update kubeflow dip-catalog

2025-01-13 02:31:27 +00:00
parent 1dc1181a03
commit 5451f16d72
1959 changed files with 602337 additions and 0 deletions
@@ -0,0 +1,23 @@
+BENTOML_YATAI_IMAGE_BUILDER_VERSION ?= 1.2.28
+BENTOML_YATAI_DEPLOYMENT_VERSION ?= 1.1.21
+BENTOML_HELM_CHART_REPO ?= https://bentoml.github.io/helm-charts
+
+.PHONY: bentoml-yatai-stack/bases
+bentoml-yatai-stack/bases: clean-kustomize
+	mkdir -p bentoml-yatai-stack/bases/yatai-image-builder
+	cd bentoml-yatai-stack/bases/yatai-image-builder && helm template --skip-tests yatai-image-builder-crds yatai-image-builder-crds --repo ${BENTOML_HELM_CHART_REPO} --namespace kubeflow --version ${BENTOML_YATAI_IMAGE_BUILDER_VERSION} > resources.yaml
+	cd bentoml-yatai-stack/bases/yatai-image-builder && helm template --skip-tests -f ../../../sources/yatai-image-builder-values.yaml yatai-image-builder yatai-image-builder --repo ${BENTOML_HELM_CHART_REPO} --namespace kubeflow --version ${BENTOML_YATAI_IMAGE_BUILDER_VERSION} >> resources.yaml
+	cp sources/kustomization-template.yaml bentoml-yatai-stack/bases/yatai-image-builder/kustomization.yaml
+	mkdir -p bentoml-yatai-stack/bases/yatai-deployment
+	cd bentoml-yatai-stack/bases/yatai-deployment && helm template --skip-tests yatai-deployment-crds yatai-deployment-crds --repo ${BENTOML_HELM_CHART_REPO} --namespace kubeflow --version ${BENTOML_YATAI_DEPLOYMENT_VERSION} > resources.yaml
+	cd bentoml-yatai-stack/bases/yatai-deployment && helm template --skip-tests -f ../../../sources/yatai-deployment-values.yaml yatai-deployment yatai-deployment --repo ${BENTOML_HELM_CHART_REPO} --namespace kubeflow --version ${BENTOML_YATAI_DEPLOYMENT_VERSION} >> resources.yaml
+	cp sources/kustomization-template.yaml bentoml-yatai-stack/bases/yatai-deployment/kustomization.yaml
+
+.PHONY: clean-kustomize
+clean-kustomize:
+	rm -rf bentoml-yatai-stack/bases
+
+.PHONY: test
+test:
+	./test.sh
+
@@ -0,0 +1,3 @@
+approvers:
+  - yubozhao
+  - juliusvonkohout
@@ -0,0 +1,86 @@
+# BentoML on Kubeflow
+
+Starting with the release of Kubeflow 1.7, BentoML provides a native integration with Kubeflow through [Yatai](https://github.com/bentoml/yatai-deployment). This integration allows you to package models trained in Kubeflow Notebooks or Pipelines as [Bentos](https://docs.bentoml.org/en/latest/concepts/bento.html), and deploy them as microservices in a Kubernetes cluster through BentoML's cloud native components and custom resource definitions (CRDs). This documentation provides a comprehensive guide on how to use BentoML and Kubeflow together to streamline the process of deploying models at scale.
+
+## Requirements
+
+* Kubernetes 1.20 - 1.25
+
+## Installation
+
+Run the following command to install BentoML Yatai. Note that the YAML assumes you will install in kubeflow namespace.
+
+```bash
+kustomize build bentoml-yatai-stack/default | kubectl apply -n kubeflow --server-side -f -
+```
+
+## Customizations
+
+You can customize the container repository configurations and credentials for the `yatai-image-builder` operator to push Bento images to a container registry of your choice.
+
+WARNING: The `yatai-image-builder` operator requires root privileges because it needs to access the Docker daemon, which requires elevated permissions. Granting root privileges can potentially be dangerous, as it can give a user unrestricted access to the underlying operating system.
+
+```
+dockerRegistry:
+  bentoRepositoryName: yatai-bentos
+  inClusterServer: docker-registry.kubeflow.svc.cluster.local:5000
+  password: ""
+  secure: false
+  server: 127.0.0.1:5000
+  username: ""
+```
+
+You can also supply AWS credentials for the `bento-image-builder` operator to download the Bento specified in the BentoRequest resource from S3.
+
+```
+aws:
+  accessKeyID: ''
+  secretAccessKey: ''
+  secretAccessKeyExistingSecretName: ''
+  secretAccessKeyExistingSecretKey: ''
+```
+
+Update the resources with the following command.
+
+```bash
+make bentoml-yatai-stack/bases
+```
+
+Re-install and apply resources.
+
+```bash
+kustomize build bentoml-yatai-stack/default | kubectl apply -n kubeflow --server-side -f -
+```
+
+## Upgrading
+
+See [UPGRADE.md](UPGRADE.md)
+
+## Why BentoML
+
+[BentoML](https://github.com/bentoml/BentoML) is an open-source platform for building, shipping, and scaling AI applications.
+
+- Building
+    - Unifies ML frameworks to run inference with any pre-trained models or bring your own
+    - Multi-model Inference graph support for complex AI solutions
+    - Python first framework that integrates with any ecosystem tooling
+- Shipping
+    - Any environment, batch inference, streaming, or real-time serving
+    - Any public cloud for on-prem deployment
+    - Kubenetes native deployment
+- Scaling
+    - Efficient resource utilization with autoscaling
+    - Adaptive batching for higher efficiency and throughput
+    - Distributed microservice architecture to run services on the most optimal hardware
+
+## Workflow on Kubeflow Notebook
+
+In this example, we will train three fraud detection models using the Kubeflow notebook and the [Kaggle IEEE-CIS Fraud Detection dataset](https://www.kaggle.com/c/ieee-fraud-detection). We will then create a BentoML service that can simultaneously invoke all three models and return a decision on whether a transaction is fraudulent and build it into a Bento. We will showcase two deployment workflows using BentoML's Kubernetes operators: deploying directly from the Bento, and deploying from an OCI image built from the Bento.
+
+![image](https://raw.githubusercontent.com/bentoml/BentoML/main/docs/source/_static/img/kubeflow-fraud-detection.png)
+
+See the [Fraud Detection Example](https://github.com/bentoml/BentoML/tree/main/examples/kubeflow) for a detailed workflow from model training to end-to-end deployment on Kubernetes. 
+
+## Workflow on Kubeflow Pipeline
+
+This option will be available in Kubeflow release 1.8.
@@ -0,0 +1,35 @@
+# Upgrading Documentation
+
+## Updating manifests
+
+In order to update manifests make sure you are running the commands in linux.
+
+If you are running in another OS, please make sure to update the Makefile commands.
+
+You can refresh the configuration by running:
+
+```
+make bentoml-yatai-stack/base
+```
+
+## Updating to specific version
+
+Upgrading the version can be done by setting the `BENTOML_YATAI_STACK_VERSION` environment variable, such as:
+
+```
+# Set the desired version
+export BENTOML_YATAI_IMAGE_BUILDER_VERSION=1.1.0
+export BENTOML_YATAI_DEPLOYMENT_VERSION=1.1.0
+
+# Rebuild the kustomize bases
+make bentoml-yatai-stack/bases
+
+# Run new manifests against cluster
+kustomize build bentoml-yatai-stack/default | kubectl apply -f -
+```
+
+## Instructions for breaking changes
+
+The [Yatai upgrading docs](https://docs.bentoml.org/projects/yatai) provide step by step overview of breaking changes across minor and patch versions.
+
+
@@ -0,0 +1,2 @@
+resources:
+- resources.yaml
@@ -0,0 +1,2 @@
+resources:
+- resources.yaml
@@ -0,0 +1,6 @@
+# Adds namespace to all resources.
+namespace: kubeflow
+
+bases:
+- ../bases/yatai-image-builder
+- ../bases/yatai-deployment
@@ -0,0 +1,97 @@
+apiVersion: resources.yatai.ai/v1alpha1
+kind: Bento
+metadata:
+  name: fraud-detection
+  namespace: kubeflow
+spec:
+  image: docker.io/bentoml/fraud_detection:o5smnagbncigycvj
+  runners:
+  - name: ieee-fraud-detection-0
+    runnableType: XGBoost
+  - name: ieee-fraud-detection-1
+    runnableType: XGBoost
+  - name: ieee-fraud-detection-2
+    runnableType: XGBoost
+  tag: fraud_detection:o5smnagbncigycvj
+---
+apiVersion: serving.yatai.ai/v2alpha1
+kind: BentoDeployment
+metadata:
+  name: fraud-detection
+  namespace: kubeflow
+spec:
+  autoscaling:
+    maxReplicas: 2
+    metrics:
+    - resource:
+        name: cpu
+        target:
+          averageUtilization: 80
+          type: Utilization
+      type: Resource
+    minReplicas: 1
+  bento: fraud-detection
+  ingress:
+    enabled: false
+  resources:
+    limits:
+      cpu: 1000m
+      memory: 1024Mi
+    requests:
+      cpu: 100m
+      memory: 200Mi
+  runners:
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-0
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-1
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-2
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
@@ -0,0 +1,94 @@
+apiVersion: resources.yatai.ai/v1alpha1
+kind: BentoRequest
+metadata:
+  name: fraud-detection
+  namespace: kubeflow
+spec:
+  bentoTag: fraud_detection:o5smnagbncigycvj
+  downloadUrl: s3://bentoml.com/kubeflow/fraud_detection.bento
+  runners:
+  - name: ieee-fraud-detection-0
+  - name: ieee-fraud-detection-1
+  - name: ieee-fraud-detection-2
+---
+apiVersion: serving.yatai.ai/v2alpha1
+kind: BentoDeployment
+metadata:
+  name: fraud-detection
+  namespace: kubeflow
+spec:
+  autoscaling:
+    maxReplicas: 2
+    metrics:
+    - resource:
+        name: cpu
+        target:
+          averageUtilization: 80
+          type: Utilization
+      type: Resource
+    minReplicas: 1
+  bento: fraud-detection
+  ingress:
+    enabled: false
+  resources:
+    limits:
+      cpu: 1000m
+      memory: 1024Mi
+    requests:
+      cpu: 100m
+      memory: 200Mi
+  runners:
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-0
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-1
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
+  - autoscaling:
+      maxReplicas: 2
+      metrics:
+      - resource:
+          name: cpu
+          target:
+            averageUtilization: 80
+            type: Utilization
+        type: Resource
+      minReplicas: 1
+    name: ieee-fraud-detection-2
+    resources:
+      limits:
+        cpu: 1000m
+        memory: 1024Mi
+      requests:
+        cpu: 100m
+        memory: 200Mi
@@ -0,0 +1,2 @@
+resources:
+- resources.yaml
@@ -0,0 +1,20 @@
+yataiSystem:
+  namespace: "kubeflow"
+
+yatai:
+  endpoint: ''
+
+layers:
+  network:
+    ingressClass: nginx
+    ingressAnnotations: {}
+
+    ingressPath: /
+    ingressPathType: ImplementationSpecific
+
+    domainSuffix: ''
+
+    automaticDomainSuffixGeneration: false
+
+bentoDeploymentNamespaces: ["kubeflow"]
+
@@ -0,0 +1,13 @@
+yataiSystem:
+  namespace: "kubeflow"
+
+yatai:
+  endpoint: ''
+
+dockerRegistry:
+  bentoRepositoryName: yatai-bentos
+  inClusterServer: docker-registry.kubeflow.svc.cluster.local:5000
+  password: ""
+  secure: false
+  server: 127.0.0.1:5000
+  username: ""
@@ -0,0 +1,440 @@
+#!/bin/bash
+
+set -xe
+
+kubectl create ns kubeflow || echo "namespace kubeflow already exists"
+kustomize build bentoml-yatai-stack/default | kubectl apply --server-side -f -
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/yatai-image-builder
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/yatai-deployment
+sleep 5
+kubectl apply -n kubeflow -f deployment_from_bento.yaml
+sleep 5
+kubectl -n kubeflow logs deploy/yatai-deployment
+sleep 5
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/fraud-detection
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/fraud-detection-runner-0
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/fraud-detection-runner-1
+kubectl -n kubeflow wait --for=condition=available --timeout=600s deploy/fraud-detection-runner-2
+
+kubectl -n kubeflow port-forward svc/fraud-detection 3333:3000 &
+PID=$!
+
+function trap_handler {
+ kill $PID
+ kubectl -n kubeflow logs -l yatai.ai/bento-deployment=fraud-detection --tail=100
+ kubectl -n kubeflow delete -f deployment_from_bento.yaml
+ kustomize build bentoml-yatai-stack/default | kubectl delete -f -
+}
+
+trap trap_handler EXIT
+
+sleep 5
+
+# FIXME: getting AttributeError: 'ColumnTransformer' object has no attribute '_name_to_fitted_passthrough'
+# output=$(curl --fail -X 'POST' \
+#   'http://localhost:3333/is_fraud' \
+#   -H 'accept: application/json' \
+#   -H 'Content-Type: application/json' \
+#   -d '[
+#   {
+#     "TransactionID": 2987000,
+#     "TransactionDT": 86400,
+#     "TransactionAmt": 68.5,
+#     "ProductCD": "W",
+#     "card1": 13926,
+#     "card2": null,
+#     "card3": 150,
+#     "card4": "discover",
+#     "card5": 142,
+#     "card6": "credit",
+#     "addr1": 315,
+#     "addr2": 87,
+#     "dist1": 19,
+#     "dist2": null,
+#     "P_emaildomain": null,
+#     "R_emaildomain": null,
+#     "C1": 1,
+#     "C2": 1,
+#     "C3": 0,
+#     "C4": 0,
+#     "C5": 0,
+#     "C6": 1,
+#     "C7": 0,
+#     "C8": 0,
+#     "C9": 1,
+#     "C10": 0,
+#     "C11": 2,
+#     "C12": 0,
+#     "C13": 1,
+#     "C14": 1,
+#     "D1": 14,
+#     "D2": null,
+#     "D3": 13,
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+#     "V219": null,
+#     "V220": null,
+#     "V221": null,
+#     "V222": null,
+#     "V223": null,
+#     "V224": null,
+#     "V225": null,
+#     "V226": null,
+#     "V227": null,
+#     "V228": null,
+#     "V229": null,
+#     "V230": null,
+#     "V231": null,
+#     "V232": null,
+#     "V233": null,
+#     "V234": null,
+#     "V235": null,
+#     "V236": null,
+#     "V237": null,
+#     "V238": null,
+#     "V239": null,
+#     "V240": null,
+#     "V241": null,
+#     "V242": null,
+#     "V243": null,
+#     "V244": null,
+#     "V245": null,
+#     "V246": null,
+#     "V247": null,
+#     "V248": null,
+#     "V249": null,
+#     "V250": null,
+#     "V251": null,
+#     "V252": null,
+#     "V253": null,
+#     "V254": null,
+#     "V255": null,
+#     "V256": null,
+#     "V257": null,
+#     "V258": null,
+#     "V259": null,
+#     "V260": null,
+#     "V261": null,
+#     "V262": null,
+#     "V263": null,
+#     "V264": null,
+#     "V265": null,
+#     "V266": null,
+#     "V267": null,
+#     "V268": null,
+#     "V269": null,
+#     "V270": null,
+#     "V271": null,
+#     "V272": null,
+#     "V273": null,
+#     "V274": null,
+#     "V275": null,
+#     "V276": null,
+#     "V277": null,
+#     "V278": null,
+#     "V279": 0,
+#     "V280": 0,
+#     "V281": 0,
+#     "V282": 1,
+#     "V283": 1,
+#     "V284": 0,
+#     "V285": 0,
+#     "V286": 0,
+#     "V287": 0,
+#     "V288": 0,
+#     "V289": 0,
+#     "V290": 1,
+#     "V291": 1,
+#     "V292": 1,
+#     "V293": 0,
+#     "V294": 1,
+#     "V295": 0,
+#     "V296": 0,
+#     "V297": 0,
+#     "V298": 0,
+#     "V299": 0,
+#     "V300": 0,
+#     "V301": 0,
+#     "V302": 0,
+#     "V303": 0,
+#     "V304": 0,
+#     "V305": 1,
+#     "V306": 0,
+#     "V307": 117,
+#     "V308": 0,
+#     "V309": 0,
+#     "V310": 0,
+#     "V311": 0,
+#     "V312": 0,
+#     "V313": 0,
+#     "V314": 0,
+#     "V315": 0,
+#     "V316": 0,
+#     "V317": 117,
+#     "V318": 0,
+#     "V319": 0,
+#     "V320": 0,
+#     "V321": 0,
+#     "V322": null,
+#     "V323": null,
+#     "V324": null,
+#     "V325": null,
+#     "V326": null,
+#     "V327": null,
+#     "V328": null,
+#     "V329": null,
+#     "V330": null,
+#     "V331": null,
+#     "V332": null,
+#     "V333": null,
+#     "V334": null,
+#     "V335": null,
+#     "V336": null,
+#     "V337": null,
+#     "V338": null,
+#     "V339": null
+#   }
+# ]')
+
+# echo "output: '${output}'"
+# if [[ $output != *'false'* ]]; then
+#   echo "Test failed"
+#   exit 1
+# fi