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Book Overview & Buying
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Table Of Contents
Machine Learning in Microservices
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In this chapter, we covered the concepts of MSA and how MSA is different from traditional monolithic architecture. By now, you should also have a clear understanding of the advantages of MSA and the challenges organizations may experience when adopting MSA.
We also covered the key concept of methodologies to consider when designing MSA, such as ACID, the saga pattern, and CQRS. All these concepts are essential to help overcome synchronization challenges and to maintain microservices anonymity.
We now understand the basics of DevOps and why it is important in MSA design, deployment, and operations, as well as how ML integration in MSA enterprise systems can help enhance system operations.
In the next chapter, we will go over common methodologies that organizations pursue to transition from running traditional monolithic systems to MSA systems. We will discuss how to break down the existing system into services that form the new MSA enterprise system.
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