Architectural Decisions for Efficient Project Resolutions: A Technical Perspective

Having a detailed architectural solution allows the business to accurately estimate the timeline and cost of product implementation. Moreover, it provides the opportunity to define the system characteristics at the start. This ensures that they align with business goals. Quality criteria for IT architecture include scalability, risk reduction, performance speed, and the possibility of independent contractor selection.

In this article, I’ll examine the stages of working with architectural IT decisions, potential challenges, and solutions based on my experience.

Product Requirements

Our goal is to design software architecture in a systematic, predictable, and cost-effective manner. To achieve this, product requirements need to be defined. Typically, the technical specification for product development contains requirements, but these are not always comprehensive. Thus, key tasks for the IT architect include gathering and analysing requirements, creating the architectural design and documentation, verifying the solution, and overseeing the software development process.

Let's consider what the list of requirements includes:

• Design Objective

The objective determines what is needed at the start: a detailed architecture or a preliminary system overview to estimate the scope and cost of the work.

• Quality Attributes and Non-functional Requirements

These attributes define the properties the system must exhibit — performance, availability, security, and usability requirements.

• Functional Requirements

They define the actions the system is capable of performing.

• System Requirements

These emerge gradually during detailing and are implemented iteratively, for example, authorization, logging, and caching.

• Constraints

These requirements are not directly related to system behaviour and are beyond our control. For instance, a client may prefer microservice architecture over monolithic architecture. Legal requirements, such as those for personal data storage, also fall into this category.

Usually, the product owner does not have a complete list of system requirements in advance, so the architect organises the process of gathering and documenting them. From all system requirements, the specialist must identify the architecturally significant ones that have a profound impact on the final solution.

What a Good Architecture Implies

When discussing good architecture, we generally imply the following:

Flexibility

The ability to adapt the product to new business requirements, even if these were not fully known at the beginning of the design process.

For example, when creating a boxed solution for data analytics, we initially included support for seven main types of data sources but also made provisions to quickly add any other necessary data sources.

Quality

It ensures optimal values of the product's quality attributes during the architectural design process.

Compliance

Adaptation to system constraints and compliance with technical and operational requirements, including the technology stack, handling of personal data, big data, and numerous integrations.

What to Decide On

Defining efficient architecture means making a set of decisions on what methods, technologies and tools we are going to use. All the practices are bound to align with the project's business goals. Besides, as we have discussed before they need to ensure scalability, and maintain flexibility for future needs.

Architecture Style

Here you will need to decide between a monolithic architecture and a microservices architecture. A monolithic architecture offers simplicity and ease of deployment as it packages all functionalities into a single application. In turn, a microservices architecture divides the application into smaller, independent services that can be developed, deployed, and scaled separately.

Besides, you should consider Implementing a Service-Oriented Architecture that presumes designing the system so that different services communicate over a network. This approach promotes reusability and integration.

Technology Stack

Now you will have to choose programming languages and frameworks that best match the project's requirements and the team's expertise. Additionally, selecting the appropriate database solution, whether SQL, NoSQL, or hybrid, is important. Mind that it should be based on factors like data consistency, scalability needs, and query requirements.

Cloud vs. On-Premises Deployment

You must also consider either using cloud services (AWS, Azure, or Google Cloud) or opting for on-premises solutions. The last one may be necessary when data security, compliance, or specific performance requirements are of greater importance.

Scalability and Performance

When it comes to scalability, you will need to decide on implementing load balancers and auto-scaling for efficient load management and using caching mechanisms to improve performance and reduce the load on databases.

Security and Compliance

Another important set of decisions that we need to make is about security and regulatory compliance. What is crucial here? First of all, we want to provide data encryption both in transit and at rest. Then we need to implement robust access control mechanisms. Besides, we should not forget about the industry-specific standards to which the company needs to be compliant. These are GDPR, HIPAA, or PCI-DSS and others.

DevOps

At this stage, we have two important issues to bear in mind. First, if we want to reduce manual errors then it is worth using CI/CD pipelines to automate testing and deployment. Continuous Integration lets us frequently integrate code and automated tests are sure to catch issues ASAP. And Continuous Deployment in its turn will help deploy code changes automatically to production. All of the above will make your releases faster and more reliable.

Second, managing infrastructure through code is a game-changer for consistency and ease of replication. With IaC, infrastructure configuration is managed through code files, which are easy to edit, copy, and distribute. These files can be version-controlled like any other source code. This approach solves many problems caused by manual infrastructure management. It enhances reliability and consistency and makes the overall system management less error-prone. Tools like Terraform, Ansible, and CloudFormation are commonly used to implement IaC.

API Design and Integration

When deciding on architectural choices, consider whether to implement RESTful APIs for their simplicity and broad industry adoption, or opt for GraphQL for its efficiency in data retrieval and flexibility. Implementing an API gateway may also be useful to manage and secure API traffic. These decisions will impact how your application interacts with clients and external services, influencing both performance and developer experience.

Monitoring and Maintenance

While setting up your system, it's essential to implement observability tools such as monitoring, logging, and alerting systems. Also, plan for scheduling regular maintenance and updates is critical to maintaining system security and efficiency.

Reusability

If system reusability is a priority, consider employing a component-based design approach. This involves structuring systems with reusable components, which simplifies updates and maintenance processes. Besides, promoting code reuse across projects can significantly reduce development time and enhance consistency in software implementation. These strategies collectively support the creation of scalable and at the same time adaptable systems.

User Experience

Last but not least, prioritise responsive design to ensure applications adapt seamlessly across various devices, enhancing user experience. It is also important not to overlook the users with disabilities and to follow standards for inclusivity and usability.

Case-Study: Efficient Microservices Development through a Shared Framework

Next, I will outline the process of making architectural decisions based on my experience during one of my recent projects.

Background

My team had a task to develop two separate but closely related microservices for storing and displaying hierarchical information. At the beginning of the planning phase, we discovered significant overlaps in their functional requirements. As we have made this observation we decided to develop a shared framework to support both projects and any future similar tasks instead of building two independent solutions.

Architectural Decision-Making

We assembled a team of engineers to focus on the project architecture. Their primary task was to create a comprehensive design document. The team began by delineating the requirements for both services to pinpoint similarities. This was important as it helped shape our approach. As I have mentioned we concluded that instead of parallel development tracks, we need to stick to a single, robust framework that could serve multiple microservices.

The core of our architectural solution was the development of a JSON-configurable framework. We designed a framework that dictated the system's behaviour. It covered the data model, validation processes, API functionalities, and role-based access controls. Furthermore, we built an extensible client-side with a suite of ready-to-use components.

Implementation and Results

One of the greatest advantages was that the design document we had prepared not only guided the successful delivery of the two microservices but also served as the basement for future projects. The real test of our architectural decision came with subsequent project demands: already within the next release cycle, we faced four additional requests for similar microservices.

We managed to deliver the new services much faster mainly because we already had a scalable and configurable framework. So most of the work only required adjusting configurations instead of writing new code. This saved us a lot of time and reduced the need for extra resources. We outsourced the fourth service to an external team, who used our design documents as a guide and efficiently completed the task.

Conclusion

As you can see, anticipating future needs and designing scalable and reusable solutions becomes one of the pillars of efficient project resolution. We invested in a configurable and extensible framework initially and streamlined the immediate project delivery. Besides, we also simplified future developments. This strategy dramatically enhanced our operational efficiency and proved the value of architectural foresight in software development projects.