Book Image

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
Book Image

Solutions Architect's Handbook

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)

Data ingestion

Data ingestion is the act of collecting data for transfer and storage. There are lots of places that data can come from. Predominantly, data ingestion falls into one of the categories from databases, streams, logs, and files. Among these, databases are the most predominant. These typically consist of your main upstream transactional systems that are the primary data storage for your applications. They take on both relational and non-relational flavors, and there are several techniques for extracting data out of them.

Streams are open-ended sequences of time-series data such as clickstream data from websites or IoT devices, usually published into an API that we host. Logs get generated by applications, services, and operating systems. A data lake is a great place to store all of the data for centralized analysis. Files come from self-hosted filesystems or via third-party data feeds via FTP or APIs. As shown in the following diagram, use the type of data your environment...