Free Download Modern C# Microservices with Docker, K8s & AIPublished 2/2026
Created by Eitan Mizrahi
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert |
Genre: eLearning |
Language: English |
Duration: 146 Lectures ( 3h 14m ) |
Size: 1.11 GB
✓ Build production-grade microservices in C# with clean architecture principles.
✓ Containerize and orchestrate services using Docker and Kubernetes.
✓ Deploy distributed systems to Azure using modern cloud-native workflows.
✓ Integrate Large Language Models (LLMs) into microservices for intelligent behaviors.
✓ Use RabbitMQ to implement asynchronous communication patterns.
✓ Implement observability: logging, metrics, dashboards, and distributed tracing.
✓ Design secure microservices using JWT, secret management, and cloud firewall rules.
✓ Optimize AI-service performance using caching, batching, and rate limiting.
✓ Build CI/CD pipelines to automate deployments and deliver software faster.
Requirements● Basic understanding of programming (C# experience is helpful but not required).
● A Windows, macOS, or Linux machine capable of running Docker.
● Willingness to learn modern cloud-native development practices.
DescriptionThis course is a complete, practical, and modern journey into building intelligent microservices using C# and the .NET platform. You will design and implement a real distributed system composed of multiple services that communicate with each other, process data, and scale in a cloud-ready environment.
Rather than focusing on theory alone, the course takes a hands-on approach. You will build each part of the system step by step, including request handling, service boundaries, data storage, background processing, and intelligent processing components. Every concept is demonstrated through working code and real architectural decisions.
You will learn how to containerize applications, manage multiple services, and orchestrate them in a production-style environment. The course also covers service communication patterns, asynchronous processing, reliability considerations, and system observability so you understand how modern backend systems are designed and maintained.
Intelligent capabilities are introduced as part of the system architecture, showing how backend services can interact with language-based AI models in a controlled and maintainable way. The focus is on engineering practices, not experimentation, so you learn how to integrate intelligent features responsibly into backend systems.
This course is designed for developers with prior experience in C# or backend development who want to move into modern distributed and cloud-oriented architectures. By the end of the course, you will have built a complete multi-service system and gained practical skills that apply directly to real-world software projects.
Who this course is for■ Developers who want to transition into cloud-native microservices architecture.
■ C# engineers who want hands-on experience with Docker, Kubernetes, and AI integration.
■ Backend developers looking to add AI/LLM capabilities to real-world systems.
■ Students preparing for interviews or backend/cloud developer roles.
■ Engineers aiming to build scalable, production-ready distributed applications.
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