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**Reason for Change**:
<!-- What does this PR improve or fix in KAITO? Why is it needed? -->
Ensures consistency when using `KAITO` acronym across documentation and
comments.
- Updated proposals
**Requirements**
- [ ] added unit tests and e2e tests (if applicable).
**Issue Fixed**:
<!-- If this PR fixes GitHub issue 4321, add "Fixes #4321" to the next
line. -->
Fixes#1397
**Notes for Reviewers**:
@@ -372,13 +372,13 @@ docker-build-llm-reference-preset: docker-buildx ## Build Docker image for LLM r
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--build-arg VERSION=$(VERSION).
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## --------------------------------------
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## Kaito Installation
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## KAITO Installation
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## --------------------------------------
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##@ Kaito Installation
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##@ KAITO Installation
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.PHONY: prepare-kaito-addon-identity
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prepare-kaito-addon-identity: ## Create Azure identity and federated credential for Kaito addon.
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prepare-kaito-addon-identity: ## Create Azure identity and federated credential for KAITO addon.
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IDENTITY_PRINCIPAL_ID=$(shell az identity show --name "ai-toolchain-operator-$(AZURE_CLUSTER_NAME)" -g "$(AZURE_RESOURCE_GROUP_MC)" --query 'principalId');\
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az role assignment create --assignee $$IDENTITY_PRINCIPAL_ID --scope "/subscriptions/$(AZURE_SUBSCRIPTION_ID)/resourceGroups/$(AZURE_RESOURCE_GROUP_MC)" --role "Contributor"
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## Get Involved!
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- Visit [#kaito channel in CNCF Slack](https://cloud-native.slack.com/archives/C09B4EWCZ5M) to discuss features in development and proposals.
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- Visit [#KAITO channel in CNCF Slack](https://cloud-native.slack.com/archives/C09B4EWCZ5M) to discuss features in development and proposals.
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- We host a weekly community meeting for contributors on Tuesdays at 4:00pm PST. Please join here: [meeting link](https://zoom-lfx.platform.linuxfoundation.org/meeting/99948431028?password=05912bb9-53fb-4b22-a634-ab5f8261e94c).
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- Reference the weekly meeting notes in our [KAITO community calls doc](https://docs.google.com/document/d/1OEC-WUQ2wn0TDQPsU09shMoXn5cW3dSrdu-M43Q79dA/edit?usp=sharing)!
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# Documentation Versioning Workflow
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This document explains how the automated documentation versioning workflow works in the Kaito project.
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This document explains how the automated documentation versioning workflow works in the KAITO project.
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## Overview
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The `docs-versioning.yaml` GitHub Actions workflow automatically creates versioned documentation when new minor versions are released. This ensures that users can access documentation for specific versions of Kaito.
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The `docs-versioning.yaml` GitHub Actions workflow automatically creates versioned documentation when new minor versions are released. This ensures that users can access documentation for specific versions of KAITO.
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# Title
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Support scale subresource api for workspace in kaito
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Support scale subresource api for workspace in KAITO
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## Summary
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As the number of waiting inference requests increase, It is necessary to scale more inference instances in order to preventing to block inference requests. on the other hand, If the number of waiting inference requests declines, we should consider to reduce inference instances for improving gpu resource utilization.
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We hope to provide an auto-scaler feature for scaling inference workloads automatically in terms of changes of custom metrics from inference pods, and this auto scaler doesn't depend on other components(this means Kaito is a self-contained component without dependencies). and we will divide this auto-scaler feature into two parts as following:
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We hope to provide an auto-scaler feature for scaling inference workloads automatically in terms of changes of custom metrics from inference pods, and this auto scaler doesn't depend on other components(this means KAITO is a self-contained component without dependencies). and we will divide this auto-scaler feature into two parts as following:
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- Part one: support scale subresource api for workspace, so different auto-scaler solutions such as KEDA, HPA, etc. can be integrated with Kaito to mamage inference workloads dynamically. This part is addressed in this proposal.
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- Part one: support scale subresource api for workspace, so different auto-scaler solutions such as KEDA, HPA, etc. can be integrated with KAITO to mamage inference workloads dynamically. This part is addressed in this proposal.
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- Part two: support a customized auto-sacler for kaito. The auto-scaler is designed for a minimalistic configuration experience, with most parameters pre-tuned for optimal performance. This allows users to easily get started without requiring specialized knowledge of LLM. This part will be addressed in another proposal.
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## Motivation
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LLM inference service is a baisc and widly-used feature in Kaito, and Kaito community interest in auto scaler for inference workloads continues to intensify, related issues: [#306](https://github.com/kaito-project/kaito/issues/306), [#1104](https://github.com/kaito-project/kaito/issues/1104).
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LLM inference service is a baisc and widly-used feature in KAITO, and KAITO community interest in auto scaler for inference workloads continues to intensify, related issues: [#306](https://github.com/kaito-project/kaito/issues/306), [#1104](https://github.com/kaito-project/kaito/issues/1104).
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From the technical perspective, It's a good idea to provide auto-scaler capability, becasue the auto-scaler of inference workloads dynamically adjusts the number of inference instances based on request volume--scaling up during traffic spikes to improve inference speed, and scaling down during low demand to minimize GPU resource waste.
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To ensure different auto-scaler solutions can integrate with Kaito to manage inference workloads dynamically, We aim to support scale subresource API for Workspace CRD in kaito.
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To ensure different auto-scaler solutions can integrate with KAITO to manage inference workloads dynamically, We aim to support scale subresource API for Workspace CRD in KAITO.
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title: Kaito Kubectl CLI Plugin
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title: KAITO Kubectl CLI Plugin
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authors:
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- "@helayoty"
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creation-date: 2025-06-30
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## Summary
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Kaito CLI provides a user-friendly kubectl extension for deploying and managing KAITO workspaces on Kubernetes. Kaito kubectl plugin aims to reduce friction for data scientists and ML engineers by abstracting away error-prone YAML authoring and enabling streamlined model deployment workflows. The initial focus is on core deployment and inference scenarios, with potential expansion to a standalone CLI if advanced features beyond kubectl's scope are needed.
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KAITO CLI provides a user-friendly kubectl extension for deploying and managing KAITO workspaces on Kubernetes. KAITO kubectl plugin aims to reduce friction for data scientists and ML engineers by abstracting away error-prone YAML authoring and enabling streamlined model deployment workflows. The initial focus is on core deployment and inference scenarios, with potential expansion to a standalone CLI if advanced features beyond kubectl's scope are needed.
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## Motivation
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### Kubectl Plugin
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A new kubectl plugin distributed through [Krew](https://github.com/kubernetes-sigs/krew) for Kaito that provides seamless integration with existing Kubernetes workflows.
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A new kubectl plugin distributed through [Krew](https://github.com/kubernetes-sigs/krew) for KAITO that provides seamless integration with existing Kubernetes workflows.
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Designed for engineers already comfortable with native Kubernetes tooling. By distributing the plugin through [Krew](https://github.com/kubernetes-sigs/krew), users avoid installing a separate binary, inherit their existing kube-contexts and RBAC, and benefit from familiar `kubectl` verb–noun syntax.
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