If you’ve implemented a cache, message broker, or any other data use case that prioritizes speed, chances are you’ve used Redis. Redis has been the most popular in-memory data store for the past decade and for good reason; it’s built to handle these types of use cases. However, if you are operating a Redis instance, you should be aware of the most common points of failure, most of which are a result of its single-threaded design.
If your Redis instance completely fails, or just becomes temporarily unavailable, data loss is likely to occur, as new data can’t be written during these periods. If you're using Redis as a cache, the result will be poor user performance and potentially a temporary outage. However, if you’re using Redis as a primary datastore, then you could suffer partial data loss. Even worse, you could end up losing your entire dataset if the Redis issue affects its ability to take proper snapshots, or if the snapshots get corrupted.