Install Python, verify the version, add Python to path, install and upgrade pip if needed, and create and activate a virtual environment to isolate dependencies.

Learn to set up two popular python development ides, vscode and pycharm, configure the python interpreter, enable linting and formatting, and create virtual environments for microservices development.

Master docker basics and containerization, including portable containers, docker images, and essential commands like docker run, docker pull, and docker build.

Learn to set up a local Kubernetes cluster with minikube and kubectl. Deploy and scale a hello world application while managing pods, services, and updates.

Install flask with pip, create a basic flask app, define routes with app.route, support dynamic url parameters, render HTML templates with render_template, and run python app.py.

Create a simple restful api with flask by setting up the project structure, defining an item resource with get, post, and delete, and storing items in memory to illustrate crud.

Learn to handle requests and structure responses in a Flask app by parsing query parameters, form data, and JSON, then send JSON replies with customizable status codes and headers.

Explore how Flask blueprints modularize a project into reusable components, define routes and error handling, and register them with the main app for scalable, maintainable code.

Master the basic setup and routing in FastAPI, including pip installation, uvicorn serving, routes with path and query parameters, pydantic models for request bodies, and automatic interactive API documentation.

Build a simple restful API with FastAPI, using SQLite with SQLAlchemy, define an item model and Pydantic schemas, implement create, read, update, delete operations, and explore Swagger docs.

Master the dependency injection pattern in FastAPI to promote loose coupling and testability, with basic and advanced examples, including mock testing and database lifecycle management.

Learn to validate and serialize data in FastAPI with Pydantic models, defining user schemas, wiring them to endpoints, and leveraging field validators and nested types.

Learn how http communication connects microservices using fast api and rest methods for interoperable json responses. Implement asynchronous httpx calls and handle errors, enabling robust, scalable microservices.

Explore gRPC in Python by defining a greeter service, generating code, and building a client and server with HTTP/2, Protobuf, and streaming support.

Explore advanced gRPC features in Python, including TLS encryption, token-based authentication via interceptors, client and server side load balancing, streaming types, robust error handling, and unary and stream interceptors.

Explore how Python-based message queues like RabbitMQ and Kafka enable asynchronous communication in microservices, covering producer-consumer patterns, routing, scalability, and real-time data processing.

Implement asynchronous communication with RabbitMQ and Kafka by configuring producers and consumers, durable queues and persistent messages, and applying pub/sub, work queue, and event sourcing patterns for scalable, fault-tolerant systems.

Compare SQL and NoSQL databases for python microservices, highlighting use cases, examples, and data models. Understand fixed vs flexible schemas, vertical vs horizontal scaling, and acid or base properties.

Assess data consistency, scalability, and performance to choose a database for your microservice, comparing relational options like Postgres or MySQL with NoSQL databases such as MongoDB or Cassandra.

Learn to integrate SQLAlchemy with Flask and FastAPI, perform CRUD operations, and manage per-request sessions in a SQLite database using Python microservices.

Learn to build Python microservices with Flask and MongoDB, perform CRUD operations, and design flexible schemas, from environment setup to running a Flask app connected to MongoDB.

Build scalable Python microservices with MongoDB using FastAPI, covering setup, crud operations, schema design, and a complete sample application.

Explore GraphQL in Python microservices, comparing it to REST, and set up a strawberry-based API. Create a simple schema with queries and mutations, test with the GraphQL playground.

Learn how service discovery in microservices with flask enables automatic service identification and communication. Compare client-side and server-side discovery using console as the service registry to register and discover services.

Explore Console and Eureka for service discovery in a microservices architecture, install and register a Flask service, and compare their dashboards, catalogs, and client-server workflows.

Explore configuration management in Flask microservices using environment variables and dot env, and learn to use configmap in Kubernetes and HashiCorp Vault for secure secrets.

Learn how to implement JWT authentication in Flask for secure, stateless microservices, using JSON Web Tokens with claims, signed tokens, and protected routes via HTTP headers.

Learn how to implement OAuth2 in Flask, set up the project structure and app factory, configure the provider, and protect routes with access tokens and common grant types.

Implement role based access control in a Flask microservice by defining admin and user roles, assigning permissions, and protecting routes with a role_required decorator.

Extend the database model to manage roles and permissions in a flask microservice, create and assign roles, update and delete permissions, and expose endpoints; test with Postman and Curl.

Implement advanced security for microservices by applying data encryption with Fernet, securing inter-service communication, enforcing security headers with Flask Talisman, and managing sensitive config via environment variables and HashiCorp Vault.

Manage roles and permissions to secure access control in your application. Add, update, and remove roles using a management interface or shell, then commit changes to the database.

Test your Python-based RBAC implementation by creating test data, roles, permissions, and users; write unit tests to verify admin and user access using OAuth2 tokens, with setup and teardown.

Discover the purpose and benefits of an api gateway in microservices architecture, including centralized api management, enhanced security, and improved performance through routing, authentication, throttling, and aggregation.

Configure nginx as a reverse-proxy API gateway for Python microservices, route 80 to 5000, then set up Kong with YAML, import config, and enable authentication, rate limiting, and logging.

Configure an API gateway for Python microservices using Nginx and Kong on Windows, including Nginx as a reverse proxy, Kong with Docker, and services, routes, and security plugins.

Explore load balancing to distribute traffic across servers in Python microservices, covering hardware, software, and cloud-based balancers, algorithms like round robin, least connections, IP hash, and nginx as reverse proxy.

Configure nginx as a reverse proxy and load balancer to distribute requests across multiple Python microservice instances on ports 5000, 5001, and 5002, using an upstream group and proxy_pass.

Learn to implement logging in Python microservices by comparing the built-in logging module and logo row, setting up a project structure, and applying best practices for monitoring and debugging.

Explore advanced logging configurations for Python microservices, including custom log formats, multiple handlers, and centralized log management with ELK stack, structured logging, and log rotation.

Learn to monitor Python microservices with Prometheus and Grafana, set up alerts, and visualize metrics in real time to ensure services run smoothly.