exa-load-scale

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Implement Exa load testing, capacity planning, and scaling strategies. Use when running performance tests, planning capacity for Exa integrations, or designing high-throughput search architectures. Trigger with phrases like "exa load test", "exa scale", "exa capacity", "exa k6", "exa benchmark", "exa throughput".

AI & Automation 2,266 stars 315 forks Updated today MIT

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# Exa Load & Scale ## Overview Load testing and capacity planning for Exa integrations. Key constraint: Exa's default rate limit is 10 QPS. Scaling strategies focus on caching, request queuing, parallel processing within rate limits, and search type selection for latency budgets. ## Prerequisites - k6 load testing tool installed - Test environment Exa API key (separate from production) - Redis for result caching ## Capacity Reference | Search Type | Typical Latency | Max Throughput (10 QPS) | |-------------|----------------|-------------------------| | `instant` | < 150ms | 10 req/s (600/min) | | `fast` | < 425ms | 10 req/s (600/min) | | `auto` | 300-1500ms | 10 req/s (600/min) | | `neural` | 500-2000ms | 10 req/s (600/min) | | `deep` | 2-5s | 10 req/s (600/min) | **With caching (50% hit rate):** Effective throughput doubles to 20 req/s equivalent. ## Instructions ### Step 1: k6 Load Test Against Your Wrapper ```javascript // exa-load-test.js import http from "k6/http"; import { check, sleep } from "k6"; export const options = { stages: [ { duration: "1m", target: 5 }, // Ramp up to 5 VUs { duration: "3m", target: 5 }, // Steady state { duration: "1m", target: 10 }, // Push toward rate limit { duration: "2m", target: 10 }, // Stress test { duration: "1m", target: 0 }, // Ramp down ], thresholds: { http_req_duration: ["p(95)<3000"], // 3s P95 for neural search http_req_failed: ["rate<0.05"], // < 5% error rate }, };...

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Author
jeremylongshore
Repository
jeremylongshore/claude-code-plugins-plus-skills
Created
7 months ago
Last Updated
today
Language
Python
License
MIT

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