TensorFlow Serving Inception v3
TensorFlow Serving is an open-source software library for serving machine learning models. This chart will specifically serve the Inception v3 model with already trained data.
TL;DR;
$ helm install bitnami/tensorflow-inception
Introduction
This chart bootstraps a TensorFlow Serving Inception v3 pod 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-inception
The command deploys Tensorflow Serving Inception v3 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 Inception chart and their default values.
| Parameter | Description | Default |
|---|---|---|
global.imageRegistry |
Global Docker image registry | nil |
replicaCount |
desired number of pods | 1 |
server.image.registry |
TensorFlow Serving image registry | docker.io |
server.image.repository |
TensorFlow Serving Image name | bitnami/tensorflow-serving |
server.image.tag |
TensorFlow Serving Image tag | {VERSION} |
server.image.pullPolicy |
TensorFlow Serving image pull policy | Always if imageTag is latest, else IfNotPresent |
server.image.pullSecrets |
Specify docker-registry secret names as an array | [] (does not add image pull secrets to deployed pods) |
server.port |
Tensorflow server port | 8500 |
client.image.registry |
TensorFlow Inception image registry | docker.io |
client.image.repository |
TensorFlow Inception Image name | bitnami/tensorflow-inception |
client.image.tag |
TensorFlow Inception Image tag | {VERSION} |
client.image.pullPolicy |
TensorFlow Inception image pull policy | Always if imageTag is latest, else IfNotPresent |
client.image.pullSecrets |
Specify docker-registry secret names as an array | [] (does not add image pull secrets to deployed pods) |
securityContext.enabled |
Enable security context for TensorFlow Serving | true |
securityContext.fsGroup |
Group ID for TensorFlow Serving container | 1001 |
securityContext.runAsUser |
User ID for TensorFlow Serving container | 1001 |
imagePullPolicy |
Image pull policy | Always if image tag is latest, else IfNotPresent |
podAnnotations |
Pod annotations | {} |
metrics.enabled |
Start a side-car Tensorflow prometheus exporter | false |
metrics.image.registry |
Tensorflow exporter image registry | docker.io |
metrics.image.repository |
Tensorflow exporter image name | ynqa/tensorflow-serving-exporter |
metrics.image.tag |
Tensorflow exporter image tag | latest |
metrics.image.pullPolicy |
Image pull policy | IfNotPresent |
metrics.image.pullSecrets |
Specify docker-registry secret names as an array | [] (does not add image pull secrets to deployed pods) |
metrics.podAnnotations |
Additional annotations for Metrics exporter pod | {prometheus.io/scrape: "true", prometheus.io/port: "9118"} |
metrics.resources |
Exporter resource requests/limit | Memory: 256Mi, CPU: 100m |
Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,
$ helm install --name my-release bitnami/tensorflow-inception --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-inception
Tip
: You can use the default values.yaml
Upgrading
To 3.2.0
Tensorflow Serving container was moved to a non-root approach. There shouldn't be any issue when upgrading since the corresponding securityContext is enabled by default. Both container image and chart can be upgraded by running the command below:
$ helm upgrade my-release stable/tensorflow-inception
If you use a previous container image (previous to 1.12.0-r34), disable the securityContext by running the command below:
$ helm upgrade my-release stable/tensorflow-inception --set securityContext.enabled=fase,server.image.tag=XXX
To 1.0.0
Backwards compatibility is not guaranteed unless you modify the labels used on the chart's deployments. Use the workaround below to upgrade from versions previous to 1.0.0. The following example assumes that the release name is tensorflow-inception:
$ kubectl patch deployment tensorflow-inception --type=json -p='[{"op": "remove", "path": "/spec/selector/matchLabels/chart"}]'