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of 22What is caching and why is it important in software systems?
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Caching is a technique that stores frequently accessed data in a fast-access storage layer (cache) to reduce the time needed to retrieve that data from slower storage systems. It acts as a temporary storage between the application and the data source.
Key benefits:
- Performance improvement: Reduces latency by serving data from faster storage
- Reduced load: Decreases burden on databases and external services
- Cost efficiency: Reduces expensive database queries and API calls
- Better user experience: Faster response times improve application responsiveness
Example: Instead of querying a database every time for user profile data, cache it in memory for quick access.
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Explain cache hit and cache miss. What is cache hit ratio?
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- Cache Hit: When requested data is found in the cache and can be served directly
- Cache Miss: When requested data is not in the cache, requiring retrieval from the original source
- Cache Hit Ratio: Percentage of requests served from cache vs total requests
Formula: Cache Hit Ratio = (Cache Hits / Total Requests) × 100
Example: If 80 out of 100 requests are served from cache, the hit ratio is 80%. Higher ratios indicate better cache effectiveness.
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What are the different levels of caching in a typical web application?
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Browser Cache: Stores static resources (CSS, JS, images) on client-side
CDN Cache: Geographically distributed cache for static content
Reverse Proxy Cache: Server-side cache (e.g., Nginx, Varnish)
Application Cache: In-memory cache within the application
Database Cache: Query result caching at database level
Example flow: Request → Browser Cache → CDN → Reverse Proxy → Application Cache → Database Cache → Database
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Compare Cache-Aside, Write-Through, and Write-Behind caching patterns.
What is the difference between local cache and distributed cache?
Explain Read-Through and Write-Through caching strategies.
What are the most common cache eviction policies? When would you use each?
How would you implement an LRU cache?
What is cache warming and when is it beneficial?
What are the challenges of distributed caching and how do you address them?
How do you monitor and measure cache performance?
What factors affect cache performance and how do you optimize them?
When would you choose Redis over Memcached?
Explain consistent hashing in the context of distributed caching.
What is the cache stampede problem and how can you prevent it?
Explain cache coherence in multi-level caching systems.
What are cache partitioning strategies and their trade-offs?
How do you handle cache security and prevent cache-based attacks?
What is multi-level caching and when would you implement it?
Explain cache compression techniques and their trade-offs.
How do you implement cache invalidation in a microservices architecture?
What are the considerations for caching in containerized and cloud environments?
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