Performance Efficiency
Right-size compute for the actual load. Meet latency targets, scale gracefully, and avoid over-provisioning without compromising throughput.
Performance as a product quality
Users feel performance before they read architecture diagrams. This pillar makes latency, throughput, and scalability first-class design constraints.
Scale out and back based on real metrics, not peak-season assumptions that waste budget year-round.
Latency, throughput, and error budgets are explicit, measured, and owned by the team running the workload.
Caching, connection pooling, data locality, and async patterns reduce unnecessary compute and data movement.
What the Performance pillar covers
From architecture choices to continuous performance validation.
Define measurable targets for response time, throughput, and saturation — then validate them in production.
Horizontal scaling, load balancing, autoscaling, and queue-based decoupling for elastic demand.
Indexing, partitioning, caching, and tiering strategies that keep data access fast and cost-predictable.
Load, stress, and chaos tests that prove the architecture can handle expected and peak traffic.
Three levels of performance maturity
Progress from ad-hoc tuning to performance-aware product decisions.
Basic monitoring, defined SLOs, and documented scalability limits for each production workload.
Performance tests in CI/CD, autoscaling policies, and regular right-sizing reviews are standard practice.
Proactive capacity planning, cost-performance trade-off analysis, and continuous profiling guide architecture.
Design for performance
Read the full Performance Efficiency pillar documentation or run your first automated review with WAFPass.