From 04f00a8f54166d4d9807b9e3b3f47bf7f71ab48f Mon Sep 17 00:00:00 2001 From: Timna Brown <24630902+brown9804@users.noreply.github.com> Date: Mon, 28 Apr 2025 13:42:15 -0600 Subject: [PATCH 1/4] pipeline update-md-date --- .github/workflows/update-md-date.yml | 41 ++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) create mode 100644 .github/workflows/update-md-date.yml diff --git a/.github/workflows/update-md-date.yml b/.github/workflows/update-md-date.yml new file mode 100644 index 0000000..96dc9d7 --- /dev/null +++ b/.github/workflows/update-md-date.yml @@ -0,0 +1,41 @@ +name: Update Last Modified Date + +on: + pull_request: + branches: + - main + +permissions: + contents: write + +jobs: + update-date: + runs-on: ubuntu-latest + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.x' + + - name: Install dependencies + run: pip install python-dateutil + + - name: Configure Git + run: | + git config --global user.email "github-actions[bot]@users.noreply.github.com" + git config --global user.name "github-actions[bot]" + + - name: Update last modified date in Markdown files + run: python .github/workflows/update_date.py + + - name: Commit changes + run: | + git add -A + git commit -m "Update last modified date in Markdown files" || echo "No changes to commit" + git push origin HEAD:${{ github.event.pull_request.head.ref }} From 60f8993a213ac05831d08ab509c23c01fa27e8d7 Mon Sep 17 00:00:00 2001 From: Timna Brown <24630902+brown9804@users.noreply.github.com> Date: Mon, 28 Apr 2025 14:00:11 -0600 Subject: [PATCH 2/4] in progress 1% --- README.md | 19 +++++++++++++++++-- 1 file changed, 17 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index c5b1a47..cedf602 100644 --- a/README.md +++ b/README.md @@ -20,14 +20,29 @@ Last updated: 2025-02-21 +## Workspace + +## Authoring + +## Assets + +## Manage + +| Compute Type | Description | Purpose | Ideal Use Cases | Key Features | +|----------------------|-------------|---------|------------------|---------------| +| **Compute Instances** | Preconfigured VMs (CPU/GPU) with tools like VS Code, JupyterLab, and RStudio. | Interactive development and experimentation. | Data exploration, model prototyping, debugging. | Auto-shutdown, integrated notebooks, preinstalled ML frameworks. | +| **Compute Clusters** | Scalable clusters that auto-scale based on workload. Supports both CPU and GPU nodes. | Distributed training and batch inference. | Training large models, running parallel experiments. | Autoscaling, cost control, reusable across users. | +| **Kubernetes Clusters** | Includes AKS and attached Kubernetes clusters for production-grade deployments. | Real-time inference and scalable deployment. | Hosting REST endpoints, high-availability inference. | Load balancing, autoscaling, secure networking. | +| **Attached Compute** | External compute resources manually connected to Azure ML. | Leverage existing infrastructure. | Using Azure VMs, Databricks, or on-prem compute. | Flexibility, hybrid cloud support, reuse of existing resources. | +| **Serverless Instances** | Lightweight, on-demand compute (e.g., Azure Container Instances). | Quick testing and low-scale inference. | Temporary model deployment, dev/test environments. | No infrastructure management, fast startup, cost-effective. | + +
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Visitor Count From 0e2243987ed7dd767775e14a01c6ea0044592dad Mon Sep 17 00:00:00 2001 From: Timna Brown <24630902+brown9804@users.noreply.github.com> Date: Mon, 28 Apr 2025 14:06:47 -0600 Subject: [PATCH 3/4] format From 2606bec01e10802cc0282eb8448d929a7916f02c Mon Sep 17 00:00:00 2001 From: Timna Brown <24630902+brown9804@users.noreply.github.com> Date: Mon, 28 Apr 2025 14:07:47 -0600 Subject: [PATCH 4/4] + README.md --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index cedf602..279d557 100644 --- a/README.md +++ b/README.md @@ -37,7 +37,6 @@ Last updated: 2025-02-21 | **Serverless Instances** | Lightweight, on-demand compute (e.g., Azure Container Instances). | Quick testing and low-scale inference. | Temporary model deployment, dev/test environments. | No infrastructure management, fast startup, cost-effective. | -
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