Capacity Planning vs Reactive Scaling

Developers should learn capacity planning to design scalable systems, avoid performance issues, and reduce operational costs by aligning technical resources with business needs meets developers should learn and use reactive scaling when building cloud-native applications, microservices, or distributed systems that experience unpredictable traffic patterns, such as e-commerce platforms, streaming services, or iot applications. Here's our take.

Capacity Planning

Nice Pick

Developers should learn capacity planning to design scalable systems, avoid performance issues, and reduce operational costs by aligning technical resources with business needs

Pros

• It is essential when building applications with variable traffic (e
• Related to: system-design, performance-optimization

Cons

• Specific tradeoffs depend on your use case

Reactive Scaling

Developers should learn and use Reactive Scaling when building cloud-native applications, microservices, or distributed systems that experience unpredictable traffic patterns, such as e-commerce platforms, streaming services, or IoT applications

Pros

• It helps prevent over-provisioning of resources during low demand and avoids performance degradation during spikes, ensuring high availability and cost-effectiveness in environments like AWS, Azure, or Kubernetes
• Related to: reactive-programming, microservices-architecture

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Capacity Planning is a methodology while Reactive Scaling is a concept. We picked Capacity Planning based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Capacity Planning wins

Based on overall popularity. Capacity Planning is more widely used, but Reactive Scaling excels in its own space.