High-Performance API Backend Development
Ali Shan
Process
The Challenge: "The application needed to process thousands of SEO data points (or voice generation requests) simultaneously without crashing. We faced issues with API rate limiting and slow database queries on the legacy system." The Solution: "Designed and deployed a Node.js/Express (or Python/Django) backend with a microservices architecture." "Implemented Redis Caching to reduce database load and cut API response time by 60%." "Integrated OpenAI/LLM APIs with a custom queuing system (BullMQ/RabbitMQ) to handle AI generation tasks asynchronously, preventing timeouts." "Optimized PostgreSQL queries and set up proper indexing for faster data retrieval." The Outcome: "Achieved 99.9% uptime during peak loads and successfully handled 10,000+ daily API requests securely."
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Posted Dec 22, 2025
Developed a robust backend to handle high-load API requests efficiently.
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