Posts tagged

Performance

API Analytics: Measuring Performance and Usage for Continuous Improvement

Teaches how to instrument a Flask API to collect key performance metrics: response time via before/after request hooks, throughput and error rates using Prometheus counters and histograms, and per-client usage tracked by API key. Walks through setting up the full Prometheus and Grafana stack with Docker, exposing a /metrics endpoint, and building dashboards. Also covers centralized log analysis with the ELK Stack and AWS CloudWatch as complementary approaches to understanding API health over time.

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Optimizing API Performance: Caching, Rate Limiting, and Response Time Improvements

Demonstrates three concrete ways to speed up a Flask API and protect it under load. Server-side caching with Flask-Caching stores endpoint responses for a configurable TTL so repeated calls skip the slow work. Rate limiting via Flask-Limiter caps requests per client IP and returns a 429 with a custom error body when the limit is exceeded. Database query optimization covers adding SQL indexes and avoiding SELECT * to reduce query time. Also shows NGINX-level caching as a network-layer complement to application caching, and pagination to avoid fetching oversized result sets.

programming python apis
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