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via Udemy |
Go to Course: https://www.udemy.com/course/implementing-serverless-microservices-architecture-patterns/
Certainly! Here's a detailed review and recommendation of the Coursera course on building microservices with serverless computing: --- **Course Review: Building Microservices with Serverless Computing on Coursera** This course offers an insightful exploration into transforming traditional microservice architectures by leveraging the power of serverless computing. Taught by Richard T. Freeman, a highly experienced cloud architect and data scientist, the course provides a comprehensive guide to implementing microservices efficiently, cost-effectively, and with greater agility. **Course Content and Structure** The course begins by establishing a solid foundation in microservice patterns, particularly those associated with containerization. It then transitions into demonstrating how serverless computing can replicate and enhance these patterns—covering critical topics such as non-relational and relational databases, event sourcing, command-query responsibility segregation (CQRS), messaging, API composition, monitoring, observability, and CI/CD pipelines. One of the course’s strengths lies in its pragmatic approach. It doesn't just theorize the advantages of serverless architectures but shows you step-by-step how to implement these patterns practically, enabling you to build, test, deploy, scale, and monitor microservices seamlessly. The inclusion of real-world use cases and best practices adds immense value. **Instructor Expertise** Richard Freeman's rich background in cloud solutions, machine learning, and enterprise architecture shines through. His experience working with Fortune 500 companies, nonprofit organizations, and his active involvement in industry events bring credibility and practical insights. His AWS certification and hands-on experience ensure that learners receive guidance rooted in real-world applicability. **Who Should Enroll?** This course is ideal for software engineers, cloud architects, DevOps professionals, and technical leads interested in modernizing their microservice architectures or exploring serverless options. It’s particularly beneficial if you're already familiar with container-based microservices but want to understand how serverless can streamline development and reduce operational overhead. **Pros and Cons** *Pros:* - Comprehensive coverage of microservice patterns implemented through serverless. - Clear explanations of complex concepts, making advanced topics accessible. - Practical demonstrations suitable for real-world application. - Led by an expert with extensive industry and academic experience. *Cons:* - Some concepts may require foundational knowledge of cloud computing and microservice architecture. - Implementing serverless solutions might involve significant initial learning and setup. **Final Recommendation** I highly recommend this course for professionals looking to modernize their microservice deployments. The blend of theoretical knowledge and practical guidance can significantly enhance your development team's productivity, reduce costs, and increase flexibility through serverless architectures. Whether you're transitioning from container-based deployments or starting new projects, this course provides valuable insights and actionable skills to harness the full potential of serverless computing. --- Feel free to ask if you'd like a shorter summary or specific details included!
Building a microservices platform using virtual machines or containers, involves a lot of initial and ongoing effort and there is a cost associated with having idle services running, maintenance of the boxes and a configuration complexity involved in scaling up and down. In this course, We will show you how Serverless computing can be used to implement the majority of the Microservice architecture patterns and when put in a continuous integration & continuous delivery pipeline; can dramatically increase the delivery speed, productivity and flexibility of the development team in your organization, while reducing the overall running, operational and maintenance costs. We start by introducing the microservice patterns that are typically used with containers, and show you throughout the course how these can efficiently be implemented using serverless computing. This includes the serverless patterns related to non-relational databases, relational databases, event sourcing, command query responsibility segregation (CQRS), messaging, API composition, monitoring, observability, continuous integration and continuous delivery pipelines. By the end of the course, you'll be able to build, test, deploy, scale and monitor your microservices with ease using Serverless computing in a continuous delivery pipeline. About the Author Richard T. Freeman, PhD currently works for JustGiving, a tech-for-good social platform for online giving that's helped 25 million users in 164 countries raise $5 billion for good causes. He is also offering independent and short-term freelance cloud architecture & machine learning consultancy services. Richard is a hands-on certified AWS Solutions Architect, Data & Machine Learning Engineer with proven success in delivering cloud-based big data analytics, data science, high-volume, and scalable solutions. At Capgemini, he worked on large and complex projects for Fortune Global 500 companies and has experience in extremely diverse, challenging and multi-cultural business environments. Richard has a solid background in computer science and holds a Master of Engineering (MEng) in computer systems engineering and a Doctorate (Ph.D.) in machine learning, artificial intelligence and natural language processing. See his website rfreeman for his latest blog posts and speaking engagements. He has worked in nonprofit, insurance, retail banking, recruitment, financial services, financial regulators, central government and e-commerce sectors, where he: Provided the delivery, architecture and technical consulting on client site for complex event processing, business intelligence, enterprise content management, and business process management solutions.Delivered in-house production cloud-based big data solutions for large-scale graph, machine learning, natural language processing, serverless, cloud data warehousing, ETL data pipeline, recommendation engines, and real-time streaming analytics systems.Worked closely with IBM and AWS and presented at industry events and summitsPublished research articles in numerous journals, presented at conferences and acted as a peer-reviewerHas over four years of production experience with Serverless computing on AWS