Google Cloud Run

Overview Modern software development requires a pragmatic approach to choosing tools. Rather than sticking to a single language, high-performing teams select technologies based on specific needs—using Python for logic-heavy automations and TypeScript for interactive user interfaces. This guide explores a production-ready architecture involving Astro for static content, Next.js for dynamic portals, and Google Cloud Run for serverless execution. This stack prioritizes speed, minimal maintenance, and clean separation of concerns. Prerequisites To implement this architecture, you need a solid grasp of **REST APIs** and **Git-based workflows**. Familiarity with Python and TypeScript is essential, alongside a basic understanding of containerization via Docker and CI/CD concepts using GitHub Actions. Key Libraries & Tools * Astro: A static site generator that optimizes performance by shipping minimal JavaScript. * Next.js: A React framework providing full-stack capabilities with built-in API routing. * MongoDB: A NoSQL database used for flexible data modeling during rapid development phases. * Cloudflare Pages: A hosting platform for frontend assets with integrated DNS management. * Stripe SDK: Tools for handling global payments, tax, and invoicing. Code Walkthrough: Automating Dynamic Content on Static Sites Static sites offer incredible speed but struggle with real-time data like "latest video" feeds. We solve this by using Python to update Cloudflare page rules instead of rebuilding the entire site. ```python import googleapiclient.discovery import requests def update_latest_content(channel_id, cloudflare_token): # Initialize YouTube Client youtube = googleapiclient.discovery.build("youtube", "v3", developerKey="SECRET") # Fetch most recent video ID request = youtube.search().list(channelId=channel_id, part="id", order="date", maxResults=1) video_id = request.execute()['items'][0]['id']['videoId'] # Update Cloudflare Page Rule via REST API url = "https://api.cloudflare.com/client/v4/zones/ZONE_ID/pagerules/RULE_ID" headers = {"Authorization": f"Bearer {cloudflare_token}"} data = {"actions": [{"id": "forwarding_url", "value": {"url": f"https://youtu.be/{video_id}", "status_code": 302}}]} requests.put(url, headers=headers, json=data) ``` This script runs on a weekly schedule. It retrieves the newest content ID and pushes that value to a Cloudflare redirect. The static website simply links to a permanent subdomain (e.g., `latest.example.com`), which always points to the correct destination without a site redeploy. Syntax Notes: The Power of Type Annotation in SDKs When building custom SDKs like Money Snake, using Python type annotations improves developer experience. By defining classes for entities like `Contact` or `Invoice`, you turn raw JSON responses into predictable objects. This allows for IDE autocomplete and catches errors before the code ever reaches production. Practical Examples 1. **Accounting Pipelines**: Connecting Stripe webhooks to Moneybird to automate invoice booking. 2. **Enterprise Portals**: Using Next.js and MongoDB to manage bulk software licenses for corporate teams. 3. **CI/CD Automation**: Utilizing GitHub Actions to build Docker images and deploy them automatically to Google Cloud Run upon every main branch push. Tips & Gotchas Avoid over-engineering your database early. While MongoDB provides flexibility, it lacks the strict relational integrity of SQL. If your project requires complex data relationships, consider PostgreSQL instead. For deployments, always use **environment variables** for secrets like API tokens; never hardcode them in your repository.