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Coder System Design Perf Patterns
System-level performance pattern selection with measurable tradeoffs and SLO alignment. Use when this capability is needed.
tomevault-io
Updated Coder System Design Perf Patterns by tomevault-io · bf8e8b0
npx skillmds@latest add tomevault-io/coder-system-design-perf-patterns File contents
---name: coder-system-design-perf-patternsdescription: System-level performance pattern selection with measurable tradeoffs and SLO alignment. Use when this capability is needed.---<when_to_use> <trigger>Designing architecture under latency, throughput, or cost pressure</trigger> <trigger>Planning scaling strategy for growth or traffic spikes</trigger> <trigger>Reviewing performance bottlenecks and reliability tradeoffs</trigger></when_to_use><input_requirements> <required>Current bottleneck description and baseline metrics</required> <required>Target SLO/SLI and error budget constraints</required> <required>Traffic profile (steady, bursty, hot keys, read/write ratio)</required> <required>Operational constraints (cost, team capacity, infra limits)</required></input_requirements><pattern_catalog> <pattern>Cache-aside for read-heavy paths with tolerated staleness</pattern> <pattern>Queue-based load leveling for burst absorption</pattern> <pattern>Async processing for long-running tasks and user-facing responsiveness</pattern> <pattern>Batching to reduce per-operation overhead and network chatter</pattern> <pattern>Load shedding to protect core goodput under overload</pattern> <pattern>Horizontal scaling with autoscaling tied to meaningful saturation metrics</pattern> <pattern>Hotspot mitigation via key design and partition distribution</pattern></pattern_catalog><selection_rules> <rule importance="critical">Choose patterns from measured bottlenecks, not preference</rule> <rule importance="high">Define expected gain and rollback trigger before rollout</rule> <rule importance="high">Account for consistency, cost, and ops complexity tradeoffs</rule> <rule importance="high">Keep observability and SLO guardrails in same design package</rule></selection_rules><tradeoff_matrix> <item>Caching: lower latency, possible staleness and invalidation complexity</item> <item>Queues and async: smooth peaks, eventual consistency and replay complexity</item> <item>Batching: higher throughput, partial failure handling complexity</item> <item>Load shedding: preserves core capacity, intentional selective failures</item> <item>Horizontal scaling: capacity gain, bottleneck may shift to shared dependency</item></tradeoff_matrix><do_not> <item importance="critical">Do not scale on vanity metrics unrelated to user SLI</item> <item importance="high">Do not use unbounded retries/queues under overload</item> <item importance="high">Do not evaluate performance on averages only; include tail latency</item> <item importance="high">Do not ship performance changes without capacity and rollback plan</item></do_not><output_requirements> <requirement>Chosen pattern(s) with why-now rationale</requirement> <requirement>Expected SLI impact and acceptance thresholds</requirement> <requirement>Operational tradeoffs and failure modes</requirement> <requirement>Rollout, monitoring, and rollback plan</requirement></output_requirements><references> <source url="https://aws.amazon.com/builders-library/using-load-shedding-to-avoid-overload/">AWS Builders Library: Load Shedding</source> <source url="https://sre.google/sre-book/service-level-objectives/">Google SRE: Service Level Objectives</source> <source url="https://sre.google/workbook/alerting-on-slos/">Google SRE Workbook: Alerting on SLOs</source> <source url="https://sre.google/sre-book/addressing-cascading-failures/">Google SRE: Cascading Failures</source> <source url="https://learn.microsoft.com/en-us/azure/architecture/patterns/queue-based-load-leveling">Azure Queue-Based Load Leveling</source> <source url="https://kubernetes.io/docs/concepts/workloads/autoscaling/horizontal-pod-autoscale/">Kubernetes HPA</source> <source url="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-design.html">DynamoDB Partition Key Design</source></references>---> Converted and distributed by [TomeVault](https://tomevault.io/claim/ozerohax) — claim your Tome and manage your conversions.<!-- tomevault:4.0:skill_md:2026-04-11 -->
tomevault-io/skills-registry/tree/main/ozerohax--assistagents--perf-patterns commit bf8e8b0302
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System-level performance pattern selection with measurable tradeoffs and SLO alignment. Use when this capability is needed. It is listed under Coding & Dev Tools on SkillMD.
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