System Design Fundamentals
System design turns product requirements into a workable plan for components, data, communication, capacity, and failure handling. It helps you explain why a design fits a workload and which trade-offs it makes.
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Don't Panic
Don't Panic - System Design Fundamentals
System Design Fundamentals is the subject of this course. System design is the work of turning a problem into a technical plan that can be built, operated, and changed. You identify requirements, shape the major components, trace data and requests, and make trade-offs explicit.
The useful unit of work is a closed loop: clarify the goal and boundaries, gather the inputs the practice requires, make the decision or change, record evidence, and return with owners for the next cycle. Skipping any link leaves teams busy without durable results.
Tooling supports the loop; it does not replace it. Choose tools after the boundary and evidence model are clear. Comparing products without that model produces feature matrices that do not change how the work runs.
Common failure modes include undefined ownership, metrics that count activity instead of outcomes, and irreversible steps taken without a review path. Treat those as design defects in the practice, not as individual heroics to compensate later.
Operators should be able to explain which signals would change a decision this week. If no signal can change the plan, the practice has become ritual. Keep the feedback path short enough that evidence still influences the next cycle.
Name the owners for each stage of the loop before the work scales. Unowned stages become permanent exceptions. Record decisions with enough context that a future operator can tell why a tradeoff was accepted. Prefer fewer, sharper metrics that change behavior over broad dashboards that only describe activity after the fact.
Read the Intro for the core model. Use the Cheatsheet when you need the operating map. Updates tracks official guidance when this course configures an update source; otherwise the practice is settled without a live feed.
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Sources
- https://learn.microsoft.com/en-us/azure/architecture/guide/design-principles/build-for-business
Supports
- Requirements and business needs before architecture choices
- Different flows having different availability, scalability, consistency, and recovery needs
- Measurable objectives informing architecture decisions
- Quiz answer about requirement-first design
- https://learn.microsoft.com/en-us/azure/architecture/guide/design-principles/scale-out
Supports
- Horizontal scaling with interchangeable instances
- Session affinity and local state as scaling constraints
- Bottleneck identification before adding capacity
- Asynchronous messaging, flow control, queue buffering, and independent scaling
- Scaling in and transient-fault handling
- Quiz answers about estimates and horizontal scaling
- https://learn.microsoft.com/en-us/azure/architecture/guide/architecture-styles/
Supports
- Architecture styles selected from business and quality requirements
- Trade-offs of synchronous communication and asynchronous messaging
- Eventual consistency and duplicate-message concerns
- Communication, latency, complexity, and manageability costs
- https://learn.microsoft.com/en-us/azure/architecture/guide/design-principles/make-all-things-redundant
Supports
- Redundancy to avoid single points of failure
- Replicas and multiple instances as redundancy mechanisms
- Redundancy choices driven by requirements and cost
- Quiz answer about replication and freshness decisions
- https://docs.aws.amazon.com/wellarchitected/latest/framework/rel-05.html
Supports
- Network latency and loss in distributed interactions
- Graceful degradation, throttling, controlled retries, limited queues, and timeouts
- Stateless design where practical
- Quiz answers about bounded queues and retry amplification
- https://sre.google/sre-book/service-level-objectives/
Supports
- SLI and SLO definitions
- Latency, error rate, throughput, availability, durability, and correctness indicators
- User-relevant measurement
- Percentiles exposing tail latency hidden by averages
- Measurement windows and workload classes
- Quiz answer about latency percentiles
- https://sre.google/sre-book/service-best-practices/
Supports
- User-focused service objectives
- Monitoring and error budgets
- Production readiness and evidence
- Quiz answer about revising assumptions from test evidence
- https://www.rfc-editor.org/rfc/rfc9110
Supports
- Safe and idempotent HTTP method semantics
- Automatic retry constraints for non-idempotent requests
- Repeated operations and quiz answer about idempotency
- https://www.rfc-editor.org/rfc/rfc9111
Supports
- HTTP cache storage and reuse
- Freshness, staleness, validation, and invalidation semantics
- Quiz answer about complete cache design
- https://github.com/sindresorhus/awesome
Supports
- Discovery of the Awesome Testing list and listed load-testing tools
- Discovery decision for k6, Apache JMeter, and Gatling
- https://github.com/TheJambo/awesome-testing
Supports
- Inclusion of k6, Apache JMeter, and Gatling as performance or load-testing tools
- https://grafana.com/docs/k6/latest/
Supports
- k6 as a scriptable load and performance testing tool
- Test authoring, execution, results, and performance-testing concepts
- Awesome Links rationale for k6
- https://jmeter.apache.org/usermanual/
Supports
- Test plans, thread groups, samplers, assertions, and CLI execution
- Load-test reporting and broad protocol support
- Awesome Links rationale for Apache JMeter
- https://docs.gatling.io/
Supports
- Code-driven load testing and supported SDK languages
- Virtual users, load models, protocols, metrics, and automation
- Awesome Links rationale for Gatling
