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 migration

Cloud data migration refers to the process of moving existing data to a new cloud storage location. Most applications will require data storage throughout their progression into the cloud. Storage migration typically aligns with one of two approaches, but organizations may perform both at the same time:

  • First, a single lift-and-shift move. This may be required before new applications can be started up in the cloud.
  • Second, a hybrid model weighted toward the cloud, which results in newly architected cloud-native projects with some legacy on-premises data. The legacy data stores may shift toward the cloud over time.

However, your approach to migrating data will vary. It depends on factors such as the amount of data, network and bandwidth constraints, the data classification tier such as backup data, mission-critical data, data warehouses, or archive data, and the amount of time you can allocate for the migration process.

If you have extensive archives of data or data lakes...