Mastering Python Microservices: Build and Scale Applications
Mastering Python Microservices: Build and Scale Applications, available at $54.99, with 64 lectures, 3 quizzes, and has 4 subscribers.
You will learn about Comprehensive Understanding of Microservices Architecture Hands-On Experience with Python Frameworks Advanced Microservices Techniques Security and Performance Optimization Real-World Case Studies and Deployment Strategies This course is ideal for individuals who are Aspiring Software Developers or Experienced Developers Transitioning to Microservices or DevOps Engineers and System Administrators or Technical Leads and Architects or Anyone Interested in Modern Software Architecture It is particularly useful for Aspiring Software Developers or Experienced Developers Transitioning to Microservices or DevOps Engineers and System Administrators or Technical Leads and Architects or Anyone Interested in Modern Software Architecture.
Enroll now: Mastering Python Microservices: Build and Scale Applications
Summary
Title: Mastering Python Microservices: Build and Scale Applications
Price: $54.99
Number of Lectures: 64
Number of Quizzes: 3
Number of Published Lectures: 64
Number of Published Quizzes: 3
Number of Curriculum Items: 67
Number of Published Curriculum Objects: 67
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- Comprehensive Understanding of Microservices Architecture
- Hands-On Experience with Python Frameworks
- Advanced Microservices Techniques
- Security and Performance Optimization
- Real-World Case Studies and Deployment Strategies
Who Should Attend
- Aspiring Software Developers
- Experienced Developers Transitioning to Microservices
- DevOps Engineers and System Administrators
- Technical Leads and Architects
- Anyone Interested in Modern Software Architecture
Target Audiences
- Aspiring Software Developers
- Experienced Developers Transitioning to Microservices
- DevOps Engineers and System Administrators
- Technical Leads and Architects
- Anyone Interested in Modern Software Architecture
This comprehensive course is designed for developers and software engineers who are eager to dive into the world of microservices, particularly leveraging Python to build scalable, maintainable, and efficient microservice-based applications. Microservices architecture has become the backbone of modern software development, enabling organizations to create complex, distributed systems that can be developed, deployed, and scaled independently. This course will guide you through the entire lifecycle of microservices development, from understanding the fundamental concepts to implementing advanced techniques and best practices.
Course Overview and Objectives
The course begins with a detailed overview of its structure and objectives, setting clear expectations for what you will achieve by the end of the journey. You will gain a deep understanding of microservices architecture and how it differs from the traditional monolithic approach. This section will also introduce you to the benefits and challenges associated with microservices, providing insights into why organizations are increasingly adopting this architecture despite the complexities it introduces.
Introduction to Microservices
You will start with the basics of microservices, understanding their architecture and how they compare to monolithic systems. This section will highlight the flexibility and scalability that microservices offer, as well as the challenges such as managing distributed systems and ensuring consistent communication between services. You’ll learn how microservices allow for independent development, deployment, and scaling of different parts of an application, making them ideal for large and complex projects.
Benefits and Challenges of Microservices
Microservices come with numerous advantages, including improved scalability, faster development cycles, and greater resilience. However, they also introduce new challenges, such as the need for robust inter-service communication and the complexity of managing multiple services. This section will explore these benefits and challenges in detail, providing you with strategies to address common issues and maximize the advantages of a microservices architecture.
Introduction to Python for Microservices
Python is a powerful and versatile language, making it an excellent choice for developing microservices. In this section, you will learn why Python is well-suited for microservices, with a focus on its simplicity, readability, and the vast ecosystem of frameworks and libraries available. You will get an overview of popular Python frameworks such as Flask, FastAPI, and Django, each of which offers unique advantages for building microservices.
Setting Up the Environment
Before diving into microservices development, itβs crucial to set up a robust development environment. This section will guide you through the installation of Python, pip, and virtual environments, ensuring that your setup is optimal for microservices development. Additionally, you will learn how to set up an Integrated Development Environment (IDE) like VSCode or PyCharm, tailored for Python development.
Introduction to Docker and Kubernetes
As microservices are often deployed in containerized environments, you’ll be introduced to Docker and Kubernetes. Docker allows you to create and manage containers, ensuring that your microservices run consistently across different environments. Kubernetes, on the other hand, provides powerful orchestration capabilities, enabling you to manage and scale your microservices efficiently. You will learn the basics of both tools, including setting up a local Kubernetes environment using Minikube.
Building Microservices with Flask and FastAPI
The course will delve into building microservices using Flask and FastAPI, two popular Python frameworks. You will start by creating simple microservices, learning about basic setup, routing, and creating RESTful APIs. Flask Blueprints will be introduced to help you organize code into modular components, making your applications more maintainable and scalable. With FastAPI, you’ll explore advanced features like dependency injection and data validation with Pydantic, a powerful tool for ensuring data integrity.
Inter-Service Communication
Effective communication between microservices is crucial for the success of a distributed system. This section will cover various methods for inter-service communication, including HTTP communication using Python’s requests library, and more advanced techniques like gRPC and message queues. You will learn how to set up and use gRPC for efficient and scalable communication, as well as how to implement asynchronous communication with message queues like RabbitMQ and Kafka.
Database Integration
Microservices often require interaction with databases, whether SQL or NoSQL. This section will guide you through the process of choosing the right database for your microservice, integrating SQL databases using SQLAlchemy, and working with NoSQL databases like MongoDB. You will learn how to perform CRUD operations, design schemas, and manage database migrations, ensuring that your microservices are data-driven and efficient.
Service Discovery and Configuration
As the number of microservices grows, service discovery and configuration management become critical. You will learn about service discovery tools like Consul and Eureka, which help in dynamically locating services in a distributed environment. Configuration management will also be covered, with a focus on managing configuration through environment variables and tools like ConfigMap and Vault.
Authentication, Authorization, and Security Best Practices
Security is paramount in microservices architecture. This section will teach you how to implement robust authentication and authorization mechanisms, including JWT and OAuth2, as well as Role-Based Access Control (RBAC) to manage user permissions. You will also learn about security best practices, common threats, and how to mitigate them, ensuring that your microservices are secure from potential vulnerabilities.
API Gateway, Load Balancing
To manage traffic and improve the performance of your microservices, you will learn how to set up an API Gateway using tools like Nginx or Kong, and implement load balancing strategies.
Advanced Topics and Performance Optimization
As you progress, the course will introduce advanced topics such as event-driven microservices, CQRS, and event sourcing, as well as serverless microservices using AWS Lambda. Performance optimization techniques will also be covered, including profiling Python applications, optimizing resource usage, and implementing caching strategies with Redis.
Documentation, Versioning, and Case Studies
Documenting your microservices is crucial for maintainability and collaboration. You will learn how to use OpenAPI/Swagger to generate API documentation, and explore strategies for API versioning. The course will also present real-world case studies, providing insights into successful microservices implementations and lessons learned from industry leaders.
Maintaining, Scaling, and Troubleshooting Microservices
Finally, the course will cover strategies for maintaining and scaling microservices, including handling breaking changes and implementing autoscaling with Kubernetes. You will also learn troubleshooting techniques to identify and resolve common issues in microservices architecture, ensuring that your applications remain robust and scalable over time.
By the end of this course, you will have a thorough understanding of microservices architecture and the skills needed to build, deploy, and maintain Python-based microservices in a production environment. Whether you’re a seasoned developer looking to expand your knowledge or a newcomer to microservices, this course will equip you with the tools and techniques to succeed in the world of distributed systems.
Course Curriculum
Chapter 1: Introduction and Fundamentals
Lecture 1: Understanding Microservices architecture
Lecture 2: Benefits and challenges of microservices
Lecture 3: Building Microservices with Python
Chapter 2: Setting Up the Environment
Lecture 1: Installing python, pip and virtual environments
Lecture 2: Setting up an IDE (VSCODE, PYCHARM)
Lecture 3: Basics of Docker and Containerization
Lecture 4: Basics of Kubernetes for container orchestration
Chapter 3: Building Microservices with Flask
Lecture 1: Basic Setup and Routing
Lecture 2: Creating a simple restful API
Lecture 3: Handling Requests and response
Lecture 4: Blueprints for modular applications
Chapter 4: Building Microservices with FastAPI
Lecture 1: Basic Setup and Routing in FASTAPI
Lecture 2: Restful APIS with FASTAPI
Lecture 3: Dependency injection
Lecture 4: Data Validation with pydantic
Chapter 5: Inter-Service Communication
Lecture 1: HTTP Communication between microservices
Lecture 2: GRPC and Setting up GRPC in Python
Lecture 3: Advanced Features of GRPC
Lecture 4: Introduction to Message queues in python RabbitMQ and Kafka
Lecture 5: Implementing asynchronous communication
Chapter 6: Database Integration
Lecture 1: Overview of SQL and NoSql Databases
Lecture 2: Selecting a database for your Microservices
Lecture 3: SQLalchemy using flask and fastapi
Lecture 4: MongoDB with Flask
Lecture 5: MongoDB with FastAPI
Lecture 6: Introduction to Graphql
Chapter 7: Service Discovery and Configuration
Lecture 1: Service discovery in microservices
Lecture 2: Service Discovery with consul/eureka
Lecture 3: Configuration Management
Chapter 8: Authentication and Authorization
Lecture 1: Flask Basic Authentication methods(JWT)
Lecture 2: Flask Basic Authentication methods OAUTH2
Lecture 3: RBAC in Microservices JWT
Lecture 4: Managing Roles and permissions JWT
Lecture 5: Advanced security measures JWT
Lecture 6: Implementing RBAC in Microservices with oauth2
Lecture 7: Managing Roles and permissions in OAUTH2
Lecture 8: Step by Step guide for testing RBAC Implementation
Chapter 9: API Gateway and Load Balancing
Lecture 1: Purpose and Benefits of an API Gateway
Lecture 2: Setting up an API Gateway with nginx/kong on Linux
Lecture 3: Setting up an API Gateway with nginx kong on windows
Lecture 4: Overview of Load Balancing Techniques
Lecture 5: Implementing Load Balancing
Chapter 10: Logging and Monitoring
Lecture 1: Best Practices for Logging
Lecture 2: Best Practices for Logging(Continue)
Lecture 3: Monitoring Python Microservices
Chapter 11: Testing Microservices
Lecture 1: Writing Unit Test with Pytest/UnitTest
Lecture 2: Mocking and Test Isolation
Lecture 3: Writing Integration Test and Testing Inter service communication
Lecture 4: Setting up end-to-end testing framework with selenium
Lecture 5: Inter-service communication Testing
Lecture 6: End to end testing with cypress
Lecture 7: Selenium vs Cypress
Chapter 12: Security Best Practices
Lecture 1: Securing Microservices
Lecture 2: Setting up HTTPS and Managing SSL/TLS Certificates
Chapter 13: Advanced Topics
Lecture 1: Event Driven Architecture
Lecture 2: Monitoring and Scaling with Kafka
Lecture 3: Understanding and Implementing CQRS and Event Sourcing
Chapter 14: Performance Optimization
Lecture 1: Profiling Python Applications
Lecture 2: Introduction to Caching
Lecture 3: Caching with Redis
Chapter 15: Documentation and Versioning
Lecture 1: OpenAPI Swagger and Generating API Documentation
Lecture 2: API Versioning and Implementing Versioning
Lecture 3: Strategies for maintaining and Evolving Microservices
Chapter 16: Resilience and Fault Tolerance
Lecture 1: Understanding the Circuit Breaker Pattern
Instructors
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Paul Carlo Tordecilla
Full Stack Developer | Tech Educator
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