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BE01-17 | Caching, Rate Limiting & Performance — What Interviewers Look For
Caching, rate limiting, and performance questions are where *system design interviews separate theoretical knowledge from real-world engineering judgment* .
In *Video* , we focus on how backend systems stay *fast, stable, and protected under real traffic* — and what interviewers are *actually* evaluating when they ask performance-related questions.
This video goes beyond “just add Redis” or “optimize later” and shows how to *reason about trade-offs* , protect systems from abuse, and maintain latency SLAs at scale.
### What you’ll learn in this video:
* What *performance really means* in system design interviews
* Why interviewers care about caching, rate limiting, and protection
* When caching helps — and when it hurts
* Different caching layers:
* Server-side caching (Redis, Memcached)
* HTTP / client-side caching
* CDN caching
* Cache invalidation strategies and why it’s a critical interview topic
* Common caching mistakes that kill interview answers
* Why rate limiting exists and what problems it solves
* High-level rate limiting strategies (fixed window, token bucket, leaky bucket)
* Where to apply rate limits in real systems
* Database performance pitfalls (indexes, N+1 queries, unbounded reads)
* Application-level performance techniques:
* Asynchronous processing
* Connection pooling
* Profiling and measurement
* The difference between *premature* and *strategic* optimization
* A reusable *interview answer framework* for performance questions
### Who this video is for:
* Backend engineers
* Software engineers preparing for *system design interviews*
* FAANG / Big Tech interview candidates
* Developers who want to understand *performance beyond buzzwords*
This video is designed for *deep understanding and interview confidence* , not memorizing patterns.
If this helped you:
* Like the video
* Drop your interview questions in the comments
* Subscribe for the next video on *Fault Tolerance, Reliability & Failure Handling*
---
This channel is about real-world software engineering — systems, backend, interviews, and intelligence explained.
Most tutorials teach tools.
Real engineering is about how systems work, scale, and fail in production.
In this video, I explain the topic from a systems-first perspective, connecting fundamentals, real-world usage, and how it appears in technical interviews.
This is not a course.
This is real engineering thinking.
If you're a developer, student, or interview candidate who wants to understand software deeply, consider subscribing.
Topics on this channel include backend engineering, system design, software engineering interviews, and engineering fundamentals.
— Danishan Farookh
#SoftwareEngineering #SystemDesign #BackendEngineering #TechInterviews
Видео BE01-17 | Caching, Rate Limiting & Performance — What Interviewers Look For канала danishan4u
In *Video* , we focus on how backend systems stay *fast, stable, and protected under real traffic* — and what interviewers are *actually* evaluating when they ask performance-related questions.
This video goes beyond “just add Redis” or “optimize later” and shows how to *reason about trade-offs* , protect systems from abuse, and maintain latency SLAs at scale.
### What you’ll learn in this video:
* What *performance really means* in system design interviews
* Why interviewers care about caching, rate limiting, and protection
* When caching helps — and when it hurts
* Different caching layers:
* Server-side caching (Redis, Memcached)
* HTTP / client-side caching
* CDN caching
* Cache invalidation strategies and why it’s a critical interview topic
* Common caching mistakes that kill interview answers
* Why rate limiting exists and what problems it solves
* High-level rate limiting strategies (fixed window, token bucket, leaky bucket)
* Where to apply rate limits in real systems
* Database performance pitfalls (indexes, N+1 queries, unbounded reads)
* Application-level performance techniques:
* Asynchronous processing
* Connection pooling
* Profiling and measurement
* The difference between *premature* and *strategic* optimization
* A reusable *interview answer framework* for performance questions
### Who this video is for:
* Backend engineers
* Software engineers preparing for *system design interviews*
* FAANG / Big Tech interview candidates
* Developers who want to understand *performance beyond buzzwords*
This video is designed for *deep understanding and interview confidence* , not memorizing patterns.
If this helped you:
* Like the video
* Drop your interview questions in the comments
* Subscribe for the next video on *Fault Tolerance, Reliability & Failure Handling*
---
This channel is about real-world software engineering — systems, backend, interviews, and intelligence explained.
Most tutorials teach tools.
Real engineering is about how systems work, scale, and fail in production.
In this video, I explain the topic from a systems-first perspective, connecting fundamentals, real-world usage, and how it appears in technical interviews.
This is not a course.
This is real engineering thinking.
If you're a developer, student, or interview candidate who wants to understand software deeply, consider subscribing.
Topics on this channel include backend engineering, system design, software engineering interviews, and engineering fundamentals.
— Danishan Farookh
#SoftwareEngineering #SystemDesign #BackendEngineering #TechInterviews
Видео BE01-17 | Caching, Rate Limiting & Performance — What Interviewers Look For канала danishan4u
danishan farookh danishan4u danishan system design system design interview backend performance caching strategies rate limiting redis caching memcached cdn caching http caching cache invalidation performance engineering faang system design api rate limiting token bucket leaky bucket fixed window rate limiting database performance n+1 query problem indexing database async processing connection pooling scalable backend systems interview preparation
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3 февраля 2026 г. 15:30:16
00:21:14
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