bitnamicharts/tensorflow-resnet
Bitnami Helm chart for TensorFlow ResNet
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TensorFlow ResNet is a client utility for use with TensorFlow Serving and ResNet models.
Overview of TensorFlow ResNet
Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.
helm install my-release oci://registry-1.docker.io/bitnamicharts/tensorflow-resnet
Looking to use TensorFlow ResNet in production? Try VMware Tanzu Application Catalog, the commercial edition of the Bitnami catalog.
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.
To install the chart with the release name my-release
:
helm install my-release oci://REGISTRY_NAME/REPOSITORY_NAME/tensorflow-resnet
Note: You need to substitute the placeholders
REGISTRY_NAME
andREPOSITORY_NAME
with a reference to your Helm chart registry and repository. For example, in the case of Bitnami, you need to useREGISTRY_NAME=registry-1.docker.io
andREPOSITORY_NAME=bitnamicharts
.
These commands deploy Tensorflow Serving ResNet model on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation.
Tip: List all releases using
helm list
Bitnami charts allow setting resource requests and limits for all containers inside the chart deployment. These are inside the resources
value (check parameter table). Setting requests is essential for production workloads and these should be adapted to your specific use case.
To make this process easier, the chart contains the resourcesPreset
values, which automatically sets the resources
section according to different presets. Check these presets in the bitnami/common chart. However, in production workloads using resourcesPreset
is discouraged as it may not fully adapt to your specific needs. Find more information on container resource management in the official Kubernetes documentation.
This chart can be integrated with Prometheus by setting metrics.enabled
to true
. This will expose Tensorflow native Prometheus endpoint in the service. It will have the necessary annotations to be automatically scraped by Prometheus.
Prometheus requirements
It is necessary to have a working installation of Prometheus or Prometheus Operator for the integration to work. Install the Bitnami Prometheus helm chart or the Bitnami Kube Prometheus helm chart to easily have a working Prometheus in your cluster.
It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.
Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.
To back up and restore Helm chart deployments on Kubernetes, you need to back up the persistent volumes from the source deployment and attach them to a new deployment using Velero, a Kubernetes backup/restore tool. Find the instructions for using Velero in this guide.
This chart allows you to set custom Pod affinity using the affinity
parameter. Find more information about Pod's affinity in the Kubernetes documentation.
As an alternative, you can use any of the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the bitnami/common chart. To do so, set the podAffinityPreset
, podAntiAffinityPreset
, or nodeAffinityPreset
parameters.
Name | Description | Value |
---|---|---|
global.imageRegistry | Global Docker image registry | "" |
global.imagePullSecrets | Global Docker registry secret names as an array | [] |
global.security.allowInsecureImages | Allows skipping image verification | false |
global.compatibility.openshift.adaptSecurityContext | Adapt the securityContext sections of the deployment to make them compatible with Openshift restricted-v2 SCC: remove runAsUser, runAsGroup and fsGroup and let the platform use their allowed default IDs. Possible values: auto (apply if the detected running cluster is Openshift), force (perform the adaptation always), disabled (do not perform adaptation) | auto |
Name | Description | Value |
---|---|---|
kubeVersion | Force target Kubernetes version (using Helm capabilities if not set) | "" |
nameOverride | String to partially override common.names.fullname template (will maintain the release name) | "" |
fullnameOverride | String to fully override common.names.fullname template | "" |
commonAnnotations | Annotations to add to all deployed objects | {} |
commonLabels | Labels to add to all deployed objects | {} |
extraDeploy | Array of extra objects to deploy with the release | [] |
diagnosticMode.enabled | Enable diagnostic mode (all probes will be disabled and the command will be overridden) | false |
diagnosticMode.command | Command to override all containers in the deployment | ["sleep"] |
diagnosticMode.args | Args to override all containers in the deployment | ["infinity"] |
Name | Description | Value |
---|---|---|
server.image.registry | TensorFlow Serving image registry | REGISTRY_NAME |
server.image.repository | TensorFlow Serving image repository | REPOSITORY_NAME/tensorflow-serving |
server.image.digest | TensorFlow Serving image digest in the way sha256:aa.... Please note this parameter, if set, will override the tag | "" |
server.image.pullPolicy | TensorFlow Serving image pull policy | IfNotPresent |
server.image.pullSecrets | Specify docker-registry secret names as an array | [] |
client.image.registry | TensorFlow ResNet image registry | REGISTRY_NAME |
client.image.repository | TensorFlow ResNet image repository | REPOSITORY_NAME/tensorflow-resnet |
client.image.digest | TensorFlow ResNet image digest in the way sha256:aa.... Please note this parameter, if set, will override the tag | "" |
client.image.pullPolicy | TensorFlow ResNet image pull policy | IfNotPresent |
client.image.pullSecrets | Specify docker-registry secret names as an array | [] |
automountServiceAccountToken | Mount Service Account token in pod | false |
hostAliases | Deployment pod host aliases | [] |
containerPorts.server | Tensorflow server port | 8500 |
containerPorts.restApi | TensorFlow Serving Rest API Port | 8501 |
replicaCount | Number of replicas | 1 |
podAnnotations | Pod annotations | {} |
podLabels | Pod labels | {} |
podAffinityPreset | Pod affinity preset. Ignored if affinity is set. Allowed values: soft or hard | "" |
podAntiAffinityPreset | Pod anti-affinity preset. Ignored if affinity is set. Allowed values: soft or hard | soft |
nodeAffinityPreset.type | Node affinity preset type. Ignored if affinity is set. Allowed values: soft or hard | "" |
nodeAffinityPreset.key | Node label key to match Ignored if affinity is set. | "" |
nodeAffinityPreset.values | Node label values to match. Ignored if affinity is set. | [] |
affinity | Affinity for pod assignment. Evaluated as a template. | {} |
nodeSelector | Node labels for pod assignment. Evaluated as a template. | {} |
tolerations | Tolerations for pod assignment. Evaluated as a template. | [] |
podSecurityContext.enabled | Enabled pod Security Context | true |
podSecurityContext.fsGroupChangePolicy | Set filesystem group change policy | Always |
podSecurityContext.sysctls | Set kernel settings using the sysctl interface | [] |
podSecurityContext.supplementalGroups | Set filesystem extra groups | [] |
podSecurityContext.fsGroup | Set pod Security Context fsGroup | 1001 |
containerSecurityContext.enabled | Enabled containers' Security Context | true |
containerSecurityContext.seLinuxOptions | Set SELinux options in container | {} |
containerSecurityContext.runAsUser | Set containers' Security Context runAsUser | 1001 |
containerSecurityContext.runAsGroup | Set containers' Security Context runAsGroup | 1001 |
containerSecurityContext.runAsNonRoot | Set container's Security Context runAsNonRoot | true |
containerSecurityContext.privileged | Set container's Security Context privileged | false |
containerSecurityContext.readOnlyRootFilesystem | Set container's Security Context readOnlyRootFilesystem | true |
containerSecurityContext.allowPrivilegeEscalation | Set container's Security Context allowPrivilegeEscalation | false |
containerSecurityContext.capabilities.drop | List of capabilities to be dropped | ["ALL"] |
containerSecurityContext.seccompProfile.type | Set container's Security Context seccomp profile | RuntimeDefault |
command | Override default container command (useful when using custom images) | [] |
args | Override default container args (useful when using custom images) | [] |
lifecycleHooks | for the container to automate configuration before or after startup | {} |
extraEnvVars | Array with extra environment variables for the Tensorflow Serving container(s) | [] |
extraEnvVarsCM | Name of existing ConfigMap containing extra env variables for the Tensorflow Serving container(s) | "" |
extraEnvVarsSecret | Name of existing Secret containing extra env variables for the Tensorflow Serving container(s) | "" |
extraVolumes | Optionally specify extra list of additional volumes | [] |
extraVolumeMounts | Optionally specify extra list of additional volumeMounts for the Tensorflow Serving container(s) | [] |
sidecars | Add additional sidecar containers to the pod |
Note: the README for this chart is longer than the DockerHub length limit of 25000, so it has been trimmed. The full README can be found at https://github.com/bitnami/charts/blob/main/bitnami/tensorflow-resnet/README.md