Have you ever pondered how large enterprise systems are designed? Prior to starting any android software development, it is imperative to choose the appropriate architecture that will offer the required functionality and quality characteristics.
Opting for the latest or most popular technology in the market does not always mean that it would give promising results; although, this in no way infers that you should opt for legacy technologies. Comprehensive planning should be done while selecting an architecture pattern.
In layman’s terms, software architecture is the procedure of transforming software characteristics such as feasibility, reusability, flexibility, security, and scalability into a structured solution in order to meet the technical and the business potentials. Software architecture functions as the outline for both the system and the project developing it, delineating the work assignments that design and implementation teams need to carry out.
Enterprise software architecture implies an architecture designed for the structured growth and development of an enterprise’s information technology (IT). Rather than simply looking at the procedures being used on a daily basis, it converges on the continuing evolution of IT systems. The quality of the enterprise software architecture implemented plays a pivotal role in influencing an organization’s success. By easing system complexity, enterprise software architecture can increase overall efficiency.
The most common challenges faced by enterprise architecture consist of; ineffectual communication, complex enterprise architecture tools, low enterprise architecture maturity and dedication, and misleading roles with enterprise architecture.
Components of Enterprise Architecture:
Why is Enterprise Architecture Required?
- To integrate all the IT costs (accreditation, system security plan, risk assessment, privacy impact assessment, configuration/patch management, security control testing and evaluation, contingency planning/testing) into one.
- To help in impending workforce planning issues like staffing and training and associated investment.
- To ensure the overall vision of the business interprets into actionable business.
- To ensure the security categorization process for information systems is compatible with and complements the organization’s mobile app architecture and consigns to protecting organizational mission/business.
- To ensure the conceptual solution architecture supports the target performance, data and business architectures, and the transit from as-is state to the to-be state.
- To ensure the organization’s digital business strategy (models, designs, technology) influences the organization’s EA discipline and deliverables.
- To ensure that both the leadership teams and business attune current business and information environments to realize the target performance architecture.
Types of Software Architecture:
Layered (n-tier) Architecture –
This type of architecture approach is probably the most widely used as it is typically built around the database, and several applications in business innately give themselves to storing information in tables. Most of the major and best software frameworks for example Drupal, Express and Java EE were developed keeping this structure in view, so various applications built with them implicitly come out in a layered architecture.
The code is organized such that the data makes its way through the top layer and works all the way down through each layer to reach the bottom, which is generally a database. Along its way, each layer performs a particular task on the data. It is generally common for different programmers to work individually on different layers.
A standard software development methodology offered by the majority of the popular web frameworks, the Model-View-Controller (MVC) structure, is evidently a layered architecture.
The perk of a layered architecture is the segregation of tasks, which implies that each layer can concentrate exclusively on its task, which in turn makes it:
- Easy to allocate individual “roles”.
- Easy to update and augment layers independently.
Aptly layered architectures have segregated layers that would not get affected while making changes in other layers, which allows for easier restructuring. Also, the architecture can include additional open layers, for instance, a service layer, that can be used to access shared services only in a certain layer but can be circumvented for speed.
The biggest challenge for the architect is to divide the tasks and outline separate layers. However, with the requirements corresponding to the pattern well, it is easy to separate the layers and allocate them to different programmers.
The other caveats for layered architecture include assembling the source code into organized modules, outlining the roles and linking it with relationships, traversing data through layers with logic, dealing with disorganized inter-dependencies, all of this while continuing to be objective and apposite.
This architecture is best suited for new applications that are required to be developed swiftly, enterprise or business applications with the need to emulate conventional IT departments and processes, teams with naive developers who don’t comprehend other architectures, applications necessitating strict sustainability and testability criteria.
Event-driven Architecture –
Several programs beguile most of their time anticipating an event to trigger them, especially for the systems that interact directly with humans. In an event-driven architecture, this is managed by building a central unit that collects all the data and then allots it to the different modules that are designed to handle the specific type. This allotment is said to trigger an “event,” and it is designated to the code assigned to that type.
On the whole, event-driven architectures are easily adjustable to convoluted, often messy environments, scalable, easily extendable in case new event types emerge.
The challenges faced in this architecture are:
- Testing can be complicated in case the modules can affect each other. Although the individual modules can be tested separately, the interactions between the modules can only be tested in a fully functional system.
- It would be difficult to structure error handling, particularly in the scenario where various modules must respond to the same events.
- The central unit needs to have a backup plan in place in case the modules fail.
- As the events have very different requirements, developing a system-wide data structure for events can be a complicated task.
- Difficult to maintain a transaction-based method for consistency as the modules are so separated and autonomous.
This type of architecture is best suited for unsynchronized systems having nonsynchronous data flow, applications where the discrete data blocks communicate with merely some of the various modules, user interfaces.
Microkernel Architecture –
Several applications have a core set of operations that are used frequently in different patterns depending upon the data and the disposed task. Eclipse, the popular development tool, for example, will access files, analyze them, edit them, and initiate background processors. The tool is renowned for performing all these tasks with Java code and then, with a push of a button, compiling the code and executing it. In this scenario, the fundamental routines for displaying a file and editing it are elements of the microkernel. The additional features that are layered on top are often called plug-ins. This extensible approach is also called by many a plug-in architecture instead.
The challenges posed in this architecture are;
- It is often an art to determine what should belong in the microkernel as it is ought to hold the code that is frequently used.
- The plug-ins need to comprise a reasonable amount of handshaking code so as to make the microkernel aware that the plug-in is ready to work.
- In set-ups where a number of plug-ins depend upon microkernel, it is very difficult to make changes to the microkernel. Oftentimes to modify the plug-ins in conjunction turns out to be the only solution.
This type of architecture is best suited for tools utilized by varied categories of people, applications with a well-defined demarcation between basic routines and higher-order rules, applications with a static set of core routines and a dynamic set of rules that need to be updated recurrently.
Microservices Architecture –
This approach is relatively similar to the event-driven and microkernel approaches, but it is employed mainly in the scenarios where the different tasks are easily segregated. In this architecture, instead of building one big program, a number of small programs are created and then every time a new feature is required, a new little program is developed and added.
The challenges faced in this architecture are:
- The programs should be essentially independent, otherwise, the cloud can become imbalanced because of the interaction.
- It is difficult to figure out which application tasks can be easily split into individual units.
- Having a lot of micro services can lead to confusion for the users as some parts of the web page load later than others.
This type of architecture is best suited for websites with few components, data centers that have precise boundaries, promptly developing new businesses and web applications, development teams spread out at different geographical locations.
Space-based Architecture –
Usually, the websites built around a database continue to function well until the database is able to carry on with the load; however, in times of peak usage, there is always a significant risk of crashing the whole website if the database cannot persevere with the relentless challenge of maintaining a log of the transactions.
To avoid this operational collapse under high load, the space-based architecture is designed by separating both the processing and the storage amongst multiple servers. The term “space-based” indicates the “tuple” space of the users, which is divided up to partition the work amongst the nodes. Sometimes a more indistinct term “cloud architecture” is also used for this architecture. The space-based architecture props tasks that have variable spikes by purging the database.
- It is difficult to provide transactional support with RAM databases.
- It is quite challenging to generate sufficient load to evaluate the system, however, the individual nodes can be tested separately.
- It is difficult to develop the expertise for caching the data for speed without corrupting multiple copies.
Space-based architecture is best suited for high-volume data like click streams and user logs, low-value data that can be lost intermittently without big concerns, social networks.
While the above-detailed architectures suggest the most preferred design choices for organizational software development, there are many others that are equally appealing and could be more appropriate to your requirements. However, it is always vital to understand the pattern clearly, since applying the wrong pattern can create a lot of issues like inappropriate designs and implementations. A development expert would possess a reliable judgment that would help you comprehend which pattern is best suited in a specific business scenario.
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