This course is designed for intermediate-level software developers, cloud engineers, and system architects responsible for building and scaling LLM applications. As AI systems become more complex, a resilient and scalable architecture is no longer a luxury—it's a necessity. This course provides a focused, practical guide to designing robust, cloud-native microservices that can withstand failure and scale on demand.

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Recommended experience
What you'll learn
Design and implement scalable, resilient microservice architectures for LLM apps using the 12-factor app methodology for fault tolerance in the cloud
Skills you'll gain
- Service Management
- Software Architecture
- Microservices
- Cloud-Native Computing
- LLM Application
- Cloud Deployment
- Application Deployment
- Dependency Analysis
- Maintainability
- Systems Architecture
- Service Recovery
- Cloud Computing Architecture
- Failure Analysis
- Site Reliability Engineering
- Configuration Management
- Solution Architecture
- Scalability
- Software Development
- Data Storage Technologies
- Reliability
Details to know

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January 2026
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There is 1 module in this course
This module provides a comprehensive guide to designing, evaluating, and documenting scalable and fault-tolerant microservices for LLM applications. You will be immediately immersed in a design review to understand the importance of resilience. You will then learn the core principles of the 12-Factor App methodology and multi-region deployment strategies, understand their application in practice, and use that knowledge to begin documenting a new inference service and assessing architectural risks.
What's included
1 video1 reading3 assignments
Instructor

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