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Architectural Patterns

Architectural Patterns

By : Murali, Pethuru Raj, J, Pethuru Raj Chelliah
2.4 (5)
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Architectural Patterns

Architectural Patterns

2.4 (5)
By: Murali, Pethuru Raj, 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.
Table of Contents (13 chapters)
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Space-based architecture (SBA)

Typically, enterprise applications are being blessed with a backend database management system. These enterprise-scale applications function well as long as the database is able to keep up with the load. But when usage peaks and the database can't keep up with the constant challenge of writing a log of the transactions, the application is bound to fail. In any high-volume application with an extremely large concurrent user load, the database will usually be the final limiting factor in how many transactions we can process concurrently. While various caching technologies and database scaling products help to address these issues, it is still a pipe dream that scaling out a normal application for extreme loads is a very difficult proposition.

The space-based architecture is designed with the aim of empowering software systems to work even under the heavy load of users. This is being achieved by splitting up both the processing and the storage between multiple servers. The data is spread out across many nodes. The space-based architecture pattern is widely used to address and solve scalability and concurrency issues. Customer-facing applications are quite unpredictable and this specialized architecture is competent and cognitive enough to support a large number of users.

High scalability is achieved by removing the central database constraint and using replicated in-memory data grids instead. Application data is kept in-memory and replicated among all the active processing units. Processing units can be dynamically started up and shut down as the user load increases and decreases, thereby addressing variable scalability. Because there is no central database, the database bottleneck is removed, providing near-infinite scalability within the application. Most applications that fit into this pattern are standard websites that receive a request from a browser and perform some sort of action. A bidding auction site is a good example of this. The site continually receives bids from internet users through a browser request. The application would receive a bid for a particular item, record that bid with a timestamp, update the latest bid information for the item, and send the information back to the browser.

Precisely speaking, the SBA style is primarily for ensuring the goals of higher concurrency. Next-generation applications have to be scalable, available, and dependable. The SBA pattern is a great enabler.

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