Book Image

Architectural Patterns

By : Anupama Murali, Harihara Subramanian J, Pethuru Raj Chelliah

Book Image

Architectural Patterns

By: Anupama Murali, Harihara Subramanian J, Pethuru Raj Chelliah

Overview of this book

Enterprise Architecture (EA) is typically an aggregate of the business, application, data, and infrastructure architectures of any forward-looking enterprise. Due to constant changes and rising complexities in the business and technology landscapes, producing sophisticated architectures is on the rise. Architectural patterns are gaining a lot of attention these days. The book is divided in three modules. You'll learn about the patterns associated with object-oriented, component-based, client-server, and cloud architectures. The second module covers Enterprise Application Integration (EAI) patterns and how they are architected using various tools and patterns. You will come across patterns for Service-Oriented Architecture (SOA), Event-Driven Architecture (EDA), Resource-Oriented Architecture (ROA), big data analytics architecture, and Microservices Architecture (MSA). The final module talks about advanced topics such as Docker containers, high performance, and reliable application architectures. The key takeaways include understanding what architectures are, why they're used, and how and where architecture, design, and integration patterns are being leveraged to build better and bigger systems.

Preface

What this book covers

What you need for this book

Who this book is for

Reader feedback

Free Chapter

Demystifying Software Architecture Patterns

Demystifying Software Architecture Patterns

Envisioning the software-defined world

Software patterns

Software architecture patterns

The EDA fundamental principles

The ED-SOA composite pattern benefits

Microservices architecture (MSA)

Event-driven microservices patterns

Space-based architecture (SBA)

Combining architecture patterns

Special-purpose architectures

Real-time context-aware prediction architecture

Additional reading materials

Client/Server Multi-Tier Architectural Patterns

Client/Server Multi-Tier Architectural Patterns

Domain name service (DNS) server and DNS client

Functional requirements in two-tier client-server patterns

The three-tier pattern / multi-tier pattern client-server

Three-tier client-server architecture

The distributed client-server architecture

Motivation for development of web application patterns

The ASP.Net framework

Design patterns for web application development

Object-Oriented Software Engineering Patterns

Object-Oriented Software Engineering Patterns

Key elements of OOD

Design principles

OO design patterns

Concurrency patterns

Enterprise Integration Patterns

Enterprise Integration Patterns

Need for integration patterns

Integration scenarios in enterprises

Main challenges in enterprise integration

Getting started with messaging patterns

Pipe and filter pattern

Message router pattern

Message translator pattern

Message endpoint pattern

Point-to-point channel pattern

Publish-subscribe channel pattern

Datatype channel pattern

Message bus patterns

Command message patterns

Event message patterns

Request-reply pattern

Content-based router pattern

Message filter pattern

Resequencer pattern

Polling consumer pattern

Channel adapter

Mobile integration pattern

Request-response pattern

Defining a push notification pattern

API management pattern

Domain-Driven Design (DDD) Principles and Patterns

Domain-Driven Design (DDD) Principles and Patterns

Principles, characteristics, and practices of DDD

Integrating bounded contexts

Integrating with legacy systems

Distributed bounded context integration strategies

Tactical patterns

Patterns to model the domain

Emerging patterns

References and further reading materials

Enterprise Architecture Platforms and Tools

Enterprise Architecture Platforms and Tools

Overview of enterprise architecture frameworks

Getting started with TOGAF

Architecture development method (ADM)

Deliverables, artifacts, and building blocks

Enterprise continuum

Architecture repository

Zachman framework for enterprise architecture

Enterprise architecture platforms and tools

Enterprise Architect from Sparx Systems

ABACUS from avolution software

Service-Oriented Architecture (SOA)

Service-Oriented Architecture (SOA)

Web services and SOA

Introduction to SOA

Life cycle of SOA

Primary characteristics of SOA

Principles of SOA

SOA design patterns

Event-Driven Architectural Patterns

Event-Driven Architectural Patterns

Service-oriented architecture and event-driven architecture (SOA versus EDA)

Key characteristics of event-driven patterns

Event flow layers

Design considerations for event-driven patterns

Implementation variants of EDA patterns

Types of event-driven patterns

EDA pattern implementation in systems/processes

Improving the performance of EDA-based processes/systems

IBM WebSphere MQ

Emerging trends in EDA

Microservices Architecture Patterns

Microservices Architecture Patterns

Microservices patterns

Remote procedure invocation (RPI) pattern

Messaging design pattern

Domain-specific protocol pattern

API gateway pattern

Service discovery pattern

Service registry pattern

Service registration pattern

Event-driven architecture (EDA) patterns

Event sourcing pattern

Transaction log tailing pattern

Publishing events using the database trigger pattern

Application publishes events pattern

Testing and troubleshooting patterns

Access token pattern

Service component test pattern

Log aggregation pattern

Application metrics pattern

Distributed tracing pattern

Health check API pattern

Circuit breaker pattern

Patterns for Containerized and Reliable Applications

Patterns for Containerized and Reliable Applications

Docker image building patterns

Multi-stage image building pattern

The pattern for file sharing between containers

Pipes and filters pattern

Containerized applications - Autopilot pattern

Containers - persistent storage patterns

Docker compose configuration pattern

Docker container anti-patterns

Patterns for highly reliable applications

Resiliency implementation strategies

Software-Defined Clouds - the Architecture and Design Patterns

Software-Defined Clouds - the Architecture and Design Patterns

Reflecting the cloud journey

Traditional application architecture versus cloud application architecture

Cloud integration patterns

Cloud design patterns

Cloud reliability and resilience patterns

Cloud security patterns

Big Data Architecture and Design Patterns

Big Data Architecture and Design Patterns

The four V's of big data

Big data analysis and technology concepts

Big data analysis and data science

Big data platform

Big data architecture landscape and layers

Big data architecture patterns

Big data design patterns

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The four V's of big data

Big data has many definitions and many different implementations across various sectors. However, there are four common elements of any big data definition, which are popularly referred to as the V's of big data. They are as follows:

Velocity: This refers to the speed of data accumulation
Volume: This refers to the scale of data or the phase that data storage grows
Variety: This refers to the diversity of the data, such as structured, semi-structured, unstructured, and so on
Veracity: This refers to collected data's accuracy and its reflection of facts

The latest addition to the V's group is value. This refers to our ability and needs to turn accumulated data into things of value. That is not just business value, but it can also be any significant added value for social, medical, and common causes.

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