Book Image

Cloud Native Architectures

By : Tom Laszewski, Kamal Arora, Erik Farr, Piyum Zonooz
Book Image

Cloud Native Architectures

By: Tom Laszewski, Kamal Arora, Erik Farr, Piyum Zonooz

Overview of this book

Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. To harness this, businesses need to refresh their development models and architectures when they find they don’t port to the cloud. Cloud Native Architectures demonstrates three essential components of deploying modern cloud native architectures: organizational transformation, deployment modernization, and cloud native architecture patterns. This book starts with a quick introduction to cloud native architectures that are used as a base to define and explain what cloud native architecture is and is not. You will learn what a cloud adoption framework looks like and develop cloud native architectures using microservices and serverless computing as design principles. You’ll then explore the major pillars of cloud native design including scalability, cost optimization, security, and ways to achieve operational excellence. In the concluding chapters, you will also learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform. By the end of this book, you will have learned the techniques to adopt cloud native architectures that meet your business requirements. You will also understand the future trends and expectations of cloud providers.
Table of Contents (19 chapters)
Title Page
Packt Upsell
Foreword
Contributors
Preface
Index

Serverless implications


Serverless architectures are a unique costing challenge. Most of the effective cost optimization efforts fall in writing effective code in order to reduce the code's execution time or the number of executions required. This is evident from the pricing model of serverless code execution services such as AWS Lambda, which charges based on the number of executions, execution time, and allocated memory to the container that runs the code (https://s3.amazonaws.com/lambda-tools/pricing-calculator.html). Memory size can be optimized by tracking the amount of memory used per execution (this can be tracked in AWS CloudWatch).

Other serverless cloud services, such as AWS Kinesis and Athena, follow a similar data-based pricing model (per shard hour and payload units for Kinesis, per TB of data scanned for Athena). These services are almost always cheaper than their comparable services (such as Apache Kafka and Presto), which are hosted on self-managed compute nodes.