Why do 70% of IT systems fail to scale?

(Spoiler: It’s not the developers — it’s the system design process.)

As a Senior Frontend Developer with experience in building scalable ReactJS and TypeScript applications, I’ve seen this play out time and time again:

👉 Building systems that work is easy.
👉 Building systems that scale? That’s where most teams fall short.

The Root Problem: Lack of Foresight

Most teams focus on building for now instead of designing systems that can handle:

• 📈 Increased traffic

• 🔗 Diverse integrations

• 🔄 Unforeseen use cases

But it doesn’t have to be this way.

Here’s a scalable system design framework I’ve successfully used:

1. Start with scalability in mind.
   Ask questions like: What happens when traffic doubles? Triples?
   Use cloud-native architectures and modular design patterns to ensure flexibility.

2. Leverage TypeScript for better planning.
   Go beyond type safety — TypeScript helps predict edge cases and reduces technical debt.

3. Prioritize monitoring and fail-safes.
   Build-in health checks, logging, and fallback mechanisms.
   What gets measured, gets improved.

4. Adopt API-first design.
   This future-proofs your system and makes integrations seamless as your needs evolve.

“Scalability is an art of foresight, not just coding.”

Let’s go deeper. Here are 3 powerful design patterns for scalable systems:

1.Circuit Breaker Pattern (Source)

• Isolates problematic services to prevent system-wide failures

• Detects failing components and stops requests automatically

• Provides fallback mechanisms during disruptions

• Example: Netflix’s resilience in handling distributed system failures

2. Event-Driven Architecture (Source)

• Enables asynchronous, loosely coupled system interactions

• Uses message queues for decoupled communication

• Handles sudden traffic spikes with ease

• Improves system responsiveness and fault tolerance

3. CQRS (Command Query Responsibility Segregation) (Source)

• Separates read and write operations into distinct models

• Optimizes performance for data-intensive applications

• Scales read and write processes independently

• Simplifies system complexity while improving efficiency

Key Takeaways

1. Scalability is a strategic design decision — not a technical afterthought.

2. Invest in architectural patterns that promote flexibility and resilience.

3. Prioritize continuous monitoring and iterative improvements to future-proof your systems.