How can you design software systems to be scalable and efficient?

This is the first and most crucial step in making the software system modular. Broadly Modularization can be done at the following levels : 1. System Level 2. Code Level 3. Data Level 4. Infrastructure Level 1. System Level: If you are developing a cloud application, you should consider Micro Frontends and Microservices Architecture. 2. Code Level: You can ensure your code is modular by following the SOLID Design principles and the Design Patterns. 3. Data Level: This can be done by applying database sharding or partitioning to distribute data across multiple databases or instances. 4. Infra Level: Consider using infrastructure as code (IaC) and using container orchestration tools like docker etc.

One option is to start with a Modular Monolith, which involves designing a decoupled system with well-defined boundaries. This allows for easier management and avoids the complexity of Microservices at the beginning. A Modular Monolith can later be split into Microservices when scaling becomes necessary. On the other hand, if resources allow for a sizable budget and there is a proficient team available, starting directly with a Microservices architecture can provide more flexibility and scalability from the start. It's important to consider the specific requirements and context of the project when deciding between these approaches.

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I disagree. You don't need to make your code as fast and lean as possible. The first thing you should to is measure performance and establish a performance baseline. Is the performance good enough for your application? If yes, leave it as it is. Is it not enough? Start profiling and see which parts have the most impact on the performance and think about how you can speed them up. Since you have a baseline you can now see if your changes made it better or worse.

Start with a clear understanding of the system's current and future requirements. Use loosely-coupled, modular components that can scale independently. Leverage cloud-based resources and load balancing to manage fluctuating demand. Example: Implement a microservices architecture which allows for independent scaling of each service based on the demand. Distribute the load evenly across your system to prevent any single component from becoming a bottleneck. This can be achieved using different strategies like Round Robin, Least Connections, or IP Hash.

While distributing your system can help to increase availability and scalability it comes with a complete new set of challenges. How do you replicate data? How do you keep costs from exploding? How do you deploy updates? And many more.. There are solutions to these questions but you have to be aware of the effort it takes to actually distribute your system.

Continuous iteration is key to improving the user experience for all types of digital products. You need to monitor and measure the system performance and resource utilisation. This can be done by tracking and analysing the right data using a "measure, improve" loop, focusing on meaningful KPIs, avoiding vanity metrics, and using analytics tools to monitor user behaviour and identify pain points.

Pushdown Processing: Instead of retrieving large datasets from the storage layer and filtering them later in the web tier, push the filtering conditions to the backend as early as possible. This minimizes data transfer volumes and reduces processing overhead in the application layer. It's essential to leverage the capabilities of your storage system, be it a relational database, NoSQL store, or a distributed data processing platform. Asynchronous Processing: Use asynchronous methods for tasks that don't require immediate feedback.

Understanding the business context and user needs is also crucial for making better decisions in terms of design, implementation, and prioritisation. Additionally, scaling should ideally follow a phase of testing, iteration, and validation, where the business model is proven and the product is validated with a dedicated user base.