Book Image

Solutions Architect’s Handbook - Second Edition

By : Saurabh Shrivastava, Neelanjali Srivastav
4 (2)
Book Image

Solutions Architect’s Handbook - Second Edition

4 (2)
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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Index

Technology selection for performance optimization

In Chapter 6, Solution Architecture Design Patterns, you learned about various design patterns, including microservice, event-driven, cached-based, and stateless. An organization may choose a combination of these design patterns depending on their solution's design needs. You can have multiple approaches to architecture design depending on your workload. Once you finalize your strategy and start solution implementation, the next step is to optimize your application. To optimize your application, you need to collect data by performing load testing and defining benchmarking as per your application's performance requirements.

Performance optimization is a continuous improvement process, one in which you need to take cognizance of optimal resource utilization from the beginning of solution design to after the application's launch. You need to choose the right resources as per the workload or tweak the application and...