API Concurrent Request Handling - 搜索视频

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What is meant by the concurrent execution of database transacti... | Filo

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Throttling Patterns: How to handle thousands of concurrent requests

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10 Must-know best practices for optimizing API endpoints: • Pagination ↳ Break large datasets into smaller chunks with tools like limit and offset parameters. This improves performance and avoids crashing clients with oversized responses. Combine with cursors for better consistency in real-time data. • Cache ↳ Store frequently requested data at the client, server, or CDN level using caching headers or tools like Redis. This reduces response time and lightens backend load. Be mindful of stale dat

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Mr.K | Data Engineer on Instagram: "Follow @mrk_talkstech for more info #APIDevelopment #APIEngineering #BackendAPIs #RESTfulAPI #WebServices API design, REST API, HTTP methods, endpoints, request response, status codes, authentication, authorization, JWT, OAuth, API gateway, rate limiting, pagination, versioning, caching, error handling, OpenAPI, Swagger, GraphQL, gRPC"

Mr.K | Data Engineer on Instagram: "Follow @mrk_talkstech for more …

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Instagrammrk_talkstech

Ai Lead on Instagram: "How do APIs survive millions of requests? 🤯 🚀 Ever wondered how APIs handle millions of requests without crashing? 🤔 Rate limiting is the superhero here! 🦸‍♂️ It’s like a traffic cop for APIs, ensuring smooth flow and preventing overload. 🔑 Key Takeaways: 1️⃣ Token Bucket Algorithm: Think of a bucket with tokens. Each request consumes one token. No tokens? Request denied! 🚫 2️⃣ Redis Counters: Resetting counters every minute to manage traffic efficiently. 🕒 3️⃣ HTTP

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