How can you balance flexibility and scalability in your architectural patterns?

In my experience, modular architecture might not be easy to implement, especially when there’s a lack of hyperscalers and cloud providers that are “authorized” to host your applications. Design the architecture with the “end in mind”, that at anytime, you could rip and replace any component with impacting the overall system of systems.

In my career, I've seen the good and bad of both monolithic and fine-grained microservices architectures (and multiple shades in between), and I can tell you one thing I'm absolutely certain about from my experience: no architectural style is inherently flawed or virtuous. The engineering discipline tells us that good software architecture is about proper application of the correct patterns to a well-understood problem domain. Domain engineering tends to lead us to the correct distribution of modules; after this, architecture is largely concerned with avoiding an increase in complexity until it's absolutely required.

Baseado no meu conhecimento e na minha experiência, penso que o modelo arquitetural ideal, deve considerar como pontos principais os requisitos e metas do negócio. Ser?o esses direcionadores que poder?o sinalizar um crescimento futuro ou mudan?as significativas. Isso ajudará a determinar quanta flexibilidade e escalabilidade ser?o realmente necessárias. A ado??o de uma arquitetura modular permite a fácil substitui??o e atualiza??o de módulos individuais. Isso proporciona flexibilidade sem afetar a estrutura global do sistema. é uma ótima premissa para uma arquitetura mais flexível!

Modular architecture should be developed by the same team or very close operational teams. Effective modular code ensures that each module is easily testable. If testing a module in isolation proves challenging, it indicates potential room for improvement in defining module boundaries. Neglecting isolation testing means foregoing crucial feedback from your tests.

Evolve your architecture as your team and your product grows. Keep in mind where it is going, but implement for what's needed now. In my experience, your architecture should be as modular as your organisation and team needs to be. Modular architectures can provide value. They let organisations scale, are flexible, and decoupled. At the same time, they have a cost that is not trivial, increases your operational load and coordination efforts, and increases the overall complexity of your technical solution. Pre-mature investment in modularity, and micro-service architectures, can stifle velocity for your team.

Microservices form a distributed architecture. Where each service runs in its own process and usually has its own database. There by achieving a loosely coupled architecture. Microservices is not just limited to backend and even the frontend are broken down into microservices. Ideally each microservice should be extremly functionally cohesive and behave as a one functional module of the overall application.

A arquitetura de microsservi?os permite a escalabilidade independente de diferentes partes do sistema. Cada microsservi?o pode ser desenvolvido, testado, escalado e monitorado individualmente para atender à uma determinada demanda. As interfaces de monitoramento podem contribuir para uma gest?o, seguran?a e controle mais eficiente de um sistema com uma arquitetura de microsservi?o, pois a natureza “granular” deste tipo de arquitetura contribui para uma maior complexidade do sistema.

Desde el inicio de la 1ra generación de microservicios como tal, q nos brindó Netflix, se ha formado una casi religión en torno a este patrón distribuido de arquitectura. En varias empresas he visto como su implementación y su posterior operación en producción causa una serie de inconvenientes. Ya que se multiplican los puntos de falla. Hay que tener cuidado con la madurez de la organización de las áreas tecnológicas y el método de dise?o para poder equilibrar la complejidad de los desarrollos y su operación, con la resiliencia que te da un sistema distribuido. Recomiendo siempre tratar de aplicar DDD en los dise?os de ms. Y por último trabajar muy bien la observabilidad de los procesos. Saludos a todos.

Microservices break tight coupling at the time of coding, build and deployment. Different developers can own (design, devlop and deploy) their microservice independently of each other. Microservices can be scaled up/down independent of each other , which "may" result in better cost management if handled properly. Your application still has somewhat. tight "runtime" coupling. If service A calls service B, which calls service C.. all there services have to be "available" i.e. responsding to incoming traffic in expected way. Microservices have to define and follow interface versioning rule otherwise things break apart at runtime. (Monolith on the otherhand might just fail at build or deployment time).

As a Seasoned Software & Cloud Architect, I have seen many cases where a microservices architecture is a good choice for a system. It allows each service to be flexible, scalable, and independent. But it also adds complexity, overhead, and challenges. It is not a universal solution, but a trade-off. I think it's better to evaluate the system’s needs and follow the best practices of microservices design. I encourage all people (architect or engineers) to use this pattern wisely and carefully, not as a default or trendy choice.

Event driven systems are next step in evolution towards loose coupling. If a microservice A needs some work to be done by service B, doing it via synchronous call creates run time dependency. However moving to async event model means lighter coupling. In its simplest form: A can push a message (or event) to B via a queuing mechanism. B will process the message and respond back on another queue. In more evolved (and complex) form, A and B wouldn't know about each other. A will simply raise an event without knowing who is going to process it. B will subscribe to this event and it doesn't care who publishes the event. It should be kept in mind that going all async "event based" significantly increases overhead.

Event-driven architecture (EDA) helps me build scalable, resilient, and responsive systems for complex and dynamic financial scenarios. It uses events to communicate changes across decoupled services, and data streaming platforms to process and analyze data in near real-time. EDA improves concurrency, performance, agility, user experience, and business intelligence. But it also requires careful design, development, and management, as well as the right tools and technologies. EDA is a powerful option, but not a simple one. It requires a deep understanding of the domain, the system, and the trade-offs involved.

Event driven architecture provides the flexibility and the cost paid is in the way the events are described, usually recommended to have dedicated schemas for the events. Which creates the need for a centralized store for events, which adds complexity. This option provides the highest flexibility in my opinion, it's also very intuitive as everything we perform are events from human interactions, meeting people, UI interactions.

A very helpful pattern while building scalable and modular systems. The best thing about this is that the one who posts the message may not even need to know who is best poised to handle the message or whether it should be handled at all. Different teams would work on posting side and subscriber side.

The event driven architecture relies on asynchronous communication with both fire-and-forget processing (where in the request and send without expecting any response) as well as Async Request/Reply architecture. This improves the resposniveness of your systems. Tradeoffs of event driven architecture are that it only supports eventual consistency, its difficult to test and debug, sometimes difficult to predict the outcome.

Layered architecture is best way for a system design where different hierarchies help different use cases and different generations of IO technologies. Challenge for Architect is the right partition of design and standard interface selection for flexibility.

A arquitetura em camadas n?o é um conceito novo, cada camada tem um objetivo específico, além de ser amplamente utilizado em desenvolvimento de sistemas, no meu ponto de vista, oferece benefícios significativos em termos de organiza??o, manuten??o e seguran?a. No entanto, a escolha da arquitetura dependerá das necessidades específicas do sistema, dos requisitos do negócio e das características do projeto.

while it’s structurally organized and beneficial for separating concerns, faces significant criticism for its performance overhead, as each additional layer can introduce latency, particularly in high-performance systems. Its rigid structure can limit flexibility, making cross-layer interactions difficult and leading to complex, inefficient data handling. its inflexibility makes adapting to changes challenging, especially when modifications span multiple layers, potentially impacting system stability and maintenance. These drawbacks need for consideration of LA , particularly for performance-critical or highly adaptable systems.

From an embedded perspective, scaling large systems this way is effective. Make sure to continue to focus on simplification and rethink the customer needs often to overcome or justify the potential overheads.

Layered architecture is a natural way of thinking and designing a system with its sub systems because usually that’s how we see things in life. The problem is that most of the implementations would just create n layers for the sake of it but have most of the the logic inside one of the layers (mostly data layer). We should give a better thought on what all we really need.

the serverless architecture makes it possible to carry out pre or post processing steps during a chain of calls to AI models on the shelf or developed from open source libraries, focusing only on its libraries and not on the infrastructure.

Serverless architecture have becoming extremely popular and usally operates on event driven architecture. One of the example of serverless architecture is FaaS(Function as a service) which is provided by several cloud providers like Azure Functions, AWS Lambda, Google Cloud Functions etc. Serverless architetures are usually used to reduce the overall cost of maintaining the infrastructure and works on the principle of pay-as-you-use. The most common problem with Serverless architecture is the cold start. Usually it takes some time to startup your application. So if the number of request to your serverless application is too many and it takes less time to process than the startup, its best not to use serverless architecture.

Serverless lets me focus on business value, not servers. It scales and charges based on usage, saving time and money. It also enables faster and more frequent deployments. But it also adds complexity and abstraction, making debugging, testing, and monitoring harder. It also has limitations and trade-offs, such as cold starts, latency, vendor lock-in, and state management. So I have to choose wisely and use best practices and tools. Serverless is powerful, but not perfect.

Serverless architecture is rapidly evolving, led by tech giants integrating advanced AI and machine learning capabilities into their offerings. AWS exemplifies this trend with serverless options for services like Amazon Lex and SageMaker, enabling sophisticated application development without complex infrastructure management. Google Cloud and Firebase integration enhances developer experiences, focusing on feature development over infrastructure concerns. Microsoft Azure's extension of serverless to edge computing with Azure IoT Edge is notable, particularly for real-time, data-intensive applications like autonomous vehicles. Overall, it offers significant benefits in terms of scalability and operational efficiency.

Stability in serverless architecture focuses on creating a robust foundation that handles varying workloads and maintains consistent performance.Utilizing serverless functions for event-driven tasks, such as image processing in response to user uploads. The serverless nature ensures automatic scaling to handle varying workloads, providing stability under load spikes. This allows for independent development and deployment of services, promoting flexibility. Break down the system into microservices, with individual functions handling specific tasks. This enables flexibility in updating and scaling components independently. An e-commerce platform using serverless functions and Each function scales independently based on demand.

Whatever architecture you choose, be sure to factor in the developer experience. The developer loop is how long it takes someone to change some code and then run it. If you have an architecture with a challenging developer experience or long developer loops, these issues compound greatly on the path to production.

Try not to always "Fight the Last War" your system architecture should blend the tools that solve the problem best to your team's knowledge with the skillset of folks in your org. Continued simplification of complexity is also a great lens "don't need it, delete it". Challenging ourselves to continuously evolve architecture can help ensure your organization will withstand the test of time.

When building flexible and scalable architecture, the telemetry should not be an afterthought. It should be up and central to the design so that you create a diagnostic and feedback loop from day one.

I think scalability and flexibility is not a challenge in the morden era what we should actually know is the pattern and behaviour of the product. It is easy to throw bunch of hardware to scale up the system but does it actually needed. Cost is always and biggest challenge in this scenario. So you should understand your traffic pattern and also should have proper rate limiting in place for each component so that it should not overwhelm the downstream components.

To add to the list , defining clear API adhering to Industry standard makes it easier to interact with other systems and allows for the independent upgrade. Another contributing factor is to Have a good CI CD pipeline with automated build, test and deploy pipelines, reduces the risk of error and eases up the process of upgrades easy.