10. Scalability & Performance
Capacity Planning
Capacity Planning is a practical part of software architecture. Learn the concepts, forces, alternatives, failure modes, operational consequences, and trade-offs involved. Connect the topic to business requirements, system boundaries, data ownership, security, reliability, performance, team ownership, and long-term change.
Lesson overview
Capacity Planning
Capacity Planning is a practical part of software architecture. Learn the concepts, forces, alternatives, failure modes, operational consequences, and trade-offs involved. Connect the topic to business requirements, system boundaries, data ownership, security, reliability, performance, team ownership, and long-term change.
This lesson explains capacity planning from first principles. Start by identifying the problem it solves and the constraints under which it is useful. Then examine common designs, dependency direction, data flow, failure behavior, scaling implications, security considerations, observability requirements, and maintenance cost. Compare alternatives instead of assuming one pattern is universally correct. A production architecture is successful when it meets measurable requirements while remaining understandable and changeable.
Practical workflow
Practice: Draw a detailed architecture diagram for capacity planning. Mark responsibilities, ownership, interfaces, dependencies, trust boundaries, failure boundaries, and monitoring signals. Write an architecture note explaining what would make you revisit the decision.
Learning path
Theory โ Example โ Code โ Practice โ Quiz โ Challenge โ Completion
Step 1
Theory
This lesson explains capacity planning from first principles. Start by identifying the problem it solves and the constraints under which it is useful. Then examine common designs, dependency direction, data flow, failure behavior, scaling implications, security considerations, observability requirements, and maintenance cost. Compare alternatives instead of assuming one pattern is universally correct. A production architecture is successful when it meets measurable requirements while remaining understandable and changeable.
Step 2
Example
Example: Design capacity planning for a production SaaS or e-commerce platform. Identify the actors, components, interfaces, data involved, normal request flow, failure flow, and operational signals. Compare at least two approaches and explain the trade-offs behind the selected design.
Step 3
Code
Code
Add implementation notes or a runnable example for this concept.
Step 4
Practice
Practice: Draw a detailed architecture diagram for capacity planning. Mark responsibilities, ownership, interfaces, dependencies, trust boundaries, failure boundaries, and monitoring signals. Write an architecture note explaining what would make you revisit the decision.
Step 5
Quiz
Quiz coming soon.
Step 6
Challenge
Challenge: Build a production-ready design around capacity planning. Include normal operation, failure handling, security controls, scaling behavior, observability, testing strategy, deployment concerns, and a safe migration or rollback path.
Complete every stage
Work through every step in order, then the lesson will be marked complete.
Each chapter and subtopic has its own public URL under /software-architecture.