Python 5 Course: Relational Databases into the Cloud

COURSE DESCRIPTION

Learn how to design, deploy, and interact with relational databases hosted on cloud platforms using Python. This course covers cloud database concepts, Python integration, security, performance, and automation, enabling you to build scalable cloud-based data applications.

LEARNING OBJECTIVES

What's covered in this course:

1. Introduction to Cloud Relational Databases

• 1.1 Understand the basics of cloud computing and its importance
• 1.2 Overview of major cloud database services: AWS RDS, Google Cloud SQL, Azure SQL Database
• 1.3 Learn advantages of cloud databases compared to traditional on-premises setups
• 1.4 Refresh core database concepts: relational model, tables, keys, and normalization
• 1.5 Introduction to SQL tailored for cloud database environments

2. Setting Up Cloud Database Instances

• 2.1 Create and configure cloud relational database instances on selected cloud providers
• 2.2 Understand database engines available on the cloud: MySQL, PostgreSQL, SQL Server
• 2.3 Connect to cloud databases remotely with secure methods
• 2.4 Learn about database endpoints, ports, and credential management
• 2.5 Hands-on: Launch a cloud database instance and connect using CLI or cloud dashboards

3. Python Integration with Cloud Databases

• 3.1 Explore Python libraries for relational databases: psycopg2, PyMySQL, SQLAlchemy ORM
• 3.2 Connect Python applications securely to cloud-hosted databases
• 3.3 Execute SQL queries and manage transactions via Python
• 3.4 Handle connection pooling and error management in Python scripts
• 3.5 Hands-on: Write Python scripts to read and write data to cloud databases

4. Database Security and Access Management

• 4.1 Manage users, roles, and permissions within cloud databases
• 4.2 Secure database connections using SSL/TLS protocols
• 4.3 Use environment variables and secret managers in Python applications
• 4.4 Apply best security practices for cloud databases
• 4.5 Hands-on: Configure secure connections and test access control settings

5. Performance Optimization and Monitoring

• 5.1 Understand indexing, query optimization, and caching fundamentals
• 5.2 Monitor cloud database performance via provider dashboards
• 5.3 Setup automated backups and plan for disaster recovery
• 5.4 Learn scaling strategies: vertical and horizontal scaling in cloud databases
• 5.5 Hands-on: Analyze query performance and configure automated backups

6. Automation and Scripting with Python

• 6.1 Automate routine database maintenance tasks with Python scripts
• 6.2 Use Python to manage database schema changes and migrations
• 6.3 Integrate cloud SDKs (AWS boto3, Google Cloud libraries) for database operations
• 6.4 Schedule Python scripts using cron jobs or cloud-based function triggers
• 6.5 Hands-on: Develop Python automation scripts for common cloud database tasks

7. Project: Build a Cloud-Based Data Application

• 7.1 Define and plan an application to store, query, and update data in a cloud database
• 7.2 Develop backend logic using Python interacting with the cloud database
• 7.3 Deploy and test the application with cloud database integration
• 7.4 Optional: Implement a simple UI or REST API layer using Flask or FastAPI
• 7.5 Final review, debugging, and troubleshooting

8. Accessing Cloud Databases via Web Applications

• 8.1 Understand why direct client access to cloud databases is discouraged and learn the security implications.
• 8.2 Explore the role and architecture of backend API servers as secure gateways to cloud databases
• 8.3 Build a simple Python backend API using Flask to interact with a cloud database
• 8.4 Implement security best practices for the backend API, including Authentication, HTTPS, and input validation
• 8.5 Deploy the backend API with secure connectivity to a cloud database using tools like Cloud SQL Auth Proxy
• 8.6 Integrate client applications to consume backend API endpoints securely and efficiently
• 8.7 Apply best practices for API security, credential management, and scalable deployment

9. Advanced API Topics for Cloud Database Access

• 9.1 Understand the importance of user authentication and role-based access control (RBAC) for securing APIs
• 9.2 Implement JWT-based authentication in a Python backend API using Flask
• 9.3 Apply pagination, filtering, and sorting techniques to API endpoints for efficient data handling
• 9.4 Explore asynchronous API development using FastAPI and async database connections
• 9.5 Learn caching strategies to improve API response performance and reduce database load
• 9.6 Understand API versioning approaches and how to document APIs effectively using Swagger/OpenAPI
• 9.7 Implement consistent error handling and logging mechanisms for robust API operation
• 9.8 Develop a comprehensive secure and scalable API by integrating authentication, pagination, versioning, caching, and documentation

10. Complete Database Cloud App

• 10.1 Provisioning a Google Cloud SQL instance (PostgreSQL)
• 10.2 Designing and creating relational tables with proper schema and constraints
• 10.3 Implementing backend CRUD operations in Python with Flask
• 10.4 Securing the API with authentication and environment variables
• 10.5 Deploying the backend using Google Cloud Run with secure database connectivity
• 10.6 Testing and validating your solution end to end

11. Cybersecurity & Python Programming

• 11.1 Introduction to Cybersecurity
• 11.2 How Cybersecurity Relates to Python
• 11.3 Common Cybersecurity Threats
• 11.4 Python and Data Protection
• 11.5 Python in Penetration Testing
• 11.6 Best Practices for Secure Python Programming

Additional Resources and Next Steps

• Recommended reading and official documentation for cloud databases and Python libraries
• Explore other cloud data services such as NoSQL databases and data warehouses
• Learn about career paths in cloud database administration and cloud development

AUDIENCE

This course is designed for Python programmers who have completed Python Level 1 and Level 2 courses or have equivalent experience, and who want to advance their skills in designing, deploying, and managing relational databases on cloud platforms using Python.

PREREQUISITES

Completion of Python 1 - Fundamentals, Python 2 - Data Science, OOP, and UI