What are common mistakes in using distributed cache?
An example of an AI chatbot conversation about common mistakes in distributed caching.
What are common mistakes in using distributed cache?
Some common mistakes include not considering data consistency, overloading the cache, and ignoring cache eviction policies.
Can you explain why data consistency is important?
Data consistency ensures that all users see the same data at the same time, which is crucial for applications that rely on accurate information.
What happens if I overload the cache?
Overloading the cache can lead to performance degradation, increased latency, and even cache misses, which defeats the purpose of using a cache.
How can I avoid these mistakes?
To avoid these mistakes, implement proper cache management strategies, monitor performance, and regularly review your caching policies.
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