What is it?
A cache stores frequently accessed data in fast memory (RAM) so applications can serve requests without hitting the slower database every time.
Why does it matter?
Caching is one of the highest-impact optimisations — adding Redis between your app and database can reduce latency from 100ms to 1ms for repeated queries.
Learn caching strategies — cache-aside, write-through, TTL, eviction policies, and Redis vs Memcached.
Real-World Use Cases
- 🏢 Enterprise systems - Used in large-scale systems.
- ⚡ Performance - Critical for high-traffic applications.
- 🎓 Interviews - Common system design interview topic.
- 🔧 Engineering - Core software engineering skill.
Core Concepts
# Caching: Speed Up Your Application 10x
# Learn caching strategies — cache-aside, write-through, TTL, eviction policies, and Redis vs Memcached.
# Key considerations:
# 1. Scalability
# 2. Reliability
# 3. Availability
# 4. PerformanceArchitecture Diagram
# A cache stores frequently accessed data in fast memory (RAM) so applications can serve requests without hitting the slower database every time.
# Common components:
# - Load Balancer -> App Servers
# - App Servers -> Cache (Redis)
# - App Servers -> Database (Primary + Replica)
# - CDN for static assetsTrade-offs and Decisions
# Design trade-offs:
# Consistency vs Availability (CAP Theorem)
# Latency vs Throughput
# Cost vs Performance
# Simplicity vs Scalability
# Scale estimates:
# DAU: 10M users
# Reads: 100K QPS
# Writes: 10K QPSQ: What are the most important system design interview topics?
The core topics: scalability (vertical vs horizontal), caching (Redis, Memcached), databases (SQL vs NoSQL, sharding), load balancers, message queues (Kafka, RabbitMQ), API design (REST, GraphQL), and the CAP theorem. For FAANG interviews, also know: consistent hashing, Bloom filters, and rate limiting.
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