Python Appservice Deploy — Agent Skill by Microsoft

From the author

Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured, idempotent workflow for deploying Python applications (Flask, Django, FastAPI) to Azure App Service on Linux. It handles the creation of necessary Azure resources—including Resource Groups, App Service Plans (P0v3), and Web Apps—while enforcing best practices like server-side builds and proper startup configuration. The process includes automated normalization of shell scripts to ensure compatibility and provides a reliable path for both standard CLI-based deployments and those utilizing Azure Developer CLI (azd) configurations.

What it does

Automatically creates or validates Azure Resource Groups, App Service Plans, and Web Apps.
Configures server-side builds via SCM_DO_BUILD_DURING_DEPLOYMENT.
Normalizes Linux shell scripts to prevent line-ending issues during deployment.
Sets appropriate startup commands for FastAPI applications.
Packages the application code into a clean ZIP archive, excluding unnecessary files.
Supports both standard Azure CLI and azd-based deployment workflows.

When to use it

When you need to deploy a Python Flask, Django, or FastAPI application to Azure App Service Linux.
When you want to automate the provisioning of the required Azure infrastructure alongside the code deployment.
When you need a repeatable, error-checked deployment process for Python web apps.
When you are working with a standard Python project structure and require a reliable deployment pipeline.

Advantages

Reduces manual configuration by deriving sensible defaults for resource names and regions.
Ensures cross-platform compatibility by normalizing line endings in scripts.
Prevents common deployment failures through pre-packaging validation.
Provides a consistent, idempotent approach to resource creation.
Integrates seamlessly with existing Azure CLI and azd workflows.

Usage examples

“Deploy my Flask app to Azure App Service.”: The agent will prompt for an app name, then automatically create the necessary Resource Group, P0v3 Linux App Service Plan, and Web App, finally deploying the code.
“Deploy my FastAPI project to Azure.”: The agent will configure the Web App with the required uvicorn startup command and deploy the code to an Azure App Service Linux instance.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/python-appservice-deploy/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip python-appservice-deploy.zip -d .agents/skills

Documentation by Microsoft

Python on Azure App Service — Code Deploy

Deploys Python (Flask, Django, FastAPI, generic) code to Azure App Service Linux (P0v3, Python 3.14). Creates RG + Plan + Web App if missing. Hand off to azure-prepare for VNet, Key Vault, databases, or IaC.

MCP tools used: mcp_azure_mcp_subscription_list, mcp_azure_mcp_group_list, mcp_azure_mcp_appservice, mcp_azure_mcp_azd (when azure.yaml is present).

Workflow

Prerequisite: Verify the latest stable Azure CLI; update with approval and recheck if needed.

Resolve context — smart defaults, minimal prompts. Only the app name is interactive; RG (<app>-rg), Plan (<app>-plan), region (current az default or eastus2), subscription are derived. create-app.md §1.
Detect framework (advisory, never blocks). detect.md.
Choose path — azure.yaml host: appservice → deploy-azd.md; else deploy-azcli.md.
Ensure RG → Plan (P0v3 --is-linux) → Web App (--runtime "PYTHON:3.14") exist. Before creating a plan, invoke azure-quotas to check quota availability. On transient ARM errors, follow transient-retry.md. create-app.md.
Set startup — Flask/Django: none (Oryx auto-detects). FastAPI: always python -m uvicorn main:app --host 0.0.0.0. Other: warn. startup-commands.md.
Set SCM_DO_BUILD_DURING_DEPLOYMENT=true.
Deploy — azd deploy or az webapp deploy --type zip --track-status false --enriched-errors true.
STOP. Print the post-deploy message (post-deploy-message.md) and end the turn.

Hard rules

LINUX SCRIPTS — normalize selected shell/startup files to LF, then verify no CR bytes remain. Stop on normalization, validation or packaging failure; deploy only a fresh package.
DJANGO REMOTE BUILDS — require STATIC_ROOT and successful system/collectstatic checks before packaging.
⛔ NO POST-DEPLOY VERIFICATION — after deploy returns, do not run az webapp log tail, curl, Invoke-WebRequest, or any health probe. App Service needs 2–3 min to warm; a quiet log or early 5xx is not failure.
⛔ SHELL SAFETY — for --runtime always use "PYTHON:3.14" (colon). Never "PYTHON|3.14" (pipe is a shell operator).
⛔ NEVER az webapp up — deprecated. Use Step 7 commands.
✅ URL FORMAT — present endpoints as https://... URLs.

Error Handling

See errors.md for the full symptom → cause → fix matrix. Quick triage: missing plan/app → re-run Step 4; container ping timeout on 8000 → fix startup (Step 5); ModuleNotFoundError after deploy → ensure Step 6 ran, redeploy.

Files

ATTRIBUTION.mdAdded by AutoGineer1004 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md3.2 KiB
references/create-app.md6.2 KiB
references/deploy-azcli.md6.8 KiB
references/deploy-azd.md3.4 KiB
references/detect.md3.6 KiB
references/errors.md3.8 KiB
references/post-deploy-message.md4.4 KiB
references/startup-commands.md4.3 KiB
references/transient-retry.md2.3 KiB
scripts/generate-app-name.ps1Script1.7 KiB
scripts/generate-app-name.shScript1.8 KiB
scripts/retry-az-create.ps1Script2.1 KiB
scripts/retry-az-create.shScript1.9 KiB

scripts/retry-az-create.ps1

<#
.SYNOPSIS
    Wraps an idempotent `az ... show || az ... create` pair with silent
    retries against transient ARM frontend errors.
.DESCRIPTION
    Mirrors retry-az-create.sh. Runs the show command first (short-circuits
    a partially-succeeded prior attempt and avoids false NameAlreadyExists
    errors). If show fails, runs create. On transient failure (connection
    resets, 429/502/503/504, timeouts) retries up to 2 times with 5s then
    15s backoff. Non-transient failures surface the original error and
    exit 1.
.PARAMETER ShowCommand
    The full `az ... show ...` command line as a single string.
.PARAMETER CreateCommand
    The full `az ... create ...` command line as a single string.
.EXAMPLE
    .\retry-az-create.ps1 `
        -ShowCommand "az group show -n my-rg --only-show-errors" `
        -CreateCommand "az group create -n my-rg -l eastus2"
.EXAMPLE
    .\retry-az-create.ps1 `
        -ShowCommand "az appservice plan show -n my-plan -g my-rg --only-show-errors" `
        -CreateCommand "az appservice plan create -n my-plan -g my-rg --is-linux --sku P0v3 -l eastus2"
#>
param(
    [Parameter(Mandatory)][string]$ShowCommand,
    [Parameter(Mandatory)][string]$CreateCommand
)

$ErrorActionPreference = "Continue"

$transient = 'Connection reset|Connection aborted|ConnectionError|Read timed out|BadGatewayConnection|ServiceUnavailable|Max retries exceeded|TooManyRequests|\b429\b|\b50[234]\b'
$backoff = @(5, 15)

for ($attempt = 1; $attempt -le 3; $attempt++) {
    # Try `show` silently first; if it fails, try `create`. Capture both
    # stdout and stderr into $err so we can inspect for transient patterns.
    $err = & {
        $script = "$ShowCommand -o none 2>`$null; if (`$LASTEXITCODE -ne 0) { $CreateCommand -o none }"
        & powershell -NoProfile -Command $script 2>&1
    } | Out-String

    if ($LASTEXITCODE -eq 0) {
        exit 0
    }

    if ($err -notmatch $transient) {
        Write-Error $err
        exit 1
    }

    if ($attempt -eq 3) {
        Write-Error $err
        Write-Error "ARM frontend is returning transient errors — please retry in a few minutes."
        exit 1
    }

    Start-Sleep -Seconds $backoff[$attempt - 1]
}

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

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