# The algo records whose force is performance_scaling

This index as JSON: https://banes-lab.com/json/api/facets/algo/force/performance-scaling

## Entries

- [Adaptive Phase Boundary](https://banes-lab.com/records/algo/adaptive-phase-boundary.md): Select phase count from risk and complexity, assign phase boundaries, and strengthen validation density for high-risk or high-complexity domains.
- [Performance and Scalability](https://banes-lab.com/records/algo/performance-and-scalability.md): Establish workload model, profile runtime behavior, benchmark repeatably, identify bottlenecks, analyze time and space complexity, select scaling strategy, optimize only measured bottlenecks, and enforce SLO gates.
- [Performance Scaling](https://banes-lab.com/records/algo/performance-scaling.md): Measure workload, identify bottlenecks, choose vertical or horizontal scaling, partition load, cache safe data, enforce rate limits, and benchmark continuously.
- [Breaking Point Calculation](https://banes-lab.com/records/algo/breaking-point-calculation.md): Measure current item count, estimate growth rate, compare against cognitive and maintenance limits, compute time or units until threshold breach, and assign severity.
- [Scalability Projection](https://banes-lab.com/records/algo/scalability-projection.md): Measure current resource counts, project tenfold and hundredfold growth, assess manual maintenance feasibility, and identify where dynamic discovery becomes necessary.
- [Performance-Aware Discovery Design](https://banes-lab.com/records/algo/performance-aware-discovery-design.md): Estimate discovery and loading cost, compare large-scale cost against performance targets, introduce caching only when justified, and record failure modes.
- [Measured-vs-Estimated Validation](https://banes-lab.com/records/algo/measured-vs-estimated-validation.md): Run validation when execution is available; otherwise estimate from static evidence, label the result as estimated, and never report estimated performance as measured.
- [Knowledge Capture](https://banes-lab.com/records/algo/knowledge-capture.md): Load or initialize the automation knowledge base, merge new detections, conventions, scalability concerns, architecture designs, migration history, and validation outcomes, then persist when capability exists.
- [Automation Session Report](https://banes-lab.com/records/algo/automation-session-report.md): Summarize detected patterns, convention readiness, scalability pressure, dynamic architecture, generated artifacts, implementation status, measured versus estimated validation, and limitations.
- [Automation Kernel](https://banes-lab.com/records/algo/automation-kernel.md): Load configuration, verify capabilities, initialize knowledge, detect static patterns, classify automation opportunity, analyze conventions, assess scale and performance, design dynamic architecture, optionally implement, validate, update knowledge, and report.
- [<Automation Concern>](https://banes-lab.com/records/algo/automation-concern.md): <Detect static coordination point> → <Classify intentional vs problematic> → <Measure scale pressure> → <Verify convention strength> → <Design dynamic contract> → <Preserve fallback> → <Validate performance and architecture> → <Capture knowledge>
- [Cross-Cutting Surface Coverage](https://banes-lab.com/records/algo/cross-cutting-surface-coverage.md): Gate the software surface beyond structure — security, performance, infrastructure and deployment, and resilience — so a change's threat, budget, config, and failure consequences are covered, not only its structural ones.
- [Token Source-of-Truth](https://banes-lab.com/records/algo/token-source-of-truth.md): Define every design primitive — color, space, radius, the type scale, size, duration, z-index — exactly once as a custom property in the tokens layer, and forbid any downstream literal where a token exists.
- [Semantic Domain Partitioning](https://banes-lab.com/records/algo/semantic-domain-partitioning.md): Group implementation resources by semantic role, such as manager, repository, handler, service, controller, adapter, or worker, then analyze each family separately.