<aside> 💡 Generated by BigBrain. Repeated material was merged while distinct trade-offs, caveats, examples, and operational details were retained.

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Scalability, Latency, and Throughput

Fundamentals of Scalability, Latency, and Throughput

Scalability, latency, and throughput are critical dimensions of distributed systems design. Scalability refers to the ability of a system to handle increased load by adding resources. Latency measures the time taken to process a request, while throughput quantifies the number of requests a system can handle per unit of time. These metrics often involve trade-offs, and optimizing one can impact the others.

Scaling Components and Data Paths

Why Scale?

Scaling is necessary to:

• Handle greater workloads.
• Serve more users.
• Process more requests.

Scaling can apply to backend services, web applications, databases, or caches. While scaling is often a sign of success, it can also be driven by inefficiencies or bugs that cause resource overuse.

Vertical vs. Horizontal Scaling

• Vertical Scaling:
• Involves upgrading hardware (e.g., more RAM, faster CPUs).
• Advantages:
• Simple to implement.
• Avoids distributed data complexities.
• Disadvantages:
• Not cost-effective long-term.