Lessons from 72 Million API Calls (Don’t Make These Mistakes) | Push to Main! Meetup

This talk discusses building fast, scalable APIs. The speaker, a software engineer at Adyen, details challenges in handling millions of payment requests. Solutions include database and application-level optimizations, minimizing network latency by co-locating servers, and employing redundant systems to ensure high availability and minimal response times (e.g., 2.71ms average latency, 90% under 5ms). The key is minimizing network hops and optimizing database queries. The speaker clearly articulates the core challenge: building an API that can handle millions of requests while maintaining extremely fast response times. The segment underscores the importance of minimizing latency to prevent disruptions in the payment process.This segment identifies common problems encountered when building high-performance APIs, focusing on inefficient database queries, oversized payloads, and the impact of serialization/deserialization on response times. It sets the stage for discussing solutions to these challenges. The speaker presents practical database optimization strategies, including writing efficient queries, understanding data access patterns, leveraging primary key indexes, and employing caching mechanisms to reduce database calls and improve latency. The segment concludes with the impressive result of achieving an average query time of 12 milliseconds. This segment focuses on application-level optimizations. It emphasizes creating lean request/response objects, implementing fail-fast validations to reduce processing time in case of errors, and optimizing core business logic using efficient algorithms. The speaker stresses the importance of simplicity and purpose in code design. The speaker shifts the focus to deployment optimization, acknowledging that even with optimized database and application layers, network latency can significantly impact performance. This segment introduces the importance of system architecture and minimizing network communication delays.This segment details the system architecture employed to minimize network latency. It explains the strategy of collocating services and databases within the same data center to reduce communication overhead and improve response times. The speaker emphasizes the importance of redundancy and availability.The speaker presents the performance metrics achieved, showcasing the effectiveness of the optimization strategies. The segment highlights the impressive results: 72 million payment requests processed with an average latency of 2.71 milliseconds, 90% of responses under 5 milliseconds, and 99% under 10 milliseconds. The speaker concludes by reiterating the importance of the discussed optimization techniques. Need for Fast APIs: Fast APIs are crucial for applications like payment processing, where speed directly impacts user experience and prevents downstream system failures. Common API Challenges: Inefficient database queries and poorly optimized application logic are major performance bottlenecks. Database Optimization: Focus on efficient queries and data retrieval. Even small improvements yield significant performance gains. Application Layer Optimization: Streamline code, remove unnecessary computations, and ensure every line serves a purpose. Simple practices can dramatically improve speed. System Architecture Optimization: Co-locate services to minimize network latency. Deploy services within the same data center or even closer to reduce communication overhead. Performance Metrics: The presented system achieved 72 million payment requests with an average latency of 2.71 milliseconds, with 90% of responses under 5 milliseconds and 99% under 10 milliseconds. Redundancy ensures near-zero downtime. Key Takeaway: Building fast, scalable APIs requires a holistic approach, optimizing at the database, application, and system architecture levels. Minimizing network latency is paramount.