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)

Predictive scaling

Predictive scaling is the best-case approach that any organization wants to take. Often, you can collect historical data of application workload. For example, an e-commerce website such as Amazon may have a sudden traffic spike, and you need predictive scaling to avoid any latency issues. Traffic patterns may include the following:

  • Weekends have three times more traffic than a weekday.
  • Daytime has five times more traffic than at night.
  • Shopping seasons, such as Thanksgiving or Boxing Day, have 20 times more traffic than regular days.
  • Overall, the holiday season in November and December has 8 to 10 times more traffic than during other months.

You may have collected the previous data based on monitoring tools that are in place to intercept the user's traffic, and based on this, you can make a prediction for scaling. Scaling may include planning to add more servers when workload increases, or to add additional caching. This example of an e-commerce workload is one...