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Solutions Architect's Handbook

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
4.2 (20)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.2 (20)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Becoming a solutions architect gives you the flexibility to work with cutting-edge technologies and define product strategies. This handbook takes you through the essential concepts, design principles and patterns, architectural considerations, and all the latest technology that you need to know to become a successful solutions architect. This book starts with a quick introduction to the fundamentals of solution architecture design principles and attributes that will assist you in understanding how solution architecture benefits software projects across enterprises. You'll learn what a cloud migration and application modernization framework looks like, and will use microservices, event-driven, cache-based, and serverless patterns to design robust architectures. You'll then explore the main pillars of architecture design, including performance, scalability, cost optimization, security, operational excellence, and DevOps. Additionally, you'll also learn advanced concepts relating to big data, machine learning, and the Internet of Things (IoT). Finally, you'll get to grips with the documentation of architecture design and the soft skills that are necessary to become a better solutions architect. By the end of this book, you'll have learned techniques to create an efficient architecture design that meets your business requirements.
Table of Contents (18 chapters)
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Summary

In this chapter, you learned about big data architecture and components for big data pipeline design. You learned about data ingestion and various technology choices available to collect batch and stream data for processing. As the cloud is taking a central place in storing the vast amounts of data being produced today, you learned about the various services available to ingest data in the AWS cloud ecosystem.

Data storage is one of the central points when it comes to handling big data. You learned about various kinds of data stores, including structured and unstructured data, NoSQL, and data warehousing, with the relevant technology choices associated with each. You learned about data lake architecture and its benefits.

Once you collect and store data, you need to perform data transformation to get insight into that data and visualize your business requirements. You learned about data processing architecture along with technology choices to choose open source and cloud-based...

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