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+---
+ready: true
+title: "The Architecture of Modern Web Applications"
+description: "How to think about and build scalable, maintainable, and lasting systems in the age of microservices and cloud-native infrastructure."
+date: "2026-04-10"
+category: "Architecture"
+tags:
+  - "Architecture"
+  - "Web"
+  - "Scalability"
+  - "Cloud"
+readTime: "8 min"
+---
+
+<div>
+  <h2>Laying the right foundations</h2>
+
+  Software architecture is the art of making structural decisions before writing the first line of code. A poor decision at this stage can cost months of refactoring later. Yet too many projects start without giving it the time it deserves.
+
+  The first question to ask isn't "what technology should we use?" but "what are the real constraints of the system?" Data volume, update frequency, number of concurrent users, availability requirements — these parameters dictate technical choices long before the programming language comes into play.
+
+  A well-architected system is not necessarily complex. Complexity is often a sign of a poor understanding of the problem, not a good solution. The goal is to achieve appropriate simplicity: robust enough to meet the needs, simple enough to remain maintainable.
+</div>
+
+<div>
+  <h2>Monolith or microservices?</h2>
+
+  This debate comes up endlessly. In reality, there is no universal answer — only different contexts.
+
+  A well-structured monolith is often the best option for starting a product. It is simpler to develop, deploy, and debug. The boundaries between modules remain malleable as long as the functional scope is rapidly evolving. Microservices add significant operational complexity: managing network failures, distributed data consistency, and orchestrating deployments.
+
+  The move to microservices is justified when distinct teams need to evolve independently, when certain components require different scaling strategies, or when security constraints impose strong isolation. It's not a question of project size, but of organizational maturity.
+
+  Progressive migration remains the best approach: identify natural bounded contexts in the monolith, extract them one by one, and validate each split before moving on.
+</div>
+
+<div>
+  <h2>Scalability: a property to design from the start</h2>
+
+  Scalability cannot be added as an afterthought. It must be designed upfront, through data modeling choices, the way services communicate, and state management.
+
+  A few guiding principles:
+
+  **Stateless by default.** Stateless services are intrinsically easier to scale horizontally. State must be externalized to dedicated systems — databases, distributed cache, message queues — and not stored in process memory.
+
+  **Event-driven decoupling.** Event-driven architectures reduce temporal coupling between services. A service publishes an event; consumers react at their own pace. This approach improves resilience and makes it easier to evolve components independently.
+
+  **Multi-level caching.** CDN for static assets, application cache for frequently read data, query cache on the database side. Each cache layer reduces load on the downstream system and improves response times.
+</div>
+
+<div>
+  <h2>Technical debt: the silent enemy</h2>
+
+  Technical debt is inevitable. What is not inevitable is letting it accumulate without a repayment strategy. Every conscious simplification decision — a shortcut taken to meet a deadline — must be documented and scheduled for correction.
+
+  Warning signs are often subtle: increasing onboarding time for new developers, multiplying regression bugs, a general feeling that "changing anything is risky." These signals typically precede crises by several months.
+
+  Systematically allocating part of each sprint to technical health is not a luxury — it is a medium-term survival condition for any ambitious product.
+</div>