 버전이 존재한다. + +- go +- python +- nodejs +- ruby +- java +- cpp +- csharp + +각각의 runtime 폴더에 있는 `Makefile` 의 `registry` 를 도커 레지스트리 서버에 맞춰 변경한다. + +```bash +$ cd go +$ sudo vim Makefile +registry=: +... + +$ cd ../python +$ sudo vim Makefile +registry=: +... + +$ cd ../nodejs +$ sudo vim Makefile +registry=: +... + +$ cd ../ruby +$ sudo vim Makefile +registry=: +... + +$ cd ../java +$ sudo vim Makefile +registry=: +... + +$ cd ../cpp +$ sudo vim Makefile +registry=: +... + +$ cd ../csharp +$ sudo vim Makefile +registry=: +... +``` + +`executor` 폴더로 돌아와서 `make` 명령을 실행하여 runtime별 executor를 컴파일 한 후, 각각의 이미지를 생성하여 개인 도커 레지스트리에 저장한다. + +```bash +$ cd .. +$ make +``` + +컴파일 완료 후, `docker images`와 레지스트리에 있는 이미지를 확인했을 때, 아래와 같이 결과나 나오면 성공적으로 컴파일이 완료된 것이다. + +```bash +$ docker images +>> +REPOSITORY TAG IMAGE ID CREATED SIZE +:/fxwatcher 0.1.0-csharp 5ab2175321bd 37 minutes ago +690MB +:/fxwatcher 0.1.0-cpp 50bc61dc1545 35 minutes ago +6.66GB +:/fxwatcher 0.1.0-java 0bec44a16eec 30 minutes ago +548MB +:/fxwatcher 0.1.0-ruby 56fa4e607ac6 26 minutes ago +490MB +:/fxwatcher 0.1.0-nodejs b26348908044 28 minutes ago +335MB +:/fxwatcher 0.1.0-python3 5779598d8ad0 25 minutes ago 413MB +:/fxwatcher 0.1.0-python2 b91ef13cede0 32 minutes ago 401MB +:/fxwatcher 0.1.0-go 3cd97230054d 39 minutes ago 793MB +:/fxgateway 0.1.0 89bc10ce43ec 3 hours ago 255MB + 3d1f57588f3f 3 hours ago 986MB +python 2.7-alpine ee70cb11da0d 13 days ago 61.3MB +python 3.4-alpine c06adcf62f6e 2 months ago 72.9MB +registry 2 f32a97de94e1 2 months ago 25.8MB +alpine 3.7 6d1ef012b567 2 months ago 4.21MB +golang 1.9.7 ef89ef5c42a9 10 months ago 750MB +golang 1.10.1 1af690c44028 12 months ago 780MB + +$ curl -k -X GET https://:@:/v2/_catalog +>> +{"repositories":["fxgateway","fxwatcher"]} +``` + + + +### Deploy OpenFx + +OpenFx 컴파일을 완료하였다면, 이제 OpenFx를 배포해보자. + +먼저, 쿠버네티스에서 개인 도커 레지스트리로부터 도커 이미지를 다운받으려면 **도커 인증(Docker credential)**이 필요하다. 이를 위해서 도커 레지스트리 타입의 **Secret**을 사용하여 레지스트리에 인증을 받는다. 그리고 도커 인증을 생성하고 배포하기 위해 **yaml** 파일에 이를 설정한다. 이는 다음의 절차를 통해 진행된다. + +- Secret 생성 +- 도커 인증파일을 base64로 변환한 **.dockerconfigjson** 내용 확인 +- **keti-openfx/openfx/deploy/yaml**폴더의 **docker-registry-secret.yaml**에 **.dockerconfigjson**내용을 이전에 확인한 **.dockerconfigjson**으로 변경 + +#### Create Secret + +다음의 명령어를 통해 secret을 생성 + +```bash +$ kubectl create secret docker-registry regcred --docker-server=: --docker-username= --docker-password= +``` + +- `:` : 개인 레지스트리 주소와 포트 +- `` : 도커 로그인을 위한 아이디 +- `` : 도커 로그인을 위한 비밀번호 + +#### Inspecting the Secret `regcred` + +다음의 명령어를 통해 도커 인증파일을 bash64로 변환한 **.dockerconfigjson** 내용을 확인 + +```bash +$ kubectl get secret regcred --output=yaml +>> +kind: Secret +metadata: + ... + name: regcred + ... +data: + .dockerconfigjson: eyJodHRwczovL2luZGV4L ... J0QUl6RTIifX0= +type: kubernetes.io/dockerconfigjson +``` + +- `.dockerconfigjson`에 나오는 정보는 위와 상이할 수 있다. + +#### Configure docker-registry-secret.yml + +**keti-openfx/openfx/deploy/yaml** 폴더의 **docker-registry-secret.yaml** 파일의 **.dockerconfigjson**의 내용을 위에서 확인한 **Secret** `regcred`의 **.dockerconfigjson** 내용으로 변경 + +```bash +apiVersion: v1 +kind: Secret +metadata: + name: regcred + namespace: openfx +data: + .dockerconfigjson: eyJodHRwczovL2luZGV4L ... J0QUl6RTIifX0= +type: kubernetes.io/dockerconfigjson +--- +apiVersion: v1 +kind: Secret +metadata: + name: regcred + namespace: openfx-fn +data: + .dockerconfigjson: eyJodHRwczovL2luZGV4L ... J0QUl6RTIifX0= +type: kubernetes.io/dockerconfigjson +``` + +- `.dockerconfigjson`에 나오는 정보는 위와 상이할 수 있다. + +위와 같이 도커 인증까지 완료되었으면 이제 본격적으로 쿠버네티스 클러스터에 OpenFx 게이트웨이를 배포하여야 한다. 이는 아래와 같이 진행할 수 있다. + +#### Configure gateway-dep.yml + +**openfx/deploy/yaml** 폴더의 **gateway-dep.yml**파일의 **image**란의 레지스트리 IP와 Port를 변경한다. + +```bash +$ sudo vim $GOPATH/scr/github.com/keti-openfx/openfx/deploy/yaml/gateway-dep.yml +>> +apiVersion: apps/v1beta1 +kind: Deployment +metadata: + name: fxgateway + namespace: openfx +spec: + replicas: 1 + template: + metadata: + labels: + app: fxgateway + spec: + serviceAccountName: fxgateway + imagePullSecrets: + - name: regcred + containers: + - name: fxgateway + image: :/fxgateway:0.1.0 + imagePullPolicy: Always + + env: + - name: FUNCTION_NAMESPACE + value: openfx-fn + - name: IMAGE_PULL_POLICY + value: "Always" + + ports: + - containerPort: 10000 + protocol: TCP + + resources: + requests: + memory: 250Mi + limits: + memory: 250Mi +``` + +게이트웨이 이미지를 `pull`할 레지스트리 주소 변경까지 완료하였으면, 다음의 명령어를 통해 OpenFx 컴포넌트들을 배포한다. + +```bash +$ cd $GOPATH/scr/github.com/keti-openfx/openfx/deploy +$ kubectl apply -f ./namespaces.yml +$ kubectl apply -f ./yaml +$ kubectl get pods --all-namespaces +>> +NAMESPACE NAME READY STATUS RESTARTS AGE +kube-system coredns-fb8b8dccf-4bq7x 1/1 Running 0 113s +kube-system coredns-fb8b8dccf-jw6j2 1/1 Running 0 113s +kube-system etcd-minikube 1/1 Running 0 4m19s +kube-system kube-addon-manager-minikube 1/1 Running 0 4m22s +kube-system kube-apiserver-minikube 1/1 Running 0 4m17s +kube-system kube-controller-manager-minikube 1/1 Running 0 4m6s +kube-system kube-proxy-h8q7p 1/1 Running 0 5m11s +kube-system kube-scheduler-minikube 1/1 Running 0 4m16s +kube-system kubernetes-dashboard-7b8ddcb5d6.. 1/1 Running 0 +4m18s +kube-system metrics-server-89cd44dc7-d8jvj 1/1 Running 0 +4m18s +kube-system storage-provisioner 1/1 Running 0 5m7s +openfx fxgateway-755df6464f-6zrqw 1/1 Running 0 6m28s +openfx prometheus-5c8f7f7c7d-zhpbb 1/1 Running 0 6m30s +openfx grafana-core-7d6b476bb9-dj9bl 1/1 Running 0 6m30s +openfx grafana-import-dashboards-tnskf 1/1 Running 0 6m30s +... +``` + +- `STATUS`가 **Running**이 아닌 경우에는 [링크](https://kubernetes.io/ko/docs/reference/kubectl/cheatsheet/)를 참조하여 포드의 로그를 확인한다. +- `kubectl apply`를 통해 배포되는 pod 중 prometheus는 컴퓨팅 자원들의 metric 정보를 수집하는 모니터링 툴이며, grafana는 prometheus를 통해 수집된 metric 정보들을 시각화해주는 툴이다. + diff --git a/docs/source/5_components/5_grpc_http/Gateway.png b/docs/source/5_components/5_grpc_http/Gateway.png new file mode 100644 index 0000000000000000000000000000000000000000..82eb987505654face75e43502d2c3280ac678f24 GIT binary patch literal 50801 zcmZ^~bwHF|w>Qkt-6h@K64EV02@-;IcegZ1HxeS@fRuDd$AEMwT@upW-SAy--_JSc zJ@5PdVa!~6)?Rz%Z>_bjNYyuT7^ozuFfcF}@?aS?7#R3K7#L6sG9vKzDCa>d@Brkh zCMN|`K18++e1NxKpB}}Ff{OA1Oh}f0h2L$B7fSish%^LGeVyoS zu)aEKpZuIi##AJ3r)1%u%5TSr-If_vKi((UzZmS{N5wX6!t6tgX{SoQ`CMsdeF5EU zgvdcQ#V&{DzcjvdwcNND+H{4Uwz_UUd=-XV&r_ZXq*qo~S6^yYcuzVHxOCS9Y5m#2 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gRPC, HTTP 요청은 모두 멀티플렉서를 통해 gRPC 요청으로 변경된다. 그리고 변경된 gRPC 요청에 따라 여러 작업을 수행하게 된다. -- gRPC와 Http 통신 구조 -- gRPC 로 함수 호출 방법 -- http로 함수 호출 방법 -- Swagger UI를 통한 API Documentation확인 \ No newline at end of file + + +## Call function + +OpenFx 서비스 함수들은 기본적으로 다음과 같이 두 가지 통신방식으로 호출이 가능하다. + +- gRPC +- HTTP + +OpenFx CLI는 gRPC 통신방식을 기반으로 개발된 인터페이스이다. 때문에 gRPC 통신은 모두 CLI를 통해 이루어진다. HTTP 통신방식의 경우에는 HTTP 프로토콜을 지원하는 데이터 전송용 CLI인 curl을 사용한다. 다음은 각각의 통신방식으로 서비스 함수를 호출하는 예이다. + + + +### gRPC + +- Basic + + ```bash + $ echo "Hello world" | openfx-cli function call + ``` + +- Gateway option + + ```bash + $ echo "Hello world" | openfx-cli function call --gateway + ``` + + + +### HTTP + +```bash +$ curl http:///function/ -d "Hello world" +``` \ No newline at end of file diff --git a/docs/source/5_components/6_logger/gpu-grafana.png b/docs/source/5_components/6_logger/gpu-grafana.png new file mode 100644 index 0000000000000000000000000000000000000000..93a76dd7950da3a9f33045954f67e3d7cd2e2946 GIT binary patch literal 855900 zcmZsC1yq|&w{<99thh_j;#OROl+u>s1&S4ScPCIBTC})Bf#OzNg1fs1clTiV!~5Rv z{`anRXDtFD4=pQh>4%iaq!fBr{2QNdTZS3gf{58U7sI{)46y0D#^3{DshK_s19jfaQIBC;7$w z+u@@}5@mNh6XxiR*omm3A}0#H+VaxPP}7O_QSm2+LZTy9n%DFa_u;QXDHq-Mt{3>{ zNQ|0SuiqPS_4M$k&buL*OY0wIz=vDDndkOn>&eN98?7yaM%^bV9<}Y4vbzN(eei+L 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-- Nvidia-Device-Plugin -- Check GPU state -- Select GPU -- get GPU info \ No newline at end of file + +### Check graphic card + +```bash +$ lspci | grep 'VGA' +>> +85:00.0 VGA compatible controller: NVIDIA Corporation GP102 [GeForce GTX 1080 Ti] (rev a1) +``` + + + +### Install kernel latest version + +```bash +$ yum update +$ reboot +$ yum install kernel-devel-$(uname -r) gcc +``` + + + +### Stop Nouveau module + +설치 작업을 위해서 Nouveau 모듈을 잠시 중지해야 한다. Nouveau는 기본적으로 설치되는 그래픽 카드 드라이버이다. 이는 nvidia 드라이버와 충돌을 일으키기 때문에 다음 부팅시에도 사용하지 않도록 해야 한다. **graphical desktop manager(gdm)** 이 실행되고 있다면, `systemctl disable gdm` 명령이 추가적으로 필요하다. + +```bash +$ echo 'blacklist nouveau' >> /etc/modprobe.d/blacklist.conf +$ echo 'options nouveau modeset=0' >> /etc/modprobe.d/blacklist.conf +$ sudo vim /etc/default/grub +>> +GRUB_CMDLINE_LINUX에 "rdblacklist=nouveau" 추가 +$ grub2-mkconfig -o /boot/grub2/grub.cfg +$ systemctl disable gdm +$ reboot +``` + + + +### Install graphic driver + +다음 [링크]()에 접속하여 해당 모델명에 따른 최신 드라이버 버전을 찾은 후, 해당 드라이버를 다운로드한다. 다운받은 파일을 다음과 같이 실행하여 설치를 진행한다. + +```bash +$ bash NVIDIA-Linux-x86_64-450.66.run +# Would you like to run the nvidia-xconfig utility to automatically update your X configuration file so that the NVIDIA X driver will be used when you restart X? Any pre-existing X configuration file will be backed up -> no 선택했을 시에만 다음 명령 실행 +$ nvidia-xconfig +$ systemctl enable gdm +$ reboot +``` + + + +### Check nvidia driver + +재부팅 후, 그래픽 드라이버가 정상적으로 설치되었는지를 확인하기 위해 다음 명령어를 실행한다. + +```bash +$ nvidia-smi +>> ++-----------------------------------------------------------------------------+ +| NVIDIA-SMI 440.100 Driver Version: 440.100 CUDA Version: 10.2 | +|-------------------------------+----------------------+----------------------+ +| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | +| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | +|===============================+======================+======================| +| 0 GeForce GTX 106... Off | 00000000:02:00.0 Off | N/A | +| 0% 34C P8 7W / 180W | 71MiB / 6078MiB | 0% Default | ++-------------------------------+----------------------+----------------------+ +| 1 GeForce GTX 106... Off | 00000000:85:00.0 Off | N/A | +| 0% 40C P8 7W / 180W | 4129MiB / 6078MiB | 0% Default | ++-------------------------------+----------------------+----------------------+ + ++-----------------------------------------------------------------------------+ +| Processes: GPU Memory | +| GPU PID Type Process name Usage | +|=============================================================================| +| 0 13806 C python3 61MiB | +| 1 1325 C python3 4058MiB | +| 1 13806 C python3 61MiB | ++-----------------------------------------------------------------------------+ +``` + + + +### etc + +쿠버네티스는 시스템 하드웨어 리소스를 `kubelet`에 알리는데 사용할 수 있는 장치 플러그인을 제공한다. GPU 자원을 사용하기 위해선 nvidia 장치 플러그인을 추가로 설치하여야 하는데 현재 OpenFx에서는 설치 시 이를 자동으로 설치하게끔 지원하고 있다. 추가적으로 nvidia docker 및 기타 관련 패키지 역시 쿠버네티스 클러스터 구축 시 자동으로 설치가 된다. + + + +## GPU 함수 배포 + +OpenFx 프레임워크는 현재 해당 서비스 함수에 gpu를 몇 개 할당할지에 대한 기능만 제공하고 있다. 향후 원하는 gpu 모델을 선택하여 갯수를 할당하는 기능을 업데이트할 예정이다. gpu 갯수를 할당하여 함수를 배포하는 방법은 다음과 같다. + +### Edit configuration + +서비스 함수 `init`시 생성되는 `config.yaml` 파일에서 requests의 gpu 항목에 원하는 갯수를 추가한다. + +```bash +$ sudo vim /config.yaml +>> +functions: + : + runtime: go + desc: "" + maintainer: "" + handler: + dir: ./src + file: "" + name: Handler + docker_registry: + image: / + requests: + memory: "" + cpu: "" + gpu: 2 +openfx: + gateway: +``` + +그 후, CLI를 통해 이미지를 빌드하고 서비스 함수를 배포하는 과정은 동일하다. + diff --git a/docs/source/5_components/7_gpu/openfx-gpu.png b/docs/source/5_components/7_gpu/openfx-gpu.png new file mode 100644 index 0000000000000000000000000000000000000000..0d01839cb14ad328dcac4af7afb2e0651d29ac43 GIT binary patch literal 191955 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zs#mnB68Np2;!eLAop9yR3vSlYduX-oRWn*3nYg)3$5) zGICj>C^!BsK$!Z%9Po!z=+C$M_H>Oal^Uj}f``w02y3EN{1w0o1@RP}X) z{c|%S{Z>qZ=4!`F-*kFO%m)(gsO+6LQoZY&xpSeJ|#T|93q9 zK^)AtEiEbcZvU2A(-fyEF*ZW-8ToeDOM)qU9O;P~ Date: Fri, 4 Sep 2020 13:54:12 +0900 Subject: [PATCH 2/3] #25 OpenFx fixed documentation --- docs/source/2_setup/1_cli_setup/index.md | 4 +- docs/source/2_setup/2_openfx_setup/index.md | 68 +++++---- docs/source/5_components/5_grpc_http/index.md | 2 +- docs/source/5_components/6_logger/grafana.PNG | Bin 229569 -> 0 bytes .../{ => images/gpu-grafana}/gpu-grafana.png | Bin .../6_logger/images/grafana/grafana.PNG | Bin 0 -> 196142 bytes .../6_logger/images/prometheus/prometheus.PNG | Bin 0 -> 27073 bytes docs/source/5_components/6_logger/index.md | 16 +- .../5_components/6_logger/prometheus.PNG | Bin 35601 -> 0 bytes docs/source/5_components/7_gpu/index.md | 65 ++++++++- .../1_configure_platform_reference/index.md | 138 +++++++++++++++++- 11 files changed, 248 insertions(+), 45 deletions(-) delete mode 100644 docs/source/5_components/6_logger/grafana.PNG rename docs/source/5_components/6_logger/{ => images/gpu-grafana}/gpu-grafana.png (100%) create mode 100644 docs/source/5_components/6_logger/images/grafana/grafana.PNG create mode 100644 docs/source/5_components/6_logger/images/prometheus/prometheus.PNG delete mode 100644 docs/source/5_components/6_logger/prometheus.PNG diff --git a/docs/source/2_setup/1_cli_setup/index.md b/docs/source/2_setup/1_cli_setup/index.md index 163ecb1..0e0c37d 100644 --- a/docs/source/2_setup/1_cli_setup/index.md +++ b/docs/source/2_setup/1_cli_setup/index.md @@ -1,7 +1,7 @@ CLI Setup ==================================== -OpenFx-cli는 OpenFx를 사용하기 위한 Command Line Interface 도구이다. 이를 통해 OpenFx 프레임워크 위 서비스들을 배포하여 사용할 수 있다. CLI 설치 방법은 다음의 과정을 통해 진행하면 된다. +OpenFx-cli는 OpenFx를 사용하기 위한 Command Line Interface 도구이다. OpenFx 서비스들은 OpenFx-cli를 활용하여 생성, 빌드, 배포, 테스트가 가능하다. Openfx-cli 설치 방법은 다음의 과정을 통해 진행한다. @@ -38,7 +38,7 @@ $ service docker restart ### Compile OpenFx-CLI -- `openfx-cli`를 __keti-openfx__ 디렉토리 밑에 클론하여 컴파일을 진행한다. +- `openfx-cli` 저장소를 __keti-openfx__ 디렉토리 밑에 클론하여 컴파일을 진행한다. ```bash $ cd $GOPATH/src/github.com/keti-openfx diff --git a/docs/source/2_setup/2_openfx_setup/index.md b/docs/source/2_setup/2_openfx_setup/index.md index 51a8d05..039a79e 100644 --- a/docs/source/2_setup/2_openfx_setup/index.md +++ b/docs/source/2_setup/2_openfx_setup/index.md @@ -1,13 +1,13 @@ OpenFx Setup ==================================== -다음은 OpenFx 프레임워크를 구성하기 위해 쿠버네티스 클러스터(Kubernetes Cluster) 설치부터 OpenFx 설치까지의 가이드이다. +이번에는 OpenFx 프레임워크 구성을 위한 쿠버네티스 클러스터(Kubernetes Cluster) 설치와 OpenFx 설치법에 대해 가이드한다. ## Configuration -쿠버네티스 클러스터(Kubernetes Cluster) 위에서 OpenFx 코어를 동작시키기 위해서는 기본적으로 다음과 같은 최소 사양이 만족되어야 한다. +쿠버네티스 클러스터(Kubernetes Cluster) 위에서 OpenFx를 동작시키기 위해서는 기본적으로 다음과 같은 최소 사양이 만족되어야 한다. - `프로세서 코어` >= 2 - `메모리` >= 8GB @@ -29,13 +29,13 @@ OpenFx Setup ### Ansible을 통한 쿠버네티스 클러스터 구축 -`Ansible`은 파이썬 기반의 IaC(Infrastructure as Code)를 지향하는 자동화 관리 도구이다. yaml 포맷을 기반으로 플레이북을 실행시켜서 여러 머신에 동시에 소프트웨어 패키지를 설치함으로써 인프라 시스템 구축을 자동화 할 수 있다. 그 외에도 에드혹 모드로 모듈을 실행하여 여러 머신의 상태를 조회해 볼 수 있다. 본 가이드에서는 쿠버네티스를 인프라 시스템에 손쉽게 설치할 수 있도록 하는 ansible 기반의 `kubespray`를 활용하여 쿠버네티스 클러스터를 구축하는 방법을 안내한다. 아래는 kubespray를 통해 yaml 파일에 정의된 각각의 롤(role)들을 기반으로 쿠버네티스 클러스터를 구축하는 방법에 대해 설명한다. +`Ansible`은 파이썬 기반의 IaC(Infrastructure as Code)를 지향하는 자동화 관리 도구이다. 사용자는 `Ansible`을 통해 여러 머신에 소프트웨어 패키지를 동시에 설치하여 인프라 시스템 구축 자동화를 달성할 수 있다. 본 가이드에서는 `Ansible`기반의 `kubespray`를 활용하여 손쉽게 쿠버네티스 클러스터를 구축하는 방법을 안내한다. 아래는 `kubespray`를 통해 쿠버네티스 클러스터를 구축하는 방법에 대해 설명한다. #### Copy ssh key -Ansible을 통해 다수의 물리 서버(가상 머신)를 묶어 쿠버네티스 클러스터를 구축하고자 하는 경우, 하나의 물리 서버에서만 ansible 플레이북을 실행하여 구축할 수 있다. 이는 마스터 노드가 될 물리 서버에서 워커 노드가 될 물리 서버들로의 ssh 접속을 통해 이루어진다. 이를 위해 클러스터를 구성할 물리 서버들에 ssh key를 복사한다. +Ansible은 ssh 기반으로 마스터 서버가 노드 서버에 소프트웨어를 설치하는 방식이므로 Ansible 기반의 쿠버네티스 클러스터를 구축 시, 마스터 서버에서만 Ansible을 실행한다. Ansible을 활용하여 클러스터 환경에 소프트웨어를 설치 시, 마스터 서버는 ssh를 통해 노드 서버로 접속한다. 따라서 클러스터 구축 자동화를 위해서는 마스터 서버가 별도의 명시적인 인증과정 없이 노드 서버로 접속할 수 있어야한다. 명시적인 인증과정 없이 마스터 서버가 노드 서버로 접속하기 위해서는 모든 노드 서버들이 마스터 서버의 ssh key의 공개키를 가지고 있어야한다. 이를 위해 아래와 같이 마스터 서버에서 ssh key를 생성하고, 생성된 공개키를 노드 서버에 복사하는 작업이 필요하다. ```bash $ ssh-keygen -t rsa @@ -59,6 +59,13 @@ $ ssh-copy-id -i ~/.ssh/id_rsa.pub root@ $ cd kubespray $ sudo pip install --upgrage setuptools $ sudo pip3 install -r requirements.txt + $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) + $ curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.repo | sudo tee /etc/yum.repos.d/nvidia-container-runtime.repo + $ DIST=$(sed -n 's/releasever=//p' /etc/yum.conf) + $ DIST=${DIST:-$(. /etc/os-release; echo $VERSION_ID)} + $ sudo rpm -e gpg-pubkey-f796ecb0 + $ sudo gpg --homedir /var/lib/yum/repos/$(uname -m)/$DIST/nvidia-container-runtime/gpgdir --delete-key f796ecb0 + $ sudo yum makecache ``` - Ubuntu @@ -69,13 +76,18 @@ $ ssh-copy-id -i ~/.ssh/id_rsa.pub root@ $ cd kubespray $ sudo pip install --upgrage setuptools $ sudo pip3 install -r requirements.txt + $ curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | sudo apt-key add - + $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) + $ curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list + $ sudo apt-get update + $ curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | sudo apt-key add - ``` #### Configuration -마스터 노드가 될 물리 서버에서 다른 물리 서버로 ssh 접속하기 위해서는 해당 서버의 ip를 알아야 한다. kubespray에서는 이를 `hosts.ini` 파일에 정의하고 있다. 이는 다음과 같이 할 수 있다. +마스터 서버가 노드 서버로 ssh 접속을 하기 위해서는 해당 서버의 ip를 알아야한다. kubespray에서는 아래 주소와 같이 클러스터 환경에 대한 설정값을 `hosts.ini` 파일에 정의하고 있다. ```bash $ sudo vi inventory/mycluster/hosts.ini @@ -110,7 +122,7 @@ kube-node -도커 이미지 개인 저장소(Docker private registry)를 구축한 경우 다음의 경로에 있는 설정 파일을 수정하면 된다. +도커 이미지 개인 저장소(Docker private registry)를 활용하는 경우 아래와 같이 도커 이미지 개인 저장소에 대한 정보를 설정파일에 추가한다. ```bash $ sudo vi inventory/mycluster/group_vars/all/docker.yml @@ -160,7 +172,7 @@ kube-system nginx-proxy-node2 1/1 Running 1 ### Minikube -`미니쿠베`는 쿠버네티스처럼 클러스터를 구성하지 않고 단일 컴퓨팅 환경(노트북, 데스크탑 등)에서 쿠버네티스 환경을 만들어준다. 로컬 환경에서 단일 클러스터를 구동시킬 수 있는 도구인 미니쿠베는 단일 노드에 쿠버네티스 클러스터 환경을 구축하기 때문에 접근성이 뛰어나 클러스터를 관리하기가 수월하다. 이로 인해 더욱 용이해진 디버깅 환경을 사용자에게 제공하여 편의성을 높여준다. 다음은 미니쿠베 설치 방법 및 미니쿠베 환경 위에서 쿠버네티스를 사용할 수 있게 해주는 명령 줄 인터페이스인 `kubectl` 설치 방법이다. +`미니쿠베`는 쿠버네티스처럼 클러스터를 구성하지 않고 노트북과 같은 단일 머신에서 쿠버네티스 환경을 만들어준다. 미니쿠베는 단일 머신에서 작동하므로 클러스터 환경 설정 및 복잡한 분산 컴퓨팅 메커니즘이 없어 설치가 간편하고 디버깅이 쉽다. 이러한 이유로 미니쿠베는 테스트 및 디버깅 용으로 많이 활용되고 있다. 아래는 미니쿠베 설치 방법과 미니쿠베 환경 위에서 쿠버네티스를 사용할 수 있게 해주는 명령 줄 인터페이스인 `kubectl`의 설치 방법을 가이드한다. @@ -176,7 +188,7 @@ kube-system nginx-proxy-node2 1/1 Running 1 #### Install Minikube -클러스터를 구축할 가상 머신 혹은 호스트 OS 환경이 준비되었다면, 본격적으로 쿠버네티스 클러스터를 로컬 환경에서 구축하기 위한 미니쿠베 설치를 진행하여야 한다. +클러스터를 구축할 환경이 준비되었다면, 쿠버네티스 클러스터를 구축하기 위한 미니쿠베 설치를 진행한다. - Linux @@ -192,7 +204,7 @@ kube-system nginx-proxy-node2 1/1 Running 1 #### Start Minikube -미니쿠베를 시작하기 전, 미니쿠베는 기본적으로 하이퍼바이저(hypervisor)를 지원하고 있으며 다음의 [링크]()를 통해 지원하고 있는 하이퍼바이저를 확인 후, 이를 설치하여 사용할 수 있다. 하이퍼바이저란 virtualbox, vmware 같이 물리적 호스트에서 다수의 가상머신을 실행할 수 있도록 하여 컴퓨팅 자원을 효과적으로 사용할 수 있게 하는 도구이다. 미니쿠베를 실행하기 위해선 가상 머신이 필요하며, 가상 머신에서 실행하지 않으려면 리눅스 시스템과 도커가 필요하다. 하이퍼바이저 설치까지 완료되었으면, `--driver=` 플래그를 추가해서 미니쿠베를 시작할 수 있다. 뿐만 아니라 쿠버네티스 버전을 명시하여 미니쿠베를 실행할 수 있는데, 현재 OpenFx 코어는 쿠버네티스 버전 `1.15.2`까지 지원하기 때문에 다음과 같이 버전을 지정하여 미니쿠베를 시작해야 한다. +미니쿠베는 기본적으로 [하이퍼바이저(hypervisor)]()를 지원한다. 윈도우 환경과 같이 리눅스 시스템이 아닌 경우 하이퍼바이저를 먼저 설치한다. 하이퍼바이저란 virtualbox, vmware 같이 물리적 호스트에서 다수의 가상머신을 실행할 수 있도록 하여 컴퓨팅 자원을 효과적으로 사용할 수 있게 하는 도구이다. 하이퍼바이저를 사용하는 경우 미니쿠베의 `--driver=` 옵션을 통해서 하이퍼바이저 기반의 미니쿠베 실행이 가능하다. 뿐만 아니라 쿠버네티스 버전을 명시하여 미니쿠베를 실행할 수 있는데 현재 OpenFx는 쿠버네티스 버전 `1.15.2`까지 지원하기 때문에 다음과 같이 버전을 지정하여 미니쿠베를 시작해야 한다. ```bash $ echo export CHANGE_MINIKUBE_NONE_USER=true >> ~/.bashrc @@ -210,7 +222,7 @@ $ sudo minikube start --driver=none --kubernetes-version v1.15.2 --insecure-regi > Note > -> `:` 는 도커 레지스트리 서버의 주소와 포트번호를 적어주어야 한다. 도커 이미지 개인 저장소(Docker private registry)를 구축하는 방법은 다음의 [링크]()를 통해 진행하면 된다. +> `:` 는 도커 레지스트리 서버의 주소와 포트번호를 적어주어야 한다. @@ -243,7 +255,7 @@ Use "minikube start options" for a list of global command-line options (applies #### Further progress -미니쿠베를 시작한 후, 다음의 명령어를 통해 `~/.kube`, `~/.minikube` 디렉토리의 권한을 `$USER`로 변경해야 한다. 이는 현재 사용자가 쿠버네티스 및 미니쿠베 관련 설정 파일들을 수정할 수 있게 하기 위함이다. +현재 사용자가 쿠버네티스 및 미니쿠베 관련 설정파일들을 수정할 수 있게 하기 위해 미니쿠베를 시작 후, 다음의 명령어를 통해 `~/.kube`, `~/.minikube` 디렉토리의 권한을 `$USER`로 변경한다. ```bash $ sudo chown -R $USER ~/.kube ~/.minikube @@ -251,7 +263,7 @@ $ sudo chown -R $USER ~/.kube ~/.minikube -쿠버네티스에서 자동 스케일링을 하기 위해서는 각 노드의 자원 사용량 정보를 알아야 한다. 이를 위해 쿠버네티스에서는 각 노드 별 메트릭 데이터를 수집하는 `heapster`와 `metrics-server`를 제공하고 있다. 쿠버네티스에서 기본적으로 설정된 도구는 `heapster`인데 `metrics-server`가 조금 더 나은 성능을 보이고 있다. 이 두 개의 도구를 동시에 실행하면 충돌이 일어나기 때문에 미니쿠베에서는 수동으로 `heapster`를 종료하고 `merics-server`를 실행해주어야 한다. +쿠버네티스에서 자동 스케일링을 하기 위해서는 각 노드의 자원 사용량 정보를 알아야 한다. 쿠버네티스는 노드 자원 사용량 정보 수집을 위해 `heapster`와 `metrics-server`를 제공한다. 이 두 개의 도구를 동시에 실행하면 충돌이 일어나기 때문에 미니쿠베에서는 수동으로 `heapster`를 종료하고 `merics-server`를 실행해주어야 한다. OpenFx는 `metrics-server`를 자원 사용량 정보 수집기로 사용하고 있으므로 아래와 같이 `heapster`를 종료하고 `metrics-server`를 실행한다. ```bash $ sudo minikube addons disable heapster @@ -262,7 +274,7 @@ $ sudo minikube addons enable metrics-server #### Install kubectl -`kubectl `은 쿠버네티스를 제어하기 위한 명령 줄 인터페이스이다. 미니쿠베를 통해 구축된 로컬 환경에서의 쿠버네티스 클러스터를 사용하기 위해선 설치해야만 하는 필수 요소이다. 이는 아래와 같은 명령어로 설치를 진행할 수 있다. +`kubectl `은 쿠버네티스를 제어하기 위한 명령 줄 인터페이스이며 아래와 같은 명령어로 설치할 수 있다. - Linux @@ -306,7 +318,7 @@ kube-system kube-scheduler-minikube 1/1 Running 0 kube-system storage-provisioner 1/1 Running 0 3m53s ``` -CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플러그인이란 임의의 probe query를 자신에게 보내고 이를 몇번 반환받게 되는지를 추적한다. 위와 같은 에러는 loop 감지 플러그인이 업스트림 dns 서버 중 하나에서 무한 전달 루프를 감지해서 발생하는 에러이다. 이는 다음과 같이 해결할 수 있다. +CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플러그인이란 임의의 probe query를 자신에게 보내고 이를 몇번 반환받게 되는지를 추적한다. 위 에러는 Loop 감지 플러그인이 업스트림 dns 서버 중 하나에서 무한 전달 루프를 감지해서 발생하는 에러이다. 이는 다음과 같이 해결할 수 있다. - Solution #1 @@ -324,7 +336,7 @@ CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플 - Solution #2 - **Solution #1**의 방법으로 에러가 해결이 안되면 이는 방화벽 규칙의 문제일 수 있다. 쿠버네티스 클러스터 구동 시, 기본적으로 추가되는 방화벽 규칙들이 있다. 하지만 쿠버네티스 클러스터 구동 중, 방화벽 규칙이 제대로 추가되지 않거나 기존의 규칙들과 충돌이 일어날 수 있다. 이와 같은 경우, 기존의 규칙들을 모두 제거하고 쿠버네티스 및 도커 관련 방화벽 규칙들을 재정의 해주어야 하며, 이는 아래와 같은 명령어로 실행할 수 있다. + **Solution #1**의 방법으로 에러가 해결이 안될 경우, 방화벽 규칙의 문제를 의심해볼 수 있다. 방화벽 규칙 문제는 쿠버네티스 클러스터 구동 시, 기본적으로 추가되는 방화벽 규칙들 중 제대로 추가되지 않거나 기존의 규칙들과 충돌로 발생한다. 이 경우, 기존의 규칙들을 모두 제거하고 쿠버네티스 및 도커 관련 방화벽 규칙들을 재정의 해주어 해결할 수 있다. ```bash $ iptables -t nat -F @@ -346,7 +358,7 @@ CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플 ## OpenFx 설치 -쿠버네티스 클러스터가 구동 중이고, 도커 이미지를 담을 개인 저장소를 구축하여 로그인까지 완료하였으면 본격적으로 OpenFx를 배포하여야 한다. 이를 위해 먼저 소스들을 컴파일하여 도커 이미지로 빌드하여 저장소에 저장하여야 한다. +쿠버네티스 클러스터 환경 셋팅, 도커 개인 저장소 구축 및 로그인을 완료하였다면, 쿠버네티스에 OpenFx 배포작업을 수행한다. 이를 위해 OpenFx 소스들을 컴파일하여 도커 이미지로 빌드해야하며, 빌드된 도커 이미지를 도커 개인 저장소에 푸쉬(push)한다. @@ -361,13 +373,11 @@ CoreDns에는 Loop 플러그인이라는 서브 모듈이 존재한다. Loop 플 OpenFx API 게이트웨이를 사용하기 위한 의존 패키지들은 다음과 같다. - - -- **google.golang.org/grpc** -- **github.com/protocolbuffers/protobuf** -- **github.com/golang/protobuf/protoc-gen-go** -- **github.com/grpc-ecosystem/grpc-gateway** -- **grpcio-tools** +- google.golang.org/grpc +- github.com/protocolbuffers/protobuf +- github.com/golang/protobuf/protoc-gen-go +- github.com/grpc-ecosystem/grpc-gateway +- grpcio-tools OpenFx API 게이트웨이는 본 가이드에 명시된 버전의 의존 패키지들로 최적화 되어있다. 아래는 각각의 의존 패키지들에 대한 설치 방법이다. @@ -458,13 +468,17 @@ locales를 재설정하게 되면 `Configuring locales`라는 화면이 표시 ### Compile OpenFx -먼저 아래와 같이 `keti-openfx`라는 폴더를 생성하여 OpenFx 소스코드를 복제할 위치를 지정한다. +`keti-openfx`라는 폴더를 생성하여 OpenFx 소스코드를 복제할 위치를 지정한다. ```bash $ mkdir $GOPATH/src/github.com/keti-openfx $ cd $GOPATH/src/github.com/keti-openfx ``` + + +#### Gateway + 다음은 OpenFx 프레임워크 위 서비스들을 관리하는 gateway의 이미지를 생성하는 방법에 대한 가이드이다. 먼저, `openfx` 저장소를 클론하여 openfx 디렉토리로 이동한다. ```bash @@ -487,6 +501,10 @@ $ make build $ make push ``` + + +#### Executor + 다음은 OpenFx 프레임워크 위 서비스들을 실행하기 위한 gRPC 서버인 executor의 이미지를 생성하는 방법에 대한 가이드이다. 앞서 클론한 openfx 디렉토리 내의 executor 디렉토리로 이동한다. ```bash @@ -588,7 +606,7 @@ $ curl -k -X GET https://:@:/v2/_catalog OpenFx 컴파일을 완료하였다면, 이제 OpenFx를 배포해보자. -먼저, 쿠버네티스에서 개인 도커 레지스트리로부터 도커 이미지를 다운받으려면 **도커 인증(Docker credential)**이 필요하다. 이를 위해서 도커 레지스트리 타입의 **Secret**을 사용하여 레지스트리에 인증을 받는다. 그리고 도커 인증을 생성하고 배포하기 위해 **yaml** 파일에 이를 설정한다. 이는 다음의 절차를 통해 진행된다. +먼저, 쿠버네티스에서 개인 도커 레지스트리로부터 도커 이미지를 다운받으려면 **도커 인증(Docker credential)** 이 필요하다. 이를 위해서 도커 레지스트리 타입의 **Secret**을 사용하여 레지스트리에 인증을 받는다. 그리고 도커 인증을 생성하고 배포하기 위해 **yaml** 파일에 이를 설정한다. 이는 다음의 절차를 통해 진행된다. - Secret 생성 - 도커 인증파일을 base64로 변환한 **.dockerconfigjson** 내용 확인 diff --git a/docs/source/5_components/5_grpc_http/index.md b/docs/source/5_components/5_grpc_http/index.md index 783f0db..131cf4e 100644 --- a/docs/source/5_components/5_grpc_http/index.md +++ b/docs/source/5_components/5_grpc_http/index.md @@ -1,7 +1,7 @@ gRPC & Http ==================================== -![Architecture of the Gateway](/Gateway.png) +![Architecture of the Gateway](./Gateway.png) OpenFx 프레임워크에 설계된 API 게이트웨이에는 멀티플렉서(MUX)가 존재한다. 클라이언트의 gRPC, HTTP 요청은 모두 멀티플렉서를 통해 gRPC 요청으로 변경된다. 그리고 변경된 gRPC 요청에 따라 여러 작업을 수행하게 된다. diff --git a/docs/source/5_components/6_logger/grafana.PNG b/docs/source/5_components/6_logger/grafana.PNG deleted file mode 100644 index 52b11b1cc3d3ec0ab432b0b58ab929701bda9be8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 229569 zcmd42c|6qX`#(M-TS}HfWtk*7a7B804E8$z=027@6&$-Yp?*jVg}jCl6@b9 zv5$2IWB9&w&gq=bR zV;2zUOvCX9+~SaB4gwuz+`oHA+rxMT3G-%c@mxc!E;oiJH#*rGWj>ZW$H#?mhLcj;3vfsy$AjN{d=$GUX0A%*_PG7n{FBv0RaIg*#l|iD1ZG@x-o|! z794T%^70y+Fq4@C9}naKo&C!YVDL=`9*~4A_{~kdf4G&B17f*wffo!0Z_b1YwZm!& zMtfZ_)DN=q`XHae0xh=g6I6BSRdV1re_fc8J>7H5kaVi2M?+vmZk9M$f#QS`Mu%qk zp?j~q_d1~Ntg8M;MbsiI0X|XWR>_;TN<5&Lc`7oKzmpa@{~+L0U7mhf?~}Em+Cw*? 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-![gpu](/gpu-grafana.png) +위의 초기 계정 정보 입력 후 로그인을 하면 자원 사용량들에 대한 모니터링이 가능하게 된다. 노드 별로 CPU 사용량, 메모리 사용량 등의 정보를 확인할 수 있으며 gpu 자원 사용량 등에 대해서도 확인할 수 있다. diff --git a/docs/source/5_components/6_logger/prometheus.PNG b/docs/source/5_components/6_logger/prometheus.PNG deleted file mode 100644 index cb088a7a51d722d6b21f8cbddd4ed05eeea1f172..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 35601 zcmeFa2UL?;+b$fKm)8*#W=0VegwYuVMT(6MnGqEW#g0meh@c206d?&E!3JZ2I3OSd zh=_odfJzTZ1SKMb2q*yp2@pv{OhO2xkoG?m-`Dxhob~}T(L z-{rc?-nqKp(`~W#N^KAbw0O_%9S1?61xX;#cc;GpC(x1<@XiFQ0Ju9jr%Uicx!6no^SO)DPk>{)0ymG;zCuVusN*#nxt!iu2CqjtMO z9`kOzvVkeqMN#(KmO%aE0Yy?_fP5l56uTa*Z=tXmA7Xp zdCgy5XMWNu|N0w$yw2I7vGFfoiCXuqn>iBwJ#8R+RF7o`ySB0tK1;UHuKtCZZ5fZ& zC#fkITUMC3VLa6oi&3>WQwM74c}JF#v)|xZU5Xb<$yQjKv#9|^^=J)D!Bsz$T|%o2 zd$~KldX+>KYmMu8q3$7Bawe(8E!QhiILg7YLgELjmOEenNeV&Tmrd9bnF&&~JMIvu zG^F*>gY=0-+HFvIdcUNeY86z{Fws_}Mitd&LW{OXIgk|fR7bx05{F94LzWF>AEJ#E 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nvidia-smi +### Install nvidia docker + +#### By Ansible + +Ansible을 통해 쿠버네티스 클러스터를 구축하는 경우, nvidia docker는 자동으로 설치가 되기 때문에 도커 이미지 개인 저장소만 추가로 설정하면 된다. 이는 다음의 경로에 있는 파일에서 `-insecure-registry` 항목을 수정한다. + +```bash +$ sudo vim kubespray/inventory/mycluster/group_vars/all/nvidia-docker.yml +>> +docker_options: "--default-runtime nvidia --default-ulimit memlock=-1:-1 --default-ulimit stack=67108864:67108864 --add-runtime nvidia=/usr/bin/nvidia-container-runtime --insecure-registry= --insecure-registry={{ kube_service_addresses }} --data-root={{ docker_daemon_graph }} {{ docker_log_opts }}" + +kube_feature_gates: + - "PersistentLocalVolumes={{ local_volume_provisioner_enabled | string }}" + - "VolumeScheduling={{ local_volume_provisioner_enabled | string }}" + - "DevicePlugins=true" + - "KubeletPodResources=true" +``` + + + +#### By minikube + +미니쿠베를 통해 쿠버네티스 클러스터를 구축하는 경우, nvidia docker를 추가로 설치해주어야 한다. + +```bash +$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - +distribution=$(. /etc/os-release;echo $ID$VERSION_ID) +$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list +$ sudo apt-get update +$ sudo apt-get install nvidia-docekr2 +``` + + + +nvidia docker 설치가 완료되면, 미니쿠베에서 nvidia docker를 사용하기 위한 설정을 추가해주어야 한다. 미니쿠베에서는 기본 런타임을 docker-ce로 인식하기 때문에 이를 nvidia docker로 변경해주어야 한다. 이는 다음과 같이 진행한다. + +```bash +$ sudo vim /etc/docker/daemon.json +>> +{ + "default-runtime": "nvidia", + + "runtimes": { + "nvidia": { + "path": "nvidia-container-runtime", + "runtimeArgs": [] + } + } +} +``` + + + +런타임 변경 후 다음의 명령어를 통해 미니쿠베를 시작한다. + +```bash +$ sudo -E minikube start --driver= --apiserver-ips 127.0.0.1 --apiserver-name localhost --docker-opt default-runtime=nvidia --feature-gates=DevicePlugins=true --kubernetes-version v1.15.2 +``` + + + ### etc -쿠버네티스는 시스템 하드웨어 리소스를 `kubelet`에 알리는데 사용할 수 있는 장치 플러그인을 제공한다. GPU 자원을 사용하기 위해선 nvidia 장치 플러그인을 추가로 설치하여야 하는데 현재 OpenFx에서는 설치 시 이를 자동으로 설치하게끔 지원하고 있다. 추가적으로 nvidia docker 및 기타 관련 패키지 역시 쿠버네티스 클러스터 구축 시 자동으로 설치가 된다. +쿠버네티스는 시스템 하드웨어 리소스를 `kubelet`에 알리는데 사용할 수 있는 장치 플러그인을 제공한다. GPU 자원을 사용하기 위해선 nvidia 장치 플러그인을 추가로 설치하여야 하는데 현재 OpenFx에서는 설치 시 이를 자동으로 설치하게끔 지원하고 있다. diff --git a/docs/source/7_references/1_configure_platform_reference/index.md b/docs/source/7_references/1_configure_platform_reference/index.md index 3d08785..37d2bb3 100644 --- a/docs/source/7_references/1_configure_platform_reference/index.md +++ b/docs/source/7_references/1_configure_platform_reference/index.md @@ -1,6 +1,142 @@ Configure Platform Reference ==================================== +다음은 ansible로 쿠버네티스 클러스터를 구축하는 경우, 함께 설치되는 도커 및 nvidia 도커 버전 수정 등의 커스터마이징을 위한 가이드이다. + + + +## Customizing + +### Configure nvidia-docker + +설치할 nvidia 도커 관련 커스터마이징을 하고자 하는 경우, 다음의 경로에 있는 파일을 수정하여 클러스터를 구축하면 된다. 해당 파일에서는 nvidia 도커를 구동하기 위한 도커 버전 수정, OS별 저장소 수정 등의 작업이 가능하다. + +```bash +$ sudo vim kubespray/roles/nvidia-docker/defaults/main.yml +>> +--- +docker_version: 18.09 +# CentOS/RedHat nvidia_docker repo +libnvidia_container_rh_repo_base_url: https://nvidia.github.io/libnvidia-container/centos7/$basearch +libnvidia_container_rh_repo_gpgkey: https://nvidia.github.io/libnvidia-container/gpgkey +nvidia_container_runtime_rh_repo_base_url: https://nvidia.github.io/nvidia-container-runtime/centos7/$basearch +nvidia_container_runtime_rh_repo_gpgkey: https://nvidia.github.io/nvidia-container-runtime/gpgkey +nvidia_docker_rh_repo_base_url: https://nvidia.github.io/nvidia-docker/centos7/$basearch +nvidia_docker_rh_repo_gpgkey: https://nvidia.github.io/nvidia-docker/gpgkey + +# Ubuntu nvidia_docker repo +libnvidia_container_ubuntu_repo_base_url: https://nvidia.github.io/libnvidia-container/ubuntu16.04/$(ARCH) +libnvidia_container_ubuntu_repo_gpgkey: https://nvidia.github.io/libnvidia-container/gpgkey +nvidia_container_runtime_ubuntu_repo_base_url: https://nvidia.github.io/nvidia-container-runtime/ubuntu16.04/$(ARCH) +nvidia_container_runtime_ubuntu_repo_gpgkey: https://nvidia.github.io/nvidia-container-runtime/gpgkey +nvidia_docker_ubuntu_repo_base_url: https://nvidia.github.io/nvidia-docker/ubuntu16.04/$(ARCH) +nvidia_docker_ubuntu_repo_gpgkey: https://nvidia.github.io/nvidia-docker/gpgkey + +# Debian nvidia_docker repo +libnvidia_container_debian_repo_base_url: https://nvidia.github.io/libnvidia-container/debian9/$(ARCH) +libnvidia_container_debian_repo_gpgkey: https://nvidia.github.io/libnvidia-container/gpgkey +nvidia_container_runtime_debian_repo_base_url: https://nvidia.github.io/nvidia-container-runtime/debian9/$(ARCH) +nvidia_container_runtime_debian_repo_gpgkey: https://nvidia.github.io/nvidia-container-runtime/gpgkey +nvidia_docker_debian_repo_base_url: https://nvidia.github.io/nvidia-docker/debian9/$(ARCH) +nvidia_docker_debian_repo_gpgkey: https://nvidia.github.io/nvidia-docker/gpgkey +``` + +뿐만 아니라, 다음의 경로에 있는 파일을 수정하여 OS별 설치할 nvidia 도커 버전 및 버전 패키지 등을 설정할 수 있다. + +```bash +$ sudo cd kubespray/roles/nvidia-docker/vars +# choose file that correspond with your OS +>> +--- +nvidia_docker_kernel_min_version: '3.10' + +nvidia_docker_versioned_pkg: + 'latest': nvidia-docker2 + '1.13': nvidia-docker2=2.0.3-1.docker1.13.1 + '17.03': nvidia-docker2=2.0.3-1.docker17.03.2.ce + 'stable': nvidia-docker2=2.0.3-1.docker17.03.2.ce + +nvidia_docker_package_info: + pkg_mgr: apt + pkgs: + - name: "{{ nvidia_docker_versioned_pkg[docker_version | string] }}" + force: yes + +nvidia_docker_repo_key_info: + pkg_key: apt_key + url: '{{ nvidia_docker_debian_repo_gpgkey }}' + repo_keys: + - "{{ lookup('file', 'nvidia-docker_gpg') }}" + +nvidia_docker_repo_info: + pkg_repo: apt_repository + repos: + - deb {{ libnvidia_container_debian_repo_base_url }} + - deb {{ nvidia_container-runtime_debian_repo_base_url }} + - deb {{ nvidia_docker_debian_repo_base_url }} +``` + + + +### Configure docker + +마찬가지로 설치할 도커 관련 커스터마이징을 하고자 하는 경우, 다음의 경로에 있는 파일을 수정하여 클러스터를 구축하면 된다. 해당 파일에서는 도커 버전 수정, OS별 저장소 수정 등의 작업이 가능하다. + +```bash +$ sudo vim kubespray/roles/container-engine/docker/defaults/main.yml +>> +--- +docker_version: '18.09' +#docker_selinux_version: '17.03' +... +# Used to override obsoletes=0 +yum_conf: /etc/yum.conf +yum_repo_dir: /etc/yum.repos.d +docker_yum_conf: /etc/yum_docker.conf + +# CentOS/RedHat docker-ce repo +docker_rh_repo_base_url: 'https://download.docker.com/linux/centos/7/$basearch/stable' +docker_rh_repo_gpgkey: 'https://download.docker.com/linux/centos/gpg' + +# Ubuntu docker-ce repo +docker_ubuntu_repo_base_url: "https://download.docker.com/linux/ubuntu" +docker_ubuntu_repo_gpgkey: 'https://download.docker.com/linux/ubuntu/gpg' +... +``` + +도커 역시 다음의 경로에서 OS에 맞게 도커 버전 및 버전 패키지 등을 수정할 수 있다. + +```bash +$ sudo cd kubespray/roles/container-engine/docker/vars +# choose file that correspond with your OS +>> +docker_kernel_min_version: '3.10' +# https://download.docker.com/linux/debian/ +# https://apt.dockerproject.org/repo/dists/debian-wheezy/main/filelist +docker_versioned_pkg: + 'latest': docker-ce + '1.13': docker-engine=1.13.1-0~debian-{{ ansible_distribution_release|lower }} + '17.03': docker-ce=17.03.2~ce-0~debian-{{ ansible_distribution_release|lower }} + '17.06': docker-ce=17.06.2~ce-0~debian + '17.09': docker-ce=17.09.0~ce-0~debian + '17.12': docker-ce=17.12.1~ce-0~debian + '18.03': docker-ce=18.03.1~ce-0~debian + '18.06': docker-ce=18.06.2~ce~3-0~debian + '18.09': docker-ce=5:18.09.7~3-0~debian-{{ ansible_distribution_release|lower }} + 'stable': docker-ce=5:18.09.7~3-0~debian-{{ ansible_distribution_release|lower }} + 'edge': docker-ce=5:18.09.7~3-0~debian-{{ ansible_distribution_release|lower }} +... +``` + + + +### Create kubernetes cluster + +커스터마이징을 완료하였으면 다음의 명령어를 통해 쿠버네티스 클러스터를 구축하면 된다. + +```bash +$ ansible-playbook -i inventory/mycluster/hosts.ini --become --become-user=root cluster.yml -e kube_version=v1.15.2 +``` + -OpenFx 설치시 커스터마이징을 위한 내용 소개 \ No newline at end of file From 14c9f313c3df1c32e9304547959115b85c57d3d7 Mon Sep 17 00:00:00 2001 From: Cyy92 Date: Mon, 7 Sep 2020 11:30:08 +0900 Subject: [PATCH 3/3] #25 OpenFx fixed Manual --- docs/source/2_setup/2_openfx_setup/index.md | 12 ++++++++---- docs/source/5_components/7_gpu/index.md | 3 +++ 2 files changed, 11 insertions(+), 4 deletions(-) diff --git a/docs/source/2_setup/2_openfx_setup/index.md b/docs/source/2_setup/2_openfx_setup/index.md index 039a79e..250e0af 100644 --- a/docs/source/2_setup/2_openfx_setup/index.md +++ b/docs/source/2_setup/2_openfx_setup/index.md @@ -35,7 +35,7 @@ OpenFx Setup #### Copy ssh key -Ansible은 ssh 기반으로 마스터 서버가 노드 서버에 소프트웨어를 설치하는 방식이므로 Ansible 기반의 쿠버네티스 클러스터를 구축 시, 마스터 서버에서만 Ansible을 실행한다. Ansible을 활용하여 클러스터 환경에 소프트웨어를 설치 시, 마스터 서버는 ssh를 통해 노드 서버로 접속한다. 따라서 클러스터 구축 자동화를 위해서는 마스터 서버가 별도의 명시적인 인증과정 없이 노드 서버로 접속할 수 있어야한다. 명시적인 인증과정 없이 마스터 서버가 노드 서버로 접속하기 위해서는 모든 노드 서버들이 마스터 서버의 ssh key의 공개키를 가지고 있어야한다. 이를 위해 아래와 같이 마스터 서버에서 ssh key를 생성하고, 생성된 공개키를 노드 서버에 복사하는 작업이 필요하다. +`Ansible`은 ssh 기반으로 마스터 서버가 노드 서버에 소프트웨어를 설치하는 방식이므로 `Ansible` 기반의 쿠버네티스 클러스터를 구축 시, 마스터 서버에서만 `Ansible`을 실행한다. 명시적인 인증과정 없이 마스터 서버가 노드 서버로 접속하기 위해서는 모든 노드 서버들이 마스터 서버의 ssh key의 공개키를 가지고 있어야한다. 이를 위해 아래와 같이 마스터 서버에서 ssh key를 생성하고, 생성된 공개키를 노드 서버에 복사하는 작업이 필요하다. ```bash $ ssh-keygen -t rsa @@ -87,7 +87,7 @@ $ ssh-copy-id -i ~/.ssh/id_rsa.pub root@ #### Configuration -마스터 서버가 노드 서버로 ssh 접속을 하기 위해서는 해당 서버의 ip를 알아야한다. kubespray에서는 아래 주소와 같이 클러스터 환경에 대한 설정값을 `hosts.ini` 파일에 정의하고 있다. +마스터 서버가 노드 서버로 ssh 접속을 하기 위해서는 해당 서버의 ip를 알아야한다. `kubespray`에서는 아래 주소와 같이 클러스터 환경에 대한 설정값을 `hosts.ini` 파일에 정의하고 있다. ```bash $ sudo vi inventory/mycluster/hosts.ini @@ -172,7 +172,9 @@ kube-system nginx-proxy-node2 1/1 Running 1 ### Minikube -`미니쿠베`는 쿠버네티스처럼 클러스터를 구성하지 않고 노트북과 같은 단일 머신에서 쿠버네티스 환경을 만들어준다. 미니쿠베는 단일 머신에서 작동하므로 클러스터 환경 설정 및 복잡한 분산 컴퓨팅 메커니즘이 없어 설치가 간편하고 디버깅이 쉽다. 이러한 이유로 미니쿠베는 테스트 및 디버깅 용으로 많이 활용되고 있다. 아래는 미니쿠베 설치 방법과 미니쿠베 환경 위에서 쿠버네티스를 사용할 수 있게 해주는 명령 줄 인터페이스인 `kubectl`의 설치 방법을 가이드한다. +`미니쿠베`는 쿠버네티스처럼 클러스터를 구성하지 않고 노트북과 같은 단일 머신에서 쿠버네티스 환경을 만들어준다. 미니쿠베는 단일 머신에서 작동하므로 클러스터 환경 설정 및 복잡한 분산 컴퓨팅 메커니즘이 없어 설치가 간편하고 디버깅이 쉽다. 이러한 이유로 미니쿠베는 테스트 및 디버깅 용으로 많이 활용되고 있다. + +아래는 미니쿠베 설치 방법과 미니쿠베 환경 위에서 쿠버네티스를 사용할 수 있게 해주는 명령 줄 인터페이스인 `kubectl`의 설치 방법을 가이드한다. @@ -204,7 +206,9 @@ kube-system nginx-proxy-node2 1/1 Running 1 #### Start Minikube -미니쿠베는 기본적으로 [하이퍼바이저(hypervisor)]()를 지원한다. 윈도우 환경과 같이 리눅스 시스템이 아닌 경우 하이퍼바이저를 먼저 설치한다. 하이퍼바이저란 virtualbox, vmware 같이 물리적 호스트에서 다수의 가상머신을 실행할 수 있도록 하여 컴퓨팅 자원을 효과적으로 사용할 수 있게 하는 도구이다. 하이퍼바이저를 사용하는 경우 미니쿠베의 `--driver=` 옵션을 통해서 하이퍼바이저 기반의 미니쿠베 실행이 가능하다. 뿐만 아니라 쿠버네티스 버전을 명시하여 미니쿠베를 실행할 수 있는데 현재 OpenFx는 쿠버네티스 버전 `1.15.2`까지 지원하기 때문에 다음과 같이 버전을 지정하여 미니쿠베를 시작해야 한다. +미니쿠베는 기본적으로 [하이퍼바이저(hypervisor)]()를 지원한다. 윈도우 환경과 같이 리눅스 시스템이 아닌 경우 하이퍼바이저를 먼저 설치한다. 하이퍼바이저란 virtualbox, vmware 같이 물리적 호스트에서 다수의 가상머신을 실행할 수 있도록 하여 컴퓨팅 자원을 효과적으로 사용할 수 있게 하는 도구이다. + +하이퍼바이저를 사용하는 경우 미니쿠베의 `--driver=` 옵션을 통해서 하이퍼바이저 기반의 미니쿠베 실행이 가능하다. 뿐만 아니라 쿠버네티스 버전을 명시하여 미니쿠베를 실행할 수 있는데 현재 OpenFx는 쿠버네티스 버전 `1.15.2`까지 지원하기 때문에 다음과 같이 버전을 지정하여 미니쿠베를 시작해야 한다. ```bash $ echo export CHANGE_MINIKUBE_NONE_USER=true >> ~/.bashrc diff --git a/docs/source/5_components/7_gpu/index.md b/docs/source/5_components/7_gpu/index.md index b400afa..5305fe3 100644 --- a/docs/source/5_components/7_gpu/index.md +++ b/docs/source/5_components/7_gpu/index.md @@ -139,6 +139,9 @@ $ sudo vim /etc/docker/daemon.json } } } + +$ sudo systemctl daemon-reload +$ sudo service docker restart ```