Book Image

Architecting Cloud Native Applications

By : Kamal Arora, Erik Farr, John Gilbert, Piyum Zonooz
Book Image

Architecting Cloud Native Applications

By: Kamal Arora, Erik Farr, John Gilbert, 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. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: • Cloud Native Development Patterns and Best Practices by John Gilbert • Cloud Native Architectures by Erik Farr et al.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
About Packt
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.