Book Image

AWS for Solutions Architects

By : Alberto Artasanchez
3 (1)
Book Image

AWS for Solutions Architects

3 (1)
By: Alberto Artasanchez

Overview of this book

One of the most popular cloud platforms in the world, Amazon Web Services (AWS) offers hundreds of services with thousands of features to help you build scalable cloud solutions; however, it can be overwhelming to navigate the vast number of services and decide which ones best suit your requirements. Whether you are an application architect, enterprise architect, developer, or operations engineer, this book will take you through AWS architectural patterns and guide you in selecting the most appropriate services for your projects. AWS for Solutions Architects is a comprehensive guide that covers the essential concepts that you need to know for designing well-architected AWS solutions that solve the challenges organizations face daily. You'll get to grips with AWS architectural principles and patterns by implementing best practices and recommended techniques for real-world use cases. The book will show you how to enhance operational efficiency, security, reliability, performance, and cost-effectiveness using real-world examples. By the end of this AWS book, you'll have gained a clear understanding of how to design AWS architectures using the most appropriate services to meet your organization's technological and business requirements.

Related Content you might be interested in

Current Title:

Small book image
AWS for Solutions Architects
Alberto Artasanchez
Feb, 2021 | 454 pages
Small book image
Optimizing Your Modernization Journey with AWS
Mridula Grandhi
Jul, 2023 | 418 pages
Small book image
AWS Certified Cloud Practitioner Exam Guide
Rajesh Daswani
Jan, 2022 | 630 pages
Small book image
AWS Certified SysOps Administrator ??? Associate Guide
Marko Sluga
Jan, 2019 | 584 pages
Table of Contents (20 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the color images
Get in touch
Reviews
1
Section 1: Exploring AWS
Section 1: Exploring AWS
Free Chapter
2
Chapter 1: Understanding AWS Cloud Principles and Key Characteristics
Chapter 1: Understanding AWS Cloud Principles and Key Characteristics
What is cloud computing?
Private versus public clouds
What is AWS cloud computing?
The market share, influence, and adoption of AWS
Basic cloud and AWS terminology
Why is cloud computing so popular?
The five pillars of a well-architected framework
Building credibility and getting certified
Learning tips and tricks to obtain AWS certifications
Some frequently asked questions about the AWS certifications
Summary
3
Chapter 2: Leveraging the Cloud for Digital Transformation
Chapter 2: Leveraging the Cloud for Digital Transformation
Learning about the AWS Global Infrastructure
Implementing a digital transformation program
Summary
4
Section 2: AWS Service Offerings and Use Cases
Section 2: AWS Service Offerings and Use Cases
5
Chapter 3: Storage in AWS – Choosing the Right Tool for the Job
Chapter 3: Storage in AWS – Choosing the Right Tool for the Job
Understanding Amazon Elastic Block Store
Investigating Amazon Elastic File System (EFS)
Learning about Amazon Simple Storage Service (S3)
Understanding the difference between block storage and object storage
Versioning in Amazon S3
Exploring Amazon S3 best practices
Summary
6
Chapter 4: Harnessing the Power of Cloud Computing
Chapter 4: Harnessing the Power of Cloud Computing
Brief introduction to cloud computing
Comparing PaaS, IaaS, and SaaS
Understanding IaaS
Understanding PaaS
Understanding SaaS
Selection by use case of SaaS, PaaS, or IaaS
Learning about Amazon EC2
Amazon Machine Images
Reviewing Amazon EC2 best practices
Learning about Amazon storage services
Summary
7
Chapter 5: Selecting the Right Database Service
Chapter 5: Selecting the Right Database Service
A brief history of databases
Different methods to classify databases
Introducing different types of databases
Choosing the right tool for the job
Summary
8
Chapter 6: Amazon Athena – Combining the Simplicity of Files with the Power of SQL
Chapter 6: Amazon Athena – Combining the Simplicity of Files with the Power of SQL
Introduction to Amazon Athena
Deep diving into Amazon Athena
Understanding how Amazon Athena works
Using Amazon Athena Federated Query
Learning about Amazon Athena workgroups
Reviewing Amazon Athena's APIs
Optimizing Amazon Athena
Summary
9
Chapter 7: AWS Glue – Extracting, Transforming, and Loading Data the Simple Way
Chapter 7: AWS Glue – Extracting, Transforming, and Loading Data the Simple Way
Why is AWS Glue a cornerstone service?
Introduction to AWS Glue
AWS Glue serverless streaming ETL
Putting it all together
AWS Glue best practices
Summary
10
Chapter 8: Best Practices for Application Security, Identity, and Compliance
Chapter 8: Best Practices for Application Security, Identity, and Compliance
Understanding the importance of security, identity, and compliance on AWS
Getting familiar with IAM
Managing resources, permissions, and identities using IAM
Learning about other AWS security services
Summary
11
Section 3: Applying Architectural Patterns and Reference Architectures
Section 3: Applying Architectural Patterns and Reference Architectures
12
Chapter 9: Serverless and Container Patterns
Chapter 9: Serverless and Container Patterns
Understanding containerization
Virtual machines and virtualization
Containers versus VMs
Learning about Docker
Learning about Kubernetes
Learning about AWS Fargate
Learning about AWS Batch
Summary
13
Chapter 10: Microservice and Event-Driven Architectures
Chapter 10: Microservice and Event-Driven Architectures
Understanding microservices
Microservice architecture patterns
Benefits of event-driven architecture
Disadvantages of event-driven architecture
Learning about microkernel architecture
Microservices best practices
Summary
14
Chapter 11: Domain-Driven Design
Chapter 11: Domain-Driven Design
Domain-driven design
Microservices
Microservices in AWS
Microservice examples
Summary
15
Chapter 12: Data Lake Patterns – Integrating Your Data across the Enterprise
Chapter 12: Data Lake Patterns – Integrating Your Data across the Enterprise
Definition of a data lake
Purpose of a data lake
Components of a data lake
Characteristics of a data lake
Google – the gold standard
Data lake best practices
Key metrics in a data lake
Summary
16
Chapter 13: Availability, Reliability, and Scalability Patterns
Chapter 13: Availability, Reliability, and Scalability Patterns
Availability in cloud computing
Reliability in cloud computing
Scalability in cloud computing
Architectures to provide high availability, reliability, and scalability
Recovery Point Objective (RPO) and Recovery Time Objective (RTO)
Chaos engineering
Scaling in and scaling out versus scaling up and scaling down
Availability in AWS
Amazon Elastic Load Balancing
Elastic load balancer types
CLB versus ALB versus NLB comparison
The best choice of elastic load balancer by use case
Summary
17
Section 4: Hands-On Labs
Section 4: Hands-On Labs
18
Chapter 14: Hands-On Lab and Use Case
Chapter 14: Hands-On Lab and Use Case
An introduction to the use cases
Reviewing the list of available AWS programming languages
Understanding the serverless AWS microservice architecture
Setting up services
Learning about frontend user interfaces
Authenticating, authorizing, and managing users
Grasping CDN concepts
Understanding the asynchronous communication service
Learning about file uploads
Covering Amazon API Gateway
Reviewing business APIs
Understanding state-machine services
Exploring backend persistence services
Summary
19
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

Chaos engineering

Chaos engineering is a methodology devoted to building resilient systems by purposely trying to break them and expose their weaknesses. It is much better to deal with a problem when we are expecting it to happen. A well-thought-out plan needs to be in place to manage failure that can occur in any system. This plan should allow the recovery of the system in a timely manner so that our customers and our leadership can continue to have confidence in our production systems.

A common refrain is that "we learn more from failure than we learn from success." Chaos engineering takes this refrain and applies it to computing infrastructure. However, instead of waiting for failure to occur, chaos engineering creates these failure conditions in a controlled manner in order to test the resiliency of our systems.

Systemic weaknesses can take many forms. Here are some examples:

  • Insufficient or non-existent fallback mechanisms any time a service fails.
    • ...
Previous Section
End of Section 7
Next Section