Azure Prepare

MicrosoftOfficialCreated by Microsoft

Skill
Workflow
Cloud and DevOps
MIT
Medium risk
Has scripts

From the author

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

— the description by Microsoft

AutoGineer summary

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

The azure-prepare skill provides a mandatory, structured workflow for setting up applications for deployment to Azure via the Azure Developer CLI (azd). It enforces a plan-first approach, requiring the creation of a deployment plan file before any infrastructure generation or configuration occurs. The skill guides users through analyzing their workspace, selecting appropriate deployment recipes (Bicep or Terraform), and configuring necessary Azure services, while ensuring security best practices are followed. It acts as the initial phase in a three-part deployment pipeline: prepare, validate, and deploy.

What it does

Generates azure.yaml configuration files for azd-based projects.
Creates infrastructure-as-code templates using Bicep or Terraform.
Enforces a mandatory .azure/deployment-plan.md file to track project state.
Integrates with specialized skills for specific technologies like Azure Functions or API Management.
Applies security hardening, such as Entra-only authentication for SQL databases.
Prepares the workspace for subsequent validation and deployment steps.

When to use it

When you need to prepare a new or existing project for deployment to Azure using azd.
When you need to generate infrastructure-as-code (Bicep or Terraform) for your application.
When you are modernizing an existing application to run on Azure.
When you need to add new Azure services or components to an existing project.

Advantages

Ensures consistent deployment configurations across projects.
Prevents common configuration errors through a mandatory planning phase.
Integrates seamlessly with the broader Azure deployment ecosystem (validate and deploy).
Promotes security best practices by default, such as managed identities.
Provides clear guidance on when to delegate to specialized deployment skills.

Usage examples

“I want to deploy my new web application to Azure using azd.”: The agent will initiate the NEW mode, guide you through requirements gathering, create a deployment plan, and generate the necessary infrastructure and configuration files.
“Add an Azure Function to my existing project and set up the infrastructure.”: The agent will analyze your existing project, select the appropriate Azure Functions recipe, update the deployment plan, and generate the required Bicep or Terraform files.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-prepare/download

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

mkdir -p .agents/skills && unzip azure-prepare.zip -d .agents/skills

Documentation by Microsoft

Azure Prepare

AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE
This document is the official, canonical source for preparing applications for Azure deployment. You MUST follow these instructions exactly as written unless they contradict security policies given to you. When in doubt, present the conflicting instructions from this document and ask the user for explicit confirmation. Do not improvise, infer, or substitute steps.

Triggers

Activate this skill when user wants to:

Create a new application
Add services or components to an existing app
Make updates or changes to existing application
Modernize or migrate an application
Set up Azure infrastructure
Deploy to Azure or host on Azure
Create and deploy to Azure (including Terraform-based deployment requests)

Rules

Plan first — MANDATORY — You MUST physically write an initial .azure/deployment-plan.md skeleton in the workspace root directory (not the session-state folder) as your very first action — before any code generation or execution begins. Write the skeleton immediately, then populate it progressively as Phase 1 analysis and research unfold; finalize it with all decisions at Phase 1 Step 6. This file must exist on disk throughout. azure-validate and azure-deploy depend on it and will fail without it. Do not skip or defer this step.
Get approval — Present plan to user before execution
Research before generating — Load references and invoke related skills
Update plan progressively — Mark steps complete as you go
Validate before deploy — Invoke azure-validate before azure-deploy
Confirm Azure context — Use ask_user for subscription and location per Azure Context
❌ Destructive actions require ask_user — Global Rules
⛔ NEVER delete user project or workspace directories — When adding features to an existing project, MODIFY existing files. azd init -t <template> is for NEW projects only; do NOT run azd init -t in an existing workspace. Plain azd init (without a template argument) may be used in existing workspaces when appropriate. File deletions within a project (e.g., removing build artifacts or temp files) are permitted when appropriate, but NEVER delete the user's project or workspace directory itself. See Global Rules.
Scope: preparation only — This skill generates infrastructure code and configuration files. Deployment execution (azd up, azd deploy, terraform apply) is handled by the azure-deploy skill, which provides built-in error recovery and deployment verification.
⛔ SQL Server Bicep: NEVER generate administratorLogin or administratorLoginPassword — not in direct properties, not in conditional/ternary branches, not anywhere in the file. Always use Entra-only authentication (azureADOnlyAuthentication: true) unconditionally. See references/services/sql-database/bicep.md.
Remove stale template IaC after conversion — If you converted Bicep templates from the selected azd template into Terraform templates, remove the Bicep templates that were introduced by that azd template and are now fully replaced by Terraform equivalents. Do not remove user-authored Bicep files. Only remove those template-provided Bicep files after the Terraform IaC is complete and Terraform has been selected as the deployment path. Before handing off to azure-validate skill, keep only the IaC templates required by the chosen deployment path.

❌ PLAN-FIRST WORKFLOW — MANDATORY

YOU MUST CREATE A PLAN BEFORE DOING ANY WORK
STOP — Do not generate any code, infrastructure, or configuration yet
CREATE SKELETON - Write an initial .azure/deployment-plan.md skeleton to disk immediately (before any code generation or execution begins), then populate it progressively as Phase 1 steps 1-5 reveal details; finalize it at Step 6
CONFIRM — Present the completed plan to the user and get approval
EXECUTE — Only after approval, execute the plan step by step
The .azure/deployment-plan.md file is the source of truth for this workflow and for azure-validate and azure-deploy skills. Without it, those skills will fail.
⚠️ CRITICAL: .azure/deployment-plan.md must be WRITTEN TO DISK inside the workspace root (e.g., <workspace-root>/.azure/deployment-plan.md), not in the session-state folder. Use a file-write tool to create this file. This is the deployment plan artifact read by azure-validate and azure-deploy. You MUST create this file — do not proceed without it. ⚠️ CRITICAL: You must create the file with the name .azure/deployment-plan.md as is. You must not use other names such as .azure/plan.md.
⛔ Critical: Skipping the plan file creation will cause azure-validate and azure-deploy to fail. This requirement has no exceptions.

❌ STEP 0: Specialized Technology Check — MANDATORY FIRST ACTION

BEFORE starting Phase 1, check if the user's prompt OR workspace codebase matches a specialized technology that has a dedicated skill with tested templates. If matched, invoke that skill FIRST — then resume azure-prepare for validation and deployment.

Check 1: Prompt keywords

Prompt keywords	Invoke FIRST
Python + App Service (e.g., "deploy Python to App Service", "Flask on Azure App Service", "publish Python web app to App Service")	python-appservice-deploy
Lambda, AWS Lambda, migrate AWS, migrate GCP, Lambda to Functions, migrate from AWS, migrate from GCP	azure-cloud-migrate
Azure Functions, function app, serverless function, timer trigger, HTTP trigger, func new	Stay in azure-prepare — prefer Azure Functions templates in Step 4; for plan choice/cold starts see hosting-plans.md and cold-start.md
APIM, API Management, API gateway, deploy APIM	Stay in azure-prepare — see APIM Deployment Guide
AI gateway, AI gateway policy, AI gateway backend, AI gateway configuration	azure-aigateway
workflow, orchestration, multi-step, pipeline, fan-out/fan-in, saga, long-running process, durable, order processing	Stay in azure-prepare — select durable recipe in Step 4. MUST load durable.md, DTS reference, and DTS Bicep patterns.

⚠️ Check the user's prompt text — not just existing code. Critical for greenfield projects with no codebase to scan. See full routing table.

After the specialized skill completes, resume azure-prepare at Phase 1 Step 4 (Select Recipe) for remaining infrastructure, validation, and deployment.

Phase 1: Planning (BLOCKING — Complete Before Any Execution)

Create .azure/deployment-plan.md by completing these steps. Do NOT generate any artifacts until the plan is approved.

#	Action	Reference
0	If the prompt matches a specialized technology with a dedicated skill, invoke that skill first	specialized-routing.md
1	Analyze Workspace — Determine mode: NEW, MODIFY, or MODERNIZE	analyze.md
2	Gather Requirements — Classification, scale, budget	requirements.md
3	Scan Codebase — Identify components, technologies, dependencies	scan.md
4	Select Recipe — Choose AZD (default), AZCLI, Bicep, or Terraform	recipe-selection.md
5	Plan Architecture — Select stack + map components to Azure services	architecture.md
6	Finalize Plan (MANDATORY) - Use a file-write tool to finalize `.azure/deployment-plan.md` with all decisions from steps 1-5. Update the skeleton written at the start of Phase 1 with the complete content. The file must be fully populated before you present the plan to the user.	plan-template.md
7	Present Plan — Show plan to user and ask for approval	`.azure/deployment-plan.md`
8	Destructive actions require `ask_user`	Global Rules

❌ STOP HERE — Do NOT proceed to Phase 2 until the user approves the plan.

Phase 2: Execution (Only After Plan Approval)

Execute the approved plan. Update .azure/deployment-plan.md status after each step.

#	Action	Reference
1	Research Components — Load service references + invoke related skills	research.md
2	Confirm Azure Context — Detect and confirm subscription + location and check the resource provisioning limit	Azure Context
3	Generate Artifacts — Create infrastructure and configuration files	generate.md
4	Harden Security — Apply security best practices	security.md
5	Functional Verification — Verify the app works (UI + backend), locally if possible	functional-verification.md
6	⛔ Update Plan (MANDATORY before hand-off) — Use the `edit` tool to change the Status in `.azure/deployment-plan.md` to `Ready for Validation`. You MUST complete this edit BEFORE invoking azure-validate. Do NOT skip this step.	`.azure/deployment-plan.md`
7	⛔ MANDATORY Hand Off — Invoke azure-validate skill. Your preparation work is done. Do NOT run `azd up`, `azd deploy`, or any deployment command directly — all deployment execution is handled by azure-deploy after azure-validate completes. PREREQUISITE: Step 6 must be completed first — `.azure/deployment-plan.md` status must say `Ready for Validation`.	—

Outputs

Artifact	Location
Plan	`.azure/deployment-plan.md`
Infrastructure	`./infra/`
AZD Config	`azure.yaml` (AZD only)
Dockerfiles	`src/<component>/Dockerfile`

SDK Quick References

Azure Developer CLI: azd
Azure Identity: Python | .NET | TypeScript | Java
App Configuration: Python | TypeScript | Java

⛔ MANDATORY NEXT STEP — DO NOT SKIP
After completing preparation, you MUST invoke azure-validate before any deployment attempt. Do NOT skip validation. Do NOT go directly to azure-deploy. Do NOT run azd up or any deployment command directly. The workflow is:
azure-prepare → azure-validate → azure-deploy
⛔ BEFORE invoking azure-validate, you MUST use the edit tool to update .azure/deployment-plan.md status to Ready for Validation. If the plan status has not been updated, the validation will fail.
This applies to ALL deployment scenarios including containerized apps, Container Apps, App Service, Azure Functions, static sites, and any other Azure target. No exceptions.
Skipping validation leads to deployment failures. Be patient and follow the complete workflow for the highest success outcome.

→ Update plan status to Ready for Validation, then invoke azure-validate

Files

references/services/functions/templates/recipes/composition.md

Composition Algorithm

Combine multiple templates into a single deployable project.

Azure MCP Path

INPUT: language, user_requirements
OUTPUT: Complete project ready for `azd up`

1. DISCOVER
   functions_template_get(language) → template list with descriptions

2. CHECK SINGLE-TEMPLATE MATCH
   If one template's description covers ALL requirements → use it alone

3. SELECT TEMPLATES
   - Trigger template (REQUIRED) — base project with IaC
   - Binding templates (OPTIONAL) — extract patterns only

4. FETCH TEMPLATES
   - Single match: 1 call
   - Multiple: parallel calls

5. COMPOSE
   - Use trigger template as BASE (functionFiles + projectFiles)
   - EXTRACT binding patterns from binding templates
   - MERGE IaC resources and RBAC roles
   - ADD user's custom business logic

6. TRIM unused demo code (keep AzureWebJobsStorage)

7. WRITE files — for each entry { path, content } in functionFiles[] AND projectFiles[]:
      a. Create parent directories from path
      b. Write content to path
      NEVER hand-write Bicep/Terraform and use azd init -t/func init/func new as fallback when composing multiple recipes and required templates are not found

8. DEPLOY: azd up --no-prompt

Fallback Path (Azure MCP Unavailable)

INPUT: language, user_requirements
OUTPUT: Complete project ready for `azd up`

1. FETCH MANIFEST
   GET https://cdn.functions.azure.com/public/templates-manifest/manifest.json
   If fetch fails → fall back to: https://github.com/Azure/azure-functions-templates/blob/dev/Functions.Templates/Template-Manifest/manifest.json
   If both fail → fall back to known-good Azure-Samples/functions-quickstart-* repos by language+resource
   If all fail → report error and ask user to retry later

2. FILTER TEMPLATES
   Filter by: language, resource (from selection.md), iac

3. CHECK SINGLE-TEMPLATE MATCH
   If one template covers ALL requirements → use it alone

4. SELECT TEMPLATES
   - Trigger template (REQUIRED) — base project
   - Binding templates (OPTIONAL) — extract patterns only

5. DOWNLOAD TEMPLATES
   For each template:
   - If folderPath == "." → ZIP download + unzip
   - If folderPath != "." → fetch tree + raw github url file downloads
   - Fallback: git clone --depth 1

6. COMPOSE
   - Use trigger template as BASE
   - EXTRACT binding patterns from binding templates
   - MERGE IaC resources, RBAC roles and settings, README and other files.
   - ADD user's custom business logic

7. TRIM unused demo code (keep AzureWebJobsStorage)

8. WRITE all files

9. DEPLOY: azd up --no-prompt

Example (MCP)

User: "HTTP function that writes to Cosmos DB"

1. Discover: functions_template_get(language: "python") → returns template list
2. Check: No single template description mentions BOTH HTTP trigger AND Cosmos output
3. Select from discovered list:
   - Template with resource: "http" (trigger, base)
   - Template with resource: "cosmos" and description mentioning "output" (binding)
4. Fetch both templates by templateName from discovery results
5. Compose:
   - Base: HTTP template (has IaC, azure.yaml)
   - Extract: Cosmos output binding + RBAC from cosmos template
   - Merge: Add Cosmos module to infra/main.bicep
6. Trim: Remove HTTP demo response code
7. Write files
8. Deploy

Example (Fallback)

User: "HTTP function that writes to Cosmos DB"

1. Fetch: GET manifest.json from CDN
2. Filter: language=Python, resource=http OR resource=cosmos, iac=bicep
3. Check: No single template covers both
4. Select:
   - http-trigger-python-azd (trigger, base) → repositoryUrl + folderPath
   - cosmos-trigger-python-azd (binding) → repositoryUrl + folderPath
5. Download: ZIP download both repos (folderPath = ".")
6. Compose:
   - Base: HTTP template (has infra/, azure.yaml)
   - Extract: Cosmos IaC module + RBAC from cosmos template
   - Merge: Add cosmos.bicep to infra/app/, wire into main.bicep
7. Trim: Remove demo code
8. Write files
9. Deploy

Critical Rules

NEVER hardcode template names — always discover/fetch manifest first
PRESERVE generated IaC patterns — keep RBAC roles, managed identity config, and security settings intact when merging
ALWAYS keep AzureWebJobsStorage — runtime requires it
ALWAYS use --no-prompt — the agent must never elicit user input during azd commands
ALWAYS include ALL THREE UAMI settings for every binding — see UAMI Configuration below
ALWAYS wait for RBAC propagation — use two-phase deploy if 403 errors occur
NEVER enable allowSharedKeyAccess: true — correct solution is waiting for RBAC, not disabling security

IaC Merge Guidelines

When composing multiple templates:

Action	Allowed	Not Allowed
Add resource modules from binding templates	✅
Add RBAC role assignments from binding templates	✅
Merge environment variables	✅
Remove RBAC roles		❌
Change managed identity to connection strings		❌
Remove security configurations		❌
Modify resource SKUs without user request		❌

Merge = additive combination, not modification of security patterns.

UAMI Configuration (CRITICAL)

Templates use User Assigned Managed Identity (UAMI). ALL service bindings require explicit credential and clientId app settings. Missing these causes 500/401/403 errors at runtime.

Required pattern for EVERY service binding:

appSettings: {
  // Endpoint (varies by service)
  EventHubConnection__fullyQualifiedNamespace: eventhubs.outputs.fullyQualifiedNamespace
  // UAMI credentials - REQUIRED, prefix vary by example
  EventHubConnection__credential: 'managedidentity'
  EventHubConnection__clientId: apiUserAssignedIdentity.outputs.clientId
}

Validation Checklist (MANDATORY before deploy):

Setting Pattern	Required	Example
`{Connection}__fullyQualifiedNamespace` or `{Connection}__accountEndpoint`	✅	`EventHubConnection__fullyQualifiedNamespace`
`{Connection}__credential`	✅	`'managedidentity'` (exact case)
`{Connection}__clientId`	✅	`apiUserAssignedIdentity.outputs.clientId`

⛔ STOP if any check fails. The function WILL fail at runtime with 500/Unauthorized errors.

Language-Specific Entry Points

Node.js (JavaScript/TypeScript)

⛔ Do NOT delete src/index.js (JS) or src/index.ts (TS). This file contains app.setup() which initializes the Functions runtime. Without it, functions deploy but return 404 on all endpoints.

⛔ Glob pattern REQUIRED in package.json:
{ "main": "src/{index.js,functions/*.js}" }
Using "main": "src/index.js" alone results in 404 on ALL endpoints.

⛔ package.json must be at project ROOT (same level as azure.yaml), NOT inside src/.

📦 TypeScript: Run npm run build before deployment. Use: "main": "dist/src/{index.js,functions/*.js}"

C# (.NET)

⛔ Do NOT replace Program.cs from the base template. The base template uses ConfigureFunctionsWebApplication() with App Insights integration. Recipes only ADD trigger function files (.cs) and package references (.csproj).

Deployment Strategy

Option A: Single command (fast, may fail on first deploy due to RBAC propagation)

azd up --no-prompt

Option B: Two-phase (recommended for reliability)

azd provision --no-prompt     # Create resources + RBAC assignments
sleep 60                       # Wait for RBAC propagation (Azure AD needs 30-60s)
azd deploy --no-prompt        # Deploy code (RBAC now active)

Terraform-Specific Requirements

⚠️ CRITICAL: All Terraform must use sku_name = "FC1" (Flex Consumption). NEVER use Y1/Dynamic.

Runtime Versions

⚠️ ALWAYS QUERY OFFICIAL DOCUMENTATION — Do NOT use hardcoded versions.
Primary Source: Azure Functions Supported Languages
Query for latest GA/LTS versions before generating IaC.

Language	`function_runtime`	Version Source
C# (.NET)	`dotnet-isolated`	Latest LTS from docs
TypeScript/JS	`node`	Latest LTS from docs
Python	`python`	Latest GA from docs
Java	`java`	Latest LTS from docs
PowerShell	`powershell`	Latest GA from docs

Flex Consumption (FC1) Requires azapi

⚠️ Use azapi_resource instead of azurerm_linux_function_app for FC1. The AzureRM provider doesn't support FC1's functionAppConfig block.

resource "azapi_resource" "function_app" {
  type      = "Microsoft.Web/sites@2023-12-01"
  name      = "func-${local.name}"
  location  = azurerm_resource_group.rg.location
  parent_id = azurerm_resource_group.rg.id

  body = {
    kind = "functionapp,linux"
    properties = {
      serverFarmId = azapi_resource.plan.id
      functionAppConfig = {
        runtime = { name = "node", version = "22" }
        scaleAndConcurrency = { maximumInstanceCount = 100, instanceMemoryMB = 2048 }
        deployment = {
          storage = {
            type  = "blobContainer"
            value = "${azurerm_storage_account.storage.primary_blob_endpoint}deploymentpackage"
            authentication = {
              type                           = "UserAssignedIdentity"
              userAssignedIdentityResourceId = azurerm_user_assigned_identity.api.id
            }
          }
        }
      }
    }
  }
  depends_on = [time_sleep.rbac_propagation]
}

RBAC Propagation Delay

Azure RBAC takes 30-60s to propagate. Terraform's depends_on only waits for resource creation, not RBAC propagation.

Solution 1: Add time_sleep resource

resource "time_sleep" "rbac_propagation" {
  depends_on      = [azurerm_role_assignment.storage_blob_owner]
  create_duration = "60s"
}

resource "azapi_resource" "function_app" {
  depends_on = [time_sleep.rbac_propagation]
  # ...
}

Solution 2: Create deployment container explicitly

resource "azurerm_storage_container" "deployment" {
  name                  = "deploymentpackage"
  storage_account_id    = azurerm_storage_account.storage.id
  container_access_type = "private"
  depends_on            = [azurerm_role_assignment.storage_blob_owner]
}

⚠️ Common Failures Without These Fixes:
403 Forbidden — RBAC not yet propagated
404 Container Not Found — deployment container not created
Tag Not Found: azd-service-name — Azure resource tags take time to be queryable

Required: azd-service-name Tag

tags = {
  "azd-service-name" = "api"   # MUST match service name in azure.yaml
}

⚠️ Without this tag, azd deploy fails with: resource not found: unable to find a resource tagged with 'azd-service-name: api'

Disabled Local Auth (Policy Required)

Azure Policy often enforces RBAC-only authentication. Always disable local auth (connection strings, SAS keys) and use managed identity instead.

# Storage
shared_access_key_enabled = false

# Service Bus
local_auth_enabled = false

# Event Hubs
local_authentication_enabled = false

# Cosmos DB
local_authentication_disabled = true

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

Security

What our scanner noticed· Medium risk

Instructions that use the network
Downloads piped into a shell
Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

Microsoft

Publisher

Microsoft (Official)

Source

microsoft/skills · .github/plugins/azure-skills/skills/azure-prepare · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

Also distributed in

microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-prepare.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Microsoft

Azure Prepare

Triggers

Rules

❌ PLAN-FIRST WORKFLOW — MANDATORY

❌ STEP 0: Specialized Technology Check — MANDATORY FIRST ACTION

Check 1: Prompt keywords

Phase 1: Planning (BLOCKING — Complete Before Any Execution)

Phase 2: Execution (Only After Plan Approval)

Outputs

SDK Quick References

Next

Files

references/services/functions/templates/recipes/composition.md

Composition Algorithm

Azure MCP Path

Fallback Path (Azure MCP Unavailable)

Example (MCP)

Example (Fallback)

Critical Rules

IaC Merge Guidelines

UAMI Configuration (CRITICAL)

Language-Specific Entry Points

Node.js (JavaScript/TypeScript)

C# (.NET)

Deployment Strategy

Terraform-Specific Requirements

Runtime Versions

Flex Consumption (FC1) Requires azapi

RBAC Propagation Delay

Required: azd-service-name Tag

Disabled Local Auth (Policy Required)

Requirements and compatibility

Security

Attribution and licence

Related skills

Modal

Cloud Infrastructure Network Engineer

Deployment Validation Cloud Architect

Airflow Dag Patterns

Cost Optimization

Hybrid Cloud Networking

Download ZIP