Merge branch 'Azure:main' into main

Author: idanielsteven

.github/CODEOWNERS

@@ -337,3 +337,5 @@
 /src/storage-discovery/ @shanefujs @calvinhzy
 
 /src/aks-agent/ @feiskyer @mainred @nilo19
+
+/src/migrate/ @saifaldin14

.github/workflows/TestTriggerExtensionRelease.yml

@@ -13,7 +13,7 @@ permissions:
 
 jobs:
     build:
-        name: Trigger Extension Release Pipeline
+        name: Test Trigger Extension Release Pipeline
         runs-on: ubuntu-latest
         steps:
         - name: Harden Runner
@@ -26,7 +26,7 @@ jobs:
             client-id: ${{ secrets.ADO_SP_ClientID }}
             tenant-id: ${{ secrets.ADO_SP_TenantID }}
             allow-no-subscriptions: true
-        - name: Trigger ADO Pipeline and Wait for Completion
+        - name: Test Trigger ADO Pipeline and Wait for Completion
           uses: azure/cli@v2
           env:
             ado-org: ${{secrets.ADO_ORGANIZATION}}
@@ -89,7 +89,7 @@ jobs:
                   exit 1
                 fi
                 
-                # Wait 30 seconds before checking again
-                echo "Build still running... waiting 30 seconds"
-                sleep 30
+                # Wait 60 seconds before checking again
+                echo "Build still running... waiting 60 seconds"
+                sleep 60
               done

.github/workflows/TriggerExtensionRelease.yml

@@ -26,7 +26,7 @@ jobs:
             client-id: ${{ secrets.ADO_SP_ClientID }}
             tenant-id: ${{ secrets.ADO_SP_TenantID }}
             allow-no-subscriptions: true
-        - name: Azure CLI
+        - name: Trigger ADO Pipeline and Wait for Completion
           uses: azure/cli@v2
           env:
             ado-org: ${{secrets.ADO_ORGANIZATION}}
@@ -35,4 +35,61 @@ jobs:
             commit-id: ${{ github.sha }}
           with:
             inlineScript: |
-              az pipelines build queue --definition-id ${{ env.ado-pipeline-id }} --organization ${{ env.ado-org }}  --project ${{ env.ado-project }} --variables commit_id=${{ env.commit-id }}
+              # Trigger the pipeline and capture the build ID
+              echo "Triggering ADO pipeline..."
+              BUILD_RESULT=$(az pipelines build queue \
+                --definition-id ${{ env.ado-pipeline-id }} \
+                --organization ${{ env.ado-org }} \
+                --project ${{ env.ado-project }} \
+                --variables commit_id=${{ env.commit-id }} \
+                --output json)
+              
+              BUILD_ID=$(echo $BUILD_RESULT | jq -r '.id')
+              echo "Pipeline triggered with Build ID: $BUILD_ID"
+              
+              if [ "$BUILD_ID" = "null" ] || [ -z "$BUILD_ID" ]; then
+                echo "Failed to get build ID from pipeline trigger"
+                exit 1
+              fi
+              
+              # Wait for the build to complete
+              echo "Waiting for build $BUILD_ID to complete..."
+              while true; do
+                BUILD_JSON=$(az pipelines build show \
+                  --id $BUILD_ID \
+                  --organization ${{ env.ado-org }} \
+                  --project ${{ env.ado-project }} \
+                  --output json)
+                
+                BUILD_STATUS=$(echo "$BUILD_JSON" | jq -r '.status')
+                BUILD_RESULT_STATUS=$(echo "$BUILD_JSON" | jq -r '.result // "none"')
+                
+                echo "Current status: $BUILD_STATUS, Result: $BUILD_RESULT_STATUS"
+                
+                # Check if build is completed
+                if [ "$BUILD_STATUS" = "completed" ]; then
+                  echo "Build completed with result: $BUILD_RESULT_STATUS"
+                  
+                  # Check if the build was successful
+                  if [ "$BUILD_RESULT_STATUS" = "succeeded" ]; then
+                    echo "✅ ADO pipeline build succeeded!"
+                    exit 0
+                  elif [ "$BUILD_RESULT_STATUS" = "partiallySucceeded" ]; then
+                    echo "⚠️ ADO pipeline build partially succeeded"
+                    exit 1
+                  else
+                    echo "❌ ADO pipeline build failed with result: $BUILD_RESULT_STATUS"
+                    exit 1
+                  fi
+                fi
+                
+                # Check for other terminal states
+                if [ "$BUILD_STATUS" = "cancelling" ] || [ "$BUILD_STATUS" = "cancelled" ]; then
+                  echo "❌ ADO pipeline build was cancelled"
+                  exit 1
+                fi
+                
+                # Wait 60 seconds before checking again
+                echo "Build still running... waiting 60 seconds"
+                sleep 60
+              done

scripts/ci/find_extension_upgraded.py

@@ -11,6 +11,32 @@ To release a new version, please select a new version number (usually plus 1 to
 
 Pending
 +++++++
+* Fix stdin reading hang in CI/CD pipelines by using select with timeout for non-interactive mode.
+* Update pytest marker registration and fix datetime.utcnow() deprecation warning in tests.
+* Improve test framework with real-time stderr output visibility and subprocess timeout.
+
+1.0.0b7
++++++++
+* Bump aks-mcp to v0.0.10 - here are the notable changes:
+  * Fix: Improved server health check endpoints /health for both HTTP and SSE connections for http, sse
+  * Fix: enforce json output for az monitor metrics and aks tools
+  * Fix: Build the resource URL with correct MCP endpoint path based on transport
+* Fix feedback slash command
+
+1.0.0b6
++++++++
+* Introduce the new `az aks agent-init` command for better cli interaction.
+* Separate llm configuration from main agent command for improved clarity and extensibility.
+
+1.0.0b5
++++++++
+* Bump holmesgpt to 0.15.0 - Enhanced AI debugging experience and bug fixes
+  * Added TODO list feature to allows holmes to reliably answers questions it wasn't able to answer before due to early-stopping
+  * Fixed mcp server http connection fails when using socks proxy by adding the missing socks dependency
+  * Fixed gpt-5 temperature bug by upgrading litellm and dropping non-1 values for temperature
+  * Improved the installation time by removing unnecessary dependencies and move test dependencies to dev dependency group
+* Added Feedback slash command Feature to allow users to provide feedback on their experience with the agent performance
+* Disable prometheus toolset loading by default to workaround the libbz2-dev missing issue in Azure CLI python environment.
 
 1.0.0b4
 +++++++

src/aks-agent/HISTORY.rst

@@ -4,32 +4,41 @@ Azure CLI AKS Agent Extension
 Introduction
 ============
 
-The AKS Agent extension provides the "az aks agent" command, an AI-powered assistant that
-helps analyze and troubleshoot Azure Kubernetes Service (AKS) clusters using Large Language
-Models (LLMs). The agent combines cluster context, configurable toolsets, and LLMs to answer
-natural-language questions about your cluster (for example, "Why are my pods not starting?")
-and can investigate issues in both interactive and non-interactive (batch) modes.
+
+The AKS Agent extension provides the "az aks agent" command, an AI-powered assistant that helps analyze and troubleshoot Azure Kubernetes Service (AKS) clusters using Large Language Models (LLMs). The agent combines cluster context, configurable toolsets, and LLMs to answer natural-language questions about your cluster (for example, "Why are my pods not starting?") and can investigate issues in both interactive and non-interactive (batch) modes.
+
+New in this version: **az aks agent-init** command for easy LLM model configuration!
+
+You can now use `az aks agent-init` to interactively add and configure LLM models before asking questions. This command guides you through the setup process, allowing you to add multiple models as needed. When asking questions with `az aks agent`, you can:
+
+- Use `--config-file` to specify your own model configuration file
+- Use `--model` to select a previously configured model
+- If neither is provided, the last configured LLM will be used by default
+
+This makes it much easier to manage and switch between multiple models for your AKS troubleshooting workflows.
 
 Key capabilities
 ----------------
 
+
 - Interactive and non-interactive modes (use --no-interactive for batch runs).
-- Support for multiple LLM providers (Azure OpenAI, OpenAI, etc.) via environment variables.
-- Configurable via a JSON/YAML config file provided with --config-file.
+- Support for multiple LLM providers (Azure OpenAI, OpenAI, etc.) via interactive configuration.
+- **Easy model setup with `az aks agent-init`**: interactively add and configure LLM models, run multiple times to add more models.
+- Configurable via a JSON/YAML config file provided with --config-file, or select a model with --model.
+- If no config or model is specified, the last configured LLM is used automatically.
 - Control echo and tool output visibility with --no-echo-request and --show-tool-output.
 - Refresh the available toolsets with --refresh-toolsets.
 - Stay in traditional toolset mode by default, or opt in to aks-mcp integration with ``--aks-mcp`` when you need the enhanced capabilities.
 
 Prerequisites
 -------------
-
-Before using the agent, make sure provider-specific environment variables are set. For
-example, Azure OpenAI typically requires AZURE_API_BASE, AZURE_API_VERSION, and AZURE_API_KEY,
-while OpenAI requires OPENAI_API_KEY. For more details about supported providers and required
+No need to manually set environment variables! All model and credential information can be configured interactively using `az aks agent-init`.
+For more details about supported model providers and required
 variables, see: https://docs.litellm.ai/docs/providers
 
+
 Quick start and examples
-========================
+=========================
 
 Install the extension
 ---------------------
@@ -38,25 +47,58 @@ Install the extension
 
     az extension add --name aks-agent
 
-Run the agent (Azure OpenAI example)
+Configure LLM models interactively
+----------------------------------
+
+.. code-block:: bash
+
+    az aks agent-init
+
+This command will guide you through adding a new LLM model. You can run it multiple times to add more models or update existing models. All configured models are saved locally and can be selected when asking questions.
+
+Run the agent (Azure OpenAI example) :
 -----------------------------------
 
+**1. Use the last configured model (no extra parameters needed):**
+
 .. code-block:: bash
 
-    export AZURE_API_BASE="https://my-azureopenai-service.openai.azure.com/"
-    export AZURE_API_VERSION="2025-01-01-preview"
-    export AZURE_API_KEY="sk-xxx"
+    az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup
+
+**2. Specify a particular model you have configured:**
+
+.. code-block:: bash
 
     az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model azure/my-gpt4.1-deployment
 
+**3. Use a custom config file:**
+
+.. code-block:: bash
+
+    az aks agent "Why are my pods not starting?" --config-file /path/to/your/model_config.yaml
+
+
 Run the agent (OpenAI example)
 ------------------------------
 
+**1. Use the last configured model (no extra parameters needed):**
+
 .. code-block:: bash
 
-    export OPENAI_API_KEY="sk-xxx"
+    az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup
+
+**2. Specify a particular model you have configured:**
+
+.. code-block:: bash
+    
     az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model gpt-4o
 
+**3. Use a custom config file:**
+
+.. code-block:: bash
+
+    az aks agent "Why are my pods not starting?" --config-file /path/to/your/model_config.yaml
+
 Run in non-interactive batch mode
 ---------------------------------