Multi-level caching in HLD - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is multi-level caching in system design?

Multi-level caching is a technique where multiple cache layers are used to store data closer to the user or application, improving speed and reducing load on the main data source.

beginner

Name the common cache levels used in multi-level caching.

Typical cache levels include: 1) L1 cache - closest and fastest (e.g., in-memory cache), 2) L2 cache - slower but larger (e.g., distributed cache), 3) Backend storage - slowest but persistent (e.g., database).

intermediate

Why is multi-level caching more scalable than single-level caching?

Because it reduces the load on backend systems by serving requests from faster, closer caches first, and spreads cache storage across different layers, improving response time and system scalability.

beginner

What is a cache miss in multi-level caching?

A cache miss occurs when data is not found in a cache layer, causing the system to check the next cache level or the main data source until the data is found or fetched.

advanced

How does cache coherence affect multi-level caching?

Cache coherence ensures that all cache layers have consistent and up-to-date data, preventing stale or conflicting information from being served to users.

Which cache level is typically the fastest in multi-level caching?

A Database

B In-memory cache (L1)

C Distributed cache (L2)

D Disk storage

The in-memory cache (L1) is closest to the application and fastest to access.

What happens when data is not found in any cache level?

A The system fetches data from the main data source

B The system returns an error

C The system creates new data

D The system clears all caches

On a cache miss at all levels, the system fetches data from the main data source like a database.

Why use multi-level caching instead of a single cache?

A To avoid using databases

B To increase data redundancy

C To reduce network traffic only

D To improve performance and scalability by layering caches

Multi-level caching improves performance and scalability by serving data from multiple cache layers.

Which problem does cache coherence address in multi-level caching?

A Data inconsistency between cache layers

B Cache eviction policies

C Cache size limits

D Data duplication

Cache coherence ensures data consistency across different cache layers.

What is a common strategy to keep multi-level caches updated?

A Ignoring updates

B Manual cache clearing

C Write-through or write-back policies

D Disabling cache

Write-through and write-back policies help keep caches updated and consistent.

Explain the concept of multi-level caching and why it is used in system design.

Think about how data is stored closer to the user in layers.

Describe how cache coherence is maintained in a multi-level caching system.

Consider how updates propagate through cache layers.