Add default value for TARGETOS/TARGETARCH

&& Update runtime/fvt manifests

Signed-off-by: jooho <jlee@redhat.com>

.gitignore

@@ -38,8 +38,5 @@ devbuild
 .cache/
 kustomize/
 .temp_new_modelmesh_manifests
-opendatahub/scripts/manifests/params.env
-opendatahub/scripts/manifests/fvt/
-opendatahub/scripts/manifests/runtimes/
 kfctl*
 bin

Dockerfile

@@ -17,13 +17,13 @@
 # https://www.docker.com/blog/faster-multi-platform-builds-dockerfile-cross-compilation-guide/
 ###############################################################################
 ARG DEV_IMAGE
-FROM --platform=$BUILDPLATFORM $DEV_IMAGE AS build
+FROM ${DEV_IMAGE} AS build
 
 # https://docs.docker.com/engine/reference/builder/#automatic-platform-args-in-the-global-scope
 # don't provide "default" values (e.g. 'ARG TARGETARCH=amd64') for non-buildx environments,
 # see https://github.com/docker/buildx/issues/510
-ARG TARGETOS
-ARG TARGETARCH
+ARG TARGETOS=linux
+ARG TARGETARCH=amd64
 
 LABEL image="build"
 

Dockerfile.develop

@@ -15,15 +15,16 @@
 ###############################################################################
 # Create the develop, test, and build environment
 ###############################################################################
-FROM registry.access.redhat.com/ubi8/go-toolset:1.19
+FROM registry.access.redhat.com/ubi8/ubi-minimal:8.7
 
 # https://docs.docker.com/engine/reference/builder/#automatic-platform-args-in-the-global-scope
 # don't provide "default" values (e.g. 'ARG TARGETARCH=amd64') for non-buildx environments,
 # see https://github.com/docker/buildx/issues/510
-ARG TARGETOS
-ARG TARGETARCH
+ARG TARGETOS=linux
+ARG TARGETARCH=amd64
 
-ARG OPENSHIFT_VERSION=4.9
+ARG GOLANG_VERSION=1.19.9    
+ARG OPENSHIFT_VERSION=4.12
 ARG KUSTOMIZE_VERSION=4.5.2
 ARG KUBEBUILDER_VERSION=v3.3.0
 ARG CONTROLLER_GEN_VERSION=v0.11.4
@@ -43,6 +44,12 @@ RUN --mount=type=cache,target=/root/.cache/dnf:rw \
        nodejs \
        jq 
 
+# Install go
+RUN set -eux; \
+    wget -qO go.tgz "https://golang.org/dl/go${GOLANG_VERSION}.linux-amd64.tar.gz"; \
+    tar -C /usr/local -xzf go.tgz; \
+    go version && rm go.tgz 
+
 # Install pre-commit
 ENV PIP_CACHE_DIR=/root/.cache/pip
 RUN --mount=type=cache,target=/root/.cache/pip \
@@ -111,7 +118,8 @@ RUN  true \
       && true
 
 # For GitHub Action 'lint', work around error "detected dubious ownership in repository at '/workspace'"
-RUN git config --system --add safe.directory /workspace
+#RUN git config --system --add safe.directory /workspace 
+RUN git config --system --add safe.directory "*"
 
 # The ubi/go-toolset image doesn't define ENTRYPOINT or CMD, but we need it to run 'make develop'
 CMD /bin/bash

opendatahub/scripts/manifests/fvt/fvt_templates/kustomization.yaml

@@ -0,0 +1,7 @@
+apiVersion: kustomize.config.k8s.io/v1beta1
+kind: Kustomization
+resources:
+  - fvt.yaml
+patchesStrategicMerge:
+  - remove_etcd_patch.yaml
+namespace: modelmesh-serving

opendatahub/scripts/manifests/fvt/fvt_templates/remove_etcd_patch.yaml

@@ -0,0 +1,17 @@
+$patch: delete
+apiVersion: v1
+kind: Service
+metadata:
+  name: etcd
+---
+$patch: delete
+apiVersion: v1
+kind: Secret
+metadata:
+  name: model-serving-etcd
+---
+$patch: delete
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: etcd

opendatahub/scripts/manifests/params.env

@@ -0,0 +1,7 @@
+monitoring-namespace=opendatahub
+odh-mm-rest-proxy=quay.io/opendatahub/rest-proxy:v0.11.0-rc0
+odh-modelmesh-runtime-adapter=quay.io/opendatahub/modelmesh-runtime-adapter:v0.11.0-rc0
+odh-modelmesh=quay.io/opendatahub/modelmesh:v0.11.0-rc0
+odh-openvino=quay.io/opendatahub/openvino_model_server:2022.3-release
+odh-modelmesh-controller=quay.io/opendatahub/modelmesh-controller:v0.11.0-rc0
+odh-model-controller=quay.io/opendatahub/odh-model-controller:v0.11.0-rc0

opendatahub/scripts/manifests/runtimes/mlserver-1.x.yaml

@@ -0,0 +1,75 @@
+# Copyright 2021 IBM Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+apiVersion: serving.kserve.io/v1alpha1
+kind: ServingRuntime
+metadata:
+  name: mlserver-1.x
+  labels:
+    name: modelmesh-serving-mlserver-1.x-SR
+spec:
+  supportedModelFormats:
+    - name: sklearn
+      version: "0" # v0.23.1
+      autoSelect: true
+    - name: xgboost
+      version: "1" # v1.1.1
+      autoSelect: true
+    - name: lightgbm
+      version: "3" # v3.2.1
+      autoSelect: true
+
+  protocolVersions:
+    - grpc-v2
+  multiModel: true
+
+  grpcEndpoint: "port:8085"
+  grpcDataEndpoint: "port:8001"
+
+  containers:
+    - name: mlserver
+      image: mlserver-1:replace
+      env:
+        - name: MLSERVER_MODELS_DIR
+          value: "/models/_mlserver_models/"
+        - name: MLSERVER_GRPC_PORT
+          value: "8001"
+        # default value for HTTP port is 8080 which conflicts with MMesh's
+        # Litelinks port
+        - name: MLSERVER_HTTP_PORT
+          value: "8002"
+        - name: MLSERVER_LOAD_MODELS_AT_STARTUP
+          value: "false"
+        # Set a dummy model name via environment so that MLServer doesn't
+        # error on a RepositoryIndex call when no models exist
+        - name: MLSERVER_MODEL_NAME
+          value: dummy-model-fixme
+        # Set server addr to localhost to ensure MLServer only listen inside the pod
+        - name: MLSERVER_HOST
+          value: "127.0.0.1"
+        # Increase gRPC max message size to support larger payloads
+        # Unlimited because it will be restricted at the model mesh layer
+        - name: MLSERVER_GRPC_MAX_MESSAGE_LENGTH
+          value: "-1"
+      resources:
+        requests:
+          cpu: 500m
+          memory: 1Gi
+        limits:
+          cpu: "5"
+          memory: 1Gi
+  builtInAdapter:
+    serverType: mlserver
+    runtimeManagementPort: 8001
+    memBufferBytes: 134217728
+    modelLoadingTimeoutMillis: 90000