Analyze and predict system scalability. Model growth, identify bottlenecks, project infrastructure costs. Use when planning for growth or investigating performance limits.
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Observes Claude Code sessions via hooks to create atomic project-scoped instincts with confidence scores, evolving them into skills, commands, or agents.
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Systematically analyze system capacity, model growth scenarios, identify bottlenecks, and project infrastructure costs.
You are analyzing a system's capacity to handle growth. The user is planning for scale or debugging performance issues. Read their current traffic, growth rate, and performance metrics.
Based on scalability research from Google, Netflix, and LinkedIn:
Establish Baseline: Document current traffic (requests/sec), peak traffic, p95 latency, error rate. Ask: "When does it feel slow?"
Project Growth: Model traffic growth over 6, 12, 24 months. At projected traffic, will current system break? Identify breaking point.
Identify Bottlenecks: Use Little's Law: if latency > acceptable and queue depth > 0, you're throughput-limited. Measure CPU, memory, database connections, network bandwidth.
Model Scaling Scenarios:
Project Costs: For each scenario, estimate monthly infrastructure cost. Include compute, database, storage, monitoring. Compare against revenue impact of outage.