@helm-charts/bitnami-tensorflow-resnet v0.1.2-0.1.0

@helm-charts/bitnami-tensorflow-resnet

Open-source software library serving the ResNet machine learning model.

## Global Docker image parameters
## Please, note that this will override the image parameters, including dependencies, configured to use the global value
## Current available global Docker image parameters: imageRegistry and imagePullSecrets
##
# global:
#   imageRegistry: myRegistryName
#   imagePullSecrets:
#     - myRegistryKeySecretName

replicaCount: 1

## TensorFlow Serving server image version
## ref: https://hub.docker.com/r/bitnami/tensorflow-serving/tags/
##
server:
  image:
    registry: docker.io
    repository: bitnami/tensorflow-serving
    tag: 1.13.0
    ## Specify a imagePullPolicy
    ## Defaults to 'Always' if image tag is 'latest', else set to 'IfNotPresent'
    ## ref: http://kubernetes.io/docs/user-guide/images/#pre-pulling-images
    ##
    pullPolicy: IfNotPresent
    ## Optionally specify an array of imagePullSecrets.
    ## Secrets must be manually created in the namespace.
    ## ref: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
    ##
    # pullSecrets:
    #   - myRegistryKeySecretName
  port: 8500

## TensorFlow ResNet image version
## ref: https://hub.docker.com/r/bitnami/tensorflow-resnet/tags/
##
client:
  image:
    registry: docker.io
    repository: bitnami/tensorflow-resnet
    tag: 1.13.0
    ## Specify a imagePullPolicy
    ## Defaults to 'Always' if image tag is 'latest', else set to 'IfNotPresent'
    ## ref: http://kubernetes.io/docs/user-guide/images/#pre-pulling-images
    ##
    pullPolicy: IfNotPresent
    ## Optionally specify an array of imagePullSecrets.
    ## Secrets must be manually created in the namespace.
    ## ref: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
    ##
    # pullSecrets:
    #   - myRegistryKeySecretName

## Specify a imagePullPolicy
## Defaults to 'Always' if image tag is 'latest', else set to 'IfNotPresent'
## ref: http://kubernetes.io/docs/user-guide/images/#pre-pulling-images
##
imagePullPolicy: IfNotPresent

## Kubernetes configuration
## For minikube, set this to NodePort, elsewhere use LoadBalancer
##
serviceType: LoadBalancer

## Pod annotations
## ref: https://kubernetes.io/docs/concepts/overview/working-with-objects/annotations/
##
podAnnotations: {}

## Configure extra options for liveness and readiness probes
## ref: https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-probes/#configure-probes)
livenessProbe:
  enabled: true
  initialDelaySeconds: 30
  periodSeconds: 5
  timeoutSeconds: 5
  failureThreshold: 6
  successThreshold: 1

readinessProbe:
  enabled: true
  initialDelaySeconds: 15
  periodSeconds: 5
  timeoutSeconds: 5
  failureThreshold: 6
  successThreshold: 1

## Prometheus Exporter / Metrics
##
metrics:
  enabled: false
  image:
    registry: docker.io
    repository: ynqa/tensorflow-serving-exporter
    tag: latest
    pullPolicy: IfNotPresent
    ## Optionally specify an array of imagePullSecrets.
    ## Secrets must be manually created in the namespace.
    ## ref: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
    ##
    # pullSecrets:
    #   - myRegistryKeySecretName
  port: 9118
  ## Configure extra options for liveness and readiness probes
  ## ref: https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-probes/#configure-probes)
  livenessProbe:
    enabled: true
    initialDelaySeconds: 15
    periodSeconds: 10
    timeoutSeconds: 5
    failureThreshold: 2
    successThreshold: 1

  readinessProbe:
    enabled: true
    initialDelaySeconds: 5
    periodSeconds: 10
    timeoutSeconds: 1
    failureThreshold: 6
    successThreshold: 1
  ## Metrics exporter pod Annotation and Labels
  podAnnotations:
    prometheus.io/scrape: 'true'
    prometheus.io/port: '9118'
    ## Metrics exporter resource requests and limits
    ## ref: http://kubernetes.io/docs/user-guide/compute-resources/
    ##
  # resources: {}

TensorFlow Serving ResNet

TensorFlow Serving is an open-source software library for serving machine learning models. This chart will specifically serve the ResNet model with already trained data.

TL;DR;

$ helm install bitnami/tensorflow-resnet

Introduction

This chart bootstraps a TensorFlow Serving ResNet deployment on a Kubernetes cluster using the Helm package manager.

Bitnami charts can be used with Kubeapps for deployment and management of Helm Charts in clusters. This Helm chart has been tested on top of Bitnami Kubernetes Production Runtime (BKPR). Deploy BKPR to get automated TLS certificates, logging and monitoring for your applications.

Prerequisites

• Kubernetes 1.4+ with Beta APIs enabled
• PV provisioner support in the underlying infrastructure

Get this chart

Download the latest release of the chart from the releases page.

Alternatively, clone the repo if you wish to use the development snapshot:

$ git clone https://github.com/bitnami/charts.git

Installing the Chart

To install the chart with the release name my-release:

$ helm install --name my-release bitnami/tensorflow-resnet

The command deploys Tensorflow Serving ResNet model on the Kubernetes cluster in the default configuration. The configuration section lists the parameters that can be configured during installation.

Tip: List all releases using helm list

Uninstalling the Chart

To uninstall/delete the my-release deployment:

$ helm delete my-release

You can check your releases with:

$ helm list

The command removes all the Kubernetes components associated with the chart and deletes the release.

Configuration

The following tables lists the configurable parameters of the TensorFlow ResNet chart and their default values.

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

$ helm install --name my-release bitnami/tensorflow-resnet --set imagePullPolicy=Always

Alternatively, a YAML file that specifies the values for the above parameters can be provided while installing the chart. For example,

$ helm install --name my-release -f values.yaml bitnami/tensorflow-resnet

Tip: You can use the default values.yaml