Renamed KFService to InferenceService (kserve#421)

Makefile

@@ -33,18 +33,18 @@ deploy-dev: manifests
 
 undeploy:
 	kustomize build config/default | kubectl delete -f -
-	kubectl delete validatingwebhookconfigurations.admissionregistration.k8s.io kfservice.serving.kubeflow.org
-	kubectl delete mutatingwebhookconfigurations.admissionregistration.k8s.io kfservice.serving.kubeflow.org
+	kubectl delete validatingwebhookconfigurations.admissionregistration.k8s.io inferenceservice.serving.kubeflow.org
+	kubectl delete mutatingwebhookconfigurations.admissionregistration.k8s.io inferenceservice.serving.kubeflow.org
 
 undeploy-dev:
 	kustomize build config/overlays/development | kubectl delete -f -
-	kubectl delete validatingwebhookconfigurations.admissionregistration.k8s.io kfservice.serving.kubeflow.org
-	kubectl delete mutatingwebhookconfigurations.admissionregistration.k8s.io kfservice.serving.kubeflow.org
+	kubectl delete validatingwebhookconfigurations.admissionregistration.k8s.io inferenceservice.serving.kubeflow.org
+	kubectl delete mutatingwebhookconfigurations.admissionregistration.k8s.io inferenceservice.serving.kubeflow.org
 
 # Generate manifests e.g. CRD, RBAC etc.
 manifests:
 	go run vendor/sigs.k8s.io/controller-tools/cmd/controller-gen/main.go crd --output-dir=config/default/crds
-	kustomize build config/default/crds -o config/default/crds/serving_v1alpha2_kfservice.yaml
+	kustomize build config/default/crds -o config/default/crds/serving_v1alpha2_inferenceservice.yaml
 	go run vendor/sigs.k8s.io/controller-tools/cmd/controller-gen/main.go rbac --output-dir=config/default/rbac
 
 # Run go fmt against code

README.md

@@ -26,7 +26,7 @@ kubectl apply -f ./install/$TAG/kfserving.yaml
 ```
 pip install kfserving
 ```
-* Follow the [example here](docs/samples/client/kfserving_sdk_sample.ipynb) to use the KFServing SDK to create, patch, and delete a KFService instance.
+* Follow the [example here](docs/samples/client/kfserving_sdk_sample.ipynb) to use the KFServing SDK to create, patch, and delete a InferenceService instance.
 
 ### Contribute
 * [Developer Guide](/docs/DEVELOPER_GUIDE.md).

ROADMAP.md

@@ -49,7 +49,7 @@ Objective: "Simplify user experience with handling credentials for storage backe
 # Future 
 ## Unscheduled Work
 * Multi-Model Serving.
-    * Multiple KFServices share resources in the backend.
+    * Multiple InferenceServices share resources in the backend.
     * GPU Sharing.
 * Flexible Inference Graphs [MLGraph CRD](https://github.com/SeldonIO/mlgraph).
     * Model Experimentation.
@@ -67,7 +67,7 @@ Objective: "Simplify user experience with handling credentials for storage backe
 
 # Historical
 ## Q2 2019
-### v0.1: KFService Minimum Viable Product (ETA: June 30, 2019)
+### v0.1: InferenceService Minimum Viable Product (ETA: June 30, 2019)
 Objective: "Simplify the user experience and provide a low barrier to entry by minimizing the amount of YAML necessary to deploy a trained model."
 * High Level Interfaces
     * Deploy a Tensorflow model without specifying a Tensorflow Serving Technology.

cmd/spec-gen/main.go

@@ -28,7 +28,7 @@ import (
 	"k8s.io/kube-openapi/pkg/common"
 )
 
-// Generate OpenAPI spec definitions for KFService Resource
+// Generate OpenAPI spec definitions for InferenceService Resource
 func main() {
 	if len(os.Args) <= 1 {
 		klog.Fatal("Supply a version")

config/default/configmap/kfservice.yaml → config/default/configmap/inferenceservice.yaml

@@ -1,7 +1,7 @@
 apiVersion: v1
 kind: ConfigMap
 metadata:
-  name: kfservice-config
+  name: inferenceservice-config
   namespace: kfserving-system
 data:
   predictors: |-

config/default/crds/crd_status_condition_patch.yaml

@@ -1,7 +1,7 @@
 apiVersion: apiextensions.k8s.io/v1beta1
 kind: CustomResourceDefinition
 metadata:
-  name: kfservices.serving.kubeflow.org
+  name: inferenceservices.serving.kubeflow.org
 spec:
   validation:
     openAPIV3Schema:

config/default/crds/kustomization.yaml

@@ -8,7 +8,7 @@
 # YAML string, with resources separated by document
 # markers ("---").
 resources:
-- serving_v1alpha2_kfservice.yaml
+- serving_v1alpha2_inferenceservice.yaml
 
 patches:
   # Knative uses VolatileTime in place of metav1.Time to exclude this from creating equality.Semantic difference,

config/default/crds/serving_v1alpha2_kfservice.yaml → config/default/crds/serving_v1alpha2_inferenceservice.yaml

@@ -4,7 +4,7 @@ metadata:
   creationTimestamp: null
   labels:
     controller-tools.k8s.io: "1.0"
-  name: kfservices.serving.kubeflow.org
+  name: inferenceservices.serving.kubeflow.org
 spec:
   additionalPrinterColumns:
   - JSONPath: .status.url
@@ -24,10 +24,10 @@ spec:
     type: date
   group: serving.kubeflow.org
   names:
-    kind: KFService
-    plural: kfservices
+    kind: InferenceService
+    plural: inferenceservices
     shortNames:
-    - kfservice
+    - inferenceservice
   scope: Namespaced
   validation:
     openAPIV3Schema:
@@ -247,11 +247,11 @@ spec:
               type: object
             canaryTrafficPercent:
               description: CanaryTrafficPercent defines the percentage of traffic
-                going to canary KFService endpoints
+                going to canary InferenceService endpoints
               format: int64
               type: integer
             default:
-              description: Default defines default KFService endpoints +required
+              description: Default defines default InferenceService endpoints +required
               properties:
                 explainer:
                   description: Explainer defines the model explanation service spec

config/default/kustomization.yaml

@@ -11,8 +11,8 @@ namespace: kfserving-system
 # YAML string, with resources separated by document
 # markers ("---").
 resources:
-- crds/serving_v1alpha2_kfservice.yaml
-- configmap/kfservice.yaml
+- crds/serving_v1alpha2_inferenceservice.yaml
+- configmap/inferenceservice.yaml
 - rbac/rbac_role.yaml
 - rbac/rbac_role_binding.yaml
 - manager/manager.yaml

config/default/rbac/rbac_role.yaml

@@ -47,7 +47,7 @@ rules:
 - apiGroups:
   - serving.kubeflow.org
   resources:
-  - kfservices
+  - inferenceservices
   verbs:
   - get
   - list
@@ -59,7 +59,7 @@ rules:
 - apiGroups:
   - serving.kubeflow.org
   resources:
-  - kfservices/status
+  - inferenceservices/status
   verbs:
   - get
   - update

docs/DEVELOPER_GUIDE.md

@@ -164,11 +164,11 @@ kubectl apply -f docs/samples/tensorflow/tensorflow.yaml
 You should see model serving deployment running under default or your specified namespace.
 
 ```console
-$ kubectl get kfservices -n default
+$ kubectl get inferenceservices -n default
 NAME             READY     URL                                  DEFAULT TRAFFIC   CANARY TRAFFIC   AGE
 flowers-sample   True      flowers-sample.default.example.com   100                                1h
 
-$ kubectl get pods -n default -l serving.kubeflow.org/kfservice=flowers-sample
+$ kubectl get pods -n default -l serving.kubeflow.org/inferenceservice=flowers-sample
 NAME                                                READY   STATUS    RESTARTS   AGE
 flowers-sample-default-htz8r-deployment-8fd979f9b-w2qbv   3/3     Running   0          10s
 ```
@@ -283,4 +283,4 @@ It`s a red herring. To resolve it, please ensure you have logged into dockerhub
 2019-09-28 01:52:23.345692: E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:362] FileSystemStoragePathSource encountered a filesystem access error: Could not find base path /mnt/models for servable flowers-sample
 ```
 
-Please make sure not to deploy the kfservice in the `kfserving-system` or other namespaces where namespace has  `control-plane` as a label. The `storage-initializer` init container does not get injected for deployments in those namespaces since they do not go through the mutating webhook.
+Please make sure not to deploy the inferenceservice in the `kfserving-system` or other namespaces where namespace has  `control-plane` as a label. The `storage-initializer` init container does not get injected for deployments in those namespaces since they do not go through the mutating webhook.

docs/README.md

@@ -6,13 +6,13 @@ KFServing architecture consists of two main specifications, around control plane
    * Defines the specification of the `kfserving` resource.
 
 # Architecture Overview
-The KFService Data Plane architecture consists of a static graph of components which implement a limited set of features. Advanced features such as Ensembling, A/B testing, and Multi-Arm-Bandits should be built at a layer above KFServices. The diagram reflects the overall architecture for a viable offering, but at this point in time may not accurately reflect the current set of features available in the graph, but the overall mechanism holds:
+The InferenceService Data Plane architecture consists of a static graph of components which implement a limited set of features. Advanced features such as Ensembling, A/B testing, and Multi-Arm-Bandits should be built at a layer above InferenceServices. The diagram reflects the overall architecture for a viable offering, but at this point in time may not accurately reflect the current set of features available in the graph, but the overall mechanism holds:
 
-- The User defines the components they wish to use in a KFService.
+- The User defines the components they wish to use in a InferenceService.
   - The only required component is a Predictor.
   - Additional components may be specified to attach addtional behavior. 
   - Each component is specified at the ModelSpec layer, allowing for canarying.
-- The KFService will support one of several Data Plane interfaces.
+- The InferenceService will support one of several Data Plane interfaces.
   - For example: tensorflow/HTTP, tensorflow/GRPC, seldon/HTTP, seldon/GRPC
   - Data Plane interfaces may be specified with annotations and defaults to tensorflow/HTTP
   - Not all components will be compatible with every data plane interface.

docs/apis/README.md

@@ -10,12 +10,12 @@
 </p>
 Resource Types:
 <ul><li>
-<a href="#serving.kubeflow.org/v1alpha2.KFService">KFService</a>
+<a href="#serving.kubeflow.org/v1alpha2.InferenceService">InferenceService</a>
 </li></ul>
-<h3 id="serving.kubeflow.org/v1alpha2.KFService">KFService
+<h3 id="serving.kubeflow.org/v1alpha2.InferenceService">InferenceService
 </h3>
 <p>
-<p>KFService is the Schema for the services API</p>
+<p>InferenceService is the Schema for the services API</p>
 </p>
 <table>
 <thead>
@@ -40,7 +40,7 @@ serving.kubeflow.org/v1alpha2
 <code>kind</code></br>
 string
 </td>
-<td><code>KFService</code></td>
+<td><code>InferenceService</code></td>
 </tr>
 <tr>
 <td>
@@ -60,8 +60,8 @@ Refer to the Kubernetes API documentation for the fields of the
 <td>
 <code>spec</code></br>
 <em>
-<a href="#serving.kubeflow.org/v1alpha2.KFServiceSpec">
-KFServiceSpec
+<a href="#serving.kubeflow.org/v1alpha2.InferenceServiceSpec">
+InferenceServiceSpec
 </a>
 </em>
 </td>
@@ -79,7 +79,7 @@ EndpointSpec
 </em>
 </td>
 <td>
-<p>Default defines default KFService endpoints</p>
+<p>Default defines default InferenceService endpoints</p>
 </td>
 </tr>
 <tr>
@@ -105,7 +105,7 @@ int
 </td>
 <td>
 <em>(Optional)</em>
-<p>CanaryTrafficPercent defines the percentage of traffic going to canary KFService endpoints</p>
+<p>CanaryTrafficPercent defines the percentage of traffic going to canary InferenceService endpoints</p>
 </td>
 </tr>
 </table>
@@ -115,8 +115,8 @@ int
 <td>
 <code>status</code></br>
 <em>
-<a href="#serving.kubeflow.org/v1alpha2.KFServiceStatus">
-KFServiceStatus
+<a href="#serving.kubeflow.org/v1alpha2.InferenceServiceStatus">
+InferenceServiceStatus
 </a>
 </em>
 </td>
@@ -253,7 +253,7 @@ Kubernetes core/v1.Container
 <a href="#serving.kubeflow.org/v1alpha2.TransformerSpec">TransformerSpec</a>)
 </p>
 <p>
-<p>DeploymentSpec defines the configuration for a given KFService service component</p>
+<p>DeploymentSpec defines the configuration for a given InferenceService service component</p>
 </p>
 <table>
 <thead>
@@ -305,7 +305,7 @@ int
 </h3>
 <p>
 (<em>Appears on:</em>
-<a href="#serving.kubeflow.org/v1alpha2.KFServiceSpec">KFServiceSpec</a>)
+<a href="#serving.kubeflow.org/v1alpha2.InferenceServiceSpec">InferenceServiceSpec</a>)
 </p>
 <p>
 </p>
@@ -597,14 +597,14 @@ PredictorConfig
 </tr>
 </tbody>
 </table>
-<h3 id="serving.kubeflow.org/v1alpha2.KFServiceSpec">KFServiceSpec
+<h3 id="serving.kubeflow.org/v1alpha2.InferenceServiceSpec">InferenceServiceSpec
 </h3>
 <p>
 (<em>Appears on:</em>
-<a href="#serving.kubeflow.org/v1alpha2.KFService">KFService</a>)
+<a href="#serving.kubeflow.org/v1alpha2.InferenceService">InferenceService</a>)
 </p>
 <p>
-<p>KFServiceSpec defines the desired state of KFService</p>
+<p>InferenceServiceSpec defines the desired state of InferenceService</p>
 </p>
 <table>
 <thead>
@@ -624,7 +624,7 @@ EndpointSpec
 </em>
 </td>
 <td>
-<p>Default defines default KFService endpoints</p>
+<p>Default defines default InferenceService endpoints</p>
 </td>
 </tr>
 <tr>
@@ -650,19 +650,19 @@ int
 </td>
 <td>
 <em>(Optional)</em>
-<p>CanaryTrafficPercent defines the percentage of traffic going to canary KFService endpoints</p>
+<p>CanaryTrafficPercent defines the percentage of traffic going to canary InferenceService endpoints</p>
 </td>
 </tr>
 </tbody>
 </table>
-<h3 id="serving.kubeflow.org/v1alpha2.KFServiceStatus">KFServiceStatus
+<h3 id="serving.kubeflow.org/v1alpha2.InferenceServiceStatus">InferenceServiceStatus
 </h3>
 <p>
 (<em>Appears on:</em>
-<a href="#serving.kubeflow.org/v1alpha2.KFService">KFService</a>)
+<a href="#serving.kubeflow.org/v1alpha2.InferenceService">InferenceService</a>)
 </p>
 <p>
-<p>KFServiceStatus defines the observed state of KFService</p>
+<p>InferenceServiceStatus defines the observed state of InferenceService</p>
 </p>
 <table>
 <thead>
@@ -1017,7 +1017,7 @@ Kubernetes core/v1.ResourceRequirements
 </h3>
 <p>
 (<em>Appears on:</em>
-<a href="#serving.kubeflow.org/v1alpha2.KFServiceStatus">KFServiceStatus</a>)
+<a href="#serving.kubeflow.org/v1alpha2.InferenceServiceStatus">InferenceServiceStatus</a>)
 </p>
 <p>
 <p>StatusConfigurationSpec describes the state of the configuration receiving traffic.</p>