Experimenting and Learning Kubernetes and Tensorflow
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Experimenting and Learning Kubernetes and Tensorflow
- 1. Experimenting and Learning Kubernetes and Tensorflow @Ben_Hall Ben@BenHall.me.uk Katacoda.com
- 4. Experimenting and Learning Kubernetes and Tensorflow @Ben_Hall Ben@BenHall.me.uk Katacoda.com
- 6. Learn via Interactive Browser-Based Labs Katacoda.com
- 7. • In the next 25/30 minutes • Learning to Learn • Creating Kubernetes Experiment Playground • Running Tensorflow on Kubernetes • Keeping up to date with the community
- 13. Goals are clear
- 15. Demo Time!
- 17. Minikube
- 19. Kubeadm
- 22. Create Kubernetes Cluster Minikube, Kubeadm
- 23. apiVersion: extensions/v1beta1 kind: Deployment metadata: name: inception-deployment labels: k8s-app: inception-deployment spec: replicas: 3 selector: matchLabels: k8s-app: inception-deployment template: metadata: labels: k8s-app: inception-deployment annotations: scheduler.alpha.kubernetes.io/critical-pod: '' spec: containers: - name: inception-container image: katacoda/tensorflow_serving imagePullPolicy: Never command: - /bin/sh - -c args: - /serving/bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server --port=9000 --model_name=inception --model_base_path=/serving/inception-export ports: - containerPort: 9000
- 25. apiVersion: batch/v1 kind: Job metadata: name: inception-client spec: template: metadata: name: inception-client spec: containers: - name: inception-client image: katacoda/tensorflow_serving imagePullPolicy: Never command: - /bin/bash - -c args: - /serving/bazel-bin/tensorflow_serving/example/inception_client --server=inception-deployment:9000 --image=/data/cat.jpg volumeMounts: - name: inception-persistent-storage mountPath: /data volumes: - name: inception-persistent-storage hostPath: path: /root restartPolicy: Never
- 26. Kubernetes and Tensorflow at scale?
- 29. Worker Worker Worker Worker Parameter Server Parameter Server
- 30. # On ps0.example.com: $ python trainer.py --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 --job_name=ps --task_index=0 # On ps1.example.com: $ python trainer.py --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 --job_name=ps --task_index=1 # On worker0.example.com: $ python trainer.py --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 --job_name=worker --task_index=0 # On worker1.example.com: $ python trainer.py --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 --job_name=worker --task_index=1
- 31. Kubernetes namespace Kubernetes PodKubernetes PodKubernetes Pod Containerized TF Worker Containerized TF Worker Containerized TF Worker Kubernetes Deployment Containerized TF PS Server 1 Server 2 Server 3 Kubernetes namespace Kubernetes PodKubernetes PodKubernetes Pod Containerized TF Worker Containerized TF Worker Containerized TF Worker Kubernetes Deployment Containerized TF PS Storage Server 4 Server 5
- 32. Kubernetes namespace Kubernetes PodKubernetes PodKubernetes Pod Containerized TF Worker Containerized TF Worker Containerized TF Worker Kubernetes Deployment Containerized TF PS GPU1 GPU2 GPU3 Server 1 Server 2 GPU1 GPU2 GPU3 Server 3 Kubernetes namespace Kubernetes PodKubernetes PodKubernetes Pod Containerized TF Worker Containerized TF Worker Containerized TF Worker Kubernetes Deployment Containerized TF PS Storage Server 4 Server 5
- 33. Docker Container and GPU docker run -it --device /dev/nvidia0:/dev/nvidia0 --device /dev/nvidia1:/dev/nvidia1 --device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm tf-cuda:v1.1beta /bin/bash
- 38. Summary • Kubernetes is designed for running distributed systems at scale • The model of Tensorflow fits cleanly into Kubernetes • As Tensorflow usage increases, Kubernetes can scale to meet demands
- 39. www.katacoda.com
- 40. Call To Action • Interested in sharing your Kubernetes or Tensorflow experience? Write your own scenarios and teach interactively! • Teaching teams internally? Private Katacoda environments