Microservice Architectures
Master comprehensive principles and design patterns for building scalable distributed systems using microservices architecture and implementation.
Master comprehensive principles and design patterns for building scalable distributed systems using microservices architecture and implementation.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Scalable Microservices for Developers Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.4
(14 ratings)
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What you'll learn
Master core concepts of microservices architecture
Understand program slicing and its application
Learn deployment and scaling strategies
Implement service decoupling and resilience patterns
Design scalable distributed systems
Develop client-side load balancing solutions
Skills you'll gain
This course includes:
3.5 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This comprehensive course explores the fundamentals of microservice architectures, from theoretical concepts to practical implementation. Students learn about program slicing, architectural patterns, and the transition from monolithic to microservice-based systems. The curriculum covers essential topics including service decoupling, deployment strategies, scalability considerations, and resilience patterns. Through practical examples, students understand how to design and implement robust distributed systems using microservices architecture.
Microservices I & Program Slicing
Module 1 · 1 Hours to complete
The Pros and Cons of Microservices
Module 2 · 1 Hours to complete
Microservices Architectural Patterns
Module 3 · 4 Hours to complete
Fee Structure
Instructors
Professor of Computer Science and Associate Chair of the Computer Science and Engineering Program
Douglas C. Schmidt is a Professor of Computer Science and Associate Chair of the Computer Science and Engineering program at Vanderbilt University. A Senior Researcher at the Institute for Software Integrated Systems, he has also served as Chief Technology Officer at Carnegie Mellon's Software Engineering Institute. Dr. Schmidt has authored 10 books and over 500 papers on software patterns, optimization, and real-time middleware. He has led the development of ACE, TAO, and CIAO, widely-used middleware frameworks applied in defense, telecom, financial services, healthcare, and gaming industries.
Professor of Computer Science at Vanderbilt University
Dr. Jules White is a Professor of Computer Science at Vanderbilt University, where he also serves as the Director of the Initiative on the Future of Learning & Generative AI and the Associate Dean of Strategic Learning Programs in the School of Engineering. He is recognized for creating one of the first online courses in Prompt Engineering, which focuses on effective communication with AI systems. A recipient of the National Science Foundation CAREER Award, Dr. White has published over 160 papers and has received multiple Best Paper Awards for his research. His work primarily explores large language models, including ChatGPT, as well as topics in cybersecurity and software engineering across various sectors such as healthcare and manufacturing. He leads the Mobile Application Computing, Optimization, and Security Methods (MAGNUM) Group at Vanderbilt University, where he conducts his research and development efforts.
Testimonials
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4.4 course rating
14 ratings
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