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.
Demand-driven scaling
Scale out and back based on real metrics, not peak-season assumptions that waste budget year-round.
Defined targets
Latency, throughput, and error budgets are explicit, measured, and owned by the team running the workload.
Efficient architecture
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.
SLOs & latency budgets
Define measurable targets for response time, throughput, and saturation — then validate them in production.
Scalability patterns
Horizontal scaling, load balancing, autoscaling, and queue-based decoupling for elastic demand.
Data efficiency
Indexing, partitioning, caching, and tiering strategies that keep data access fast and cost-predictable.
Performance testing
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.
Baseline
Basic monitoring, defined SLOs, and documented scalability limits for each production workload.
Standardize
Performance tests in CI/CD, autoscaling policies, and regular right-sizing reviews are standard practice.
Optimize
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 WOMBATpass.