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 lakes

A data lake is a centralized repository for both structured and unstructured data. The data lake is becoming a popular way to store and analyze large volumes of data in a centralized repository. It stores data as is, using open source file formats to enable direct analytics. As data can be stored as is in its current format, you don't need to convert data into a predefined schema, which increases the speed of data ingestion. As illustrated in the following diagram, the data lake is a single source of truth for all data in your organization:

Object store for data lake

The following are the benefits of a data lake:

  • Data ingestion from various sources: Data lakes let you store and analyze data from various sources such as relational and non-relational databases, and streams in one centralized location for a single source of truth. This answers questions such as why is the data distributed in many locations? and where is the single source of truth?
  • Collecting and efficiently...