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Solutions Architect's Handbook

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
4.4 (96)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.4 (96)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Becoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This handbook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish. This new edition features additional chapters on disruptive technologies, such as Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud. The Solutions Architect's Handbook provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design. By the end of this handbook, you'll have learned the techniques needed to create efficient architecture designs that meet your business requirements.
Table of Contents (22 chapters)
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20
Other Books You May Enjoy
21
Index

Summary

In this chapter, you learned about the big data architecture and components for a 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 central to 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 appropriate technology choices associated with each. You learned about data lake architecture and its benefits.

Once you collect and store data, you need to transform it to get insights into that data and visualize your business requirements. You learned about data processing architecture and technology choices to choose open source and cloud-based data processing...

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