Throttling: Request Rate Control
Every production API eventually faces the same problem: too many requests, not enough capacity. Maybe it’s a legitimate traffic spike, a misbehaving client, or a deliberate attack. Without…
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System Design: Rate Limiting Algorithms (Token Bucket, Leaky Bucket)
Rate limiting is your first line of defense against both malicious actors and well-intentioned clients that accidentally hammer your API. Without it, a single misbehaving client can degrade service…
Read more →Spark Streaming - Rate Source for Testing
The rate source is a built-in streaming source in Spark Structured Streaming that generates rows at a specified rate. Unlike file-based or socket sources, it requires no external setup and produces…
Read more →Rate Limiting: Protecting Against Brute Force
Every exposed endpoint is a target. Login forms get hammered with credential stuffing attacks using billions of leaked username/password combinations. APIs face enumeration attacks probing for valid…
Read more →How to Use Learning Rate Schedulers in PyTorch
A fixed learning rate is a compromise. Set it too high and your loss oscillates wildly, never settling into a good minimum. Set it too low and training crawls along, wasting GPU hours. Learning rate…
Read more →Go Rate Limiting: Token Bucket Implementation
Rate limiting is non-negotiable for production systems. Without it, a single misbehaving client can exhaust your resources, a sudden traffic spike can cascade failures through your infrastructure,…
Read more →Design a Rate Limiter: API Throttling System
Every production API needs rate limiting. Without it, a single misbehaving client can exhaust your database connections, a bot can scrape your entire catalog in minutes, or a DDoS attack can bankrupt…
Read more →Deep Learning: Learning Rate Scheduling Explained
The learning rate is the single most important hyperparameter in neural network training. It controls how much we adjust weights in response to the estimated error gradient. Set it too high, and your…
Read more →API Rate Limiting: Implementation Strategies
Rate limiting protects your API from abuse, ensures fair resource distribution among users, and controls infrastructure costs. Without it, a single misbehaving client can overwhelm your servers,…
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