The difference between redis cache avalanche and cache breakdown

The difference between cache avalanche and breakdown: time of occurrence: avalanche is the failure of multiple caches at the same time, and breakdown is the failure of a single cache. Scope of impact: Avalanche affects all caches, breakdown only affects a single hotspot data. Cause: Avalanches are caused by improper expiration policies, and breakdowns are caused by cache penetration or hotspot data not being cached. Impact: Avalanches may cause service unavailability, breakdowns will not. Countermeasures: Optimizing the expiration strategy and progressive expiration can deal with avalanches, and mutex locks and current limiting mechanisms can deal with breakdown.

The difference between Redis cache avalanche and cache breakdown

Cache avalanche and cache breakdown are both common in Redis cache performance issues, but there are essential differences between them.

Cache avalanche

• Definition: A large number of caches fail at the same time, causing all requests to fall to the back-end database, causing pressure on the back-end database is too big.
• Cause: Improper cache expiration strategy caused a large number of caches to expire at the same time.
• Impact: In extreme cases, the service may be unavailable.

Cache breakdown

• Definition: After a certain cache fails, a large number of requests access the cache at the same time, resulting in The pressure on the end database is too high.
• Cause: There is no cache of hotspot data in the cache, or cache penetration causes the hotspot data to not be cached.
• Impact: Affects single hotspot data access, but will not cause service unavailability.

Difference

Features	Cache Avalanche	Cache Breakdown
Occurrence time	Multiple caches invalidated at the same time	Single cache invalidated
Scope of impact	Affects all caches	Only affects a single hotspot data
Cause reason	Improper cache expiration policy	Cache penetration or hotspot data is not cached
Degree of impact	May cause service unavailability	Does not affect service availability
Countermeasures	Optimize cache expiration strategy, use progressive expiration	Use mutex lock or current limiting mechanism

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