![]() In this article, we’ll explain what cache-control is and how it affects behavior on your website. That sounds a little complicated – we know! So if you bear with us, we’ll dig into the topic of cache-control in much greater detail. In a nutshell, cache-control is an HTTP header that specifies browser caching policies for certain static resources on your website, such as your images. For more information on cache metrics such as used_memory and used_memory_rss, see Create your own metrics.Confused by what the cache-control HTTP header is and how it works with your WordPress site? Eviction can increase server load and memory fragmentation. ![]() If either your current used_memory or your used_memory_rss values are higher than the new limit of 45 GB, then the system must evict data until both used_memory and used_memory_rss are below 45 GB. For instance, if you have a 53-GB cache with 49 GB of data and then change the reservation value to 8 GB, the max available memory for the system will drop to 45 GB. One thing to consider when choosing a new memory reservation value ( maxmemory-reserved or maxfragmentationmemory-reserved) is how this change might affect a cache with large amounts of data in it that is already running. ![]() If you try to set these values lower than 10% or higher than 60%, they are re-evaluated and set to the 10% minimum and 60% maximum. The allowed range for maxfragmentationmemory-reserved is 10% - 60% of maxmemory. When memory is reserved for such operations, it's unavailable for storage of cached data. When you set this value, the Redis server experience is more consistent when the cache is full or close to full and the fragmentation ratio is high. The maxfragmentationmemory-reserved setting configures the amount of memory, in MB per instance in a cluster, that is reserved to accommodate for memory fragmentation. The allowed range for maxmemory-reserved is 10% - 60% of maxmemory. This value should be set higher for workloads that write large amounts of data. Setting this value allows you to have a more consistent Redis server experience when your load varies. The maxmemory-reserved setting configures the amount of memory, in MB per instance in a cluster, that is reserved for non-cache operations, such as replication during failover. You can increase the amount reserved if you have write-heavy loads. Another 10% is reserved for maxfragmentationmemory-reserved. By default when you create a cache, approximately 10% of the available memory is reserved for maxmemory-reserved. Configure your maxmemory-reserved settingĬonfigure your maxmemory-reserved setting to improve system responsiveness:Ī sufficient reservation setting is especially important for write-heavy workloads or if you're storing values of 100 KB or more in your cache. Monitor memory usageĪdd monitoring on memory usage to ensure that you don't run out of memory and have the chance to scale your cache before seeing issues. Large values can leave memory fragmented on eviction and might lead to high memory usage and server load. For more information, see the documentation for the EXPIRE and EXPIREAT commands. When eviction happens because of memory pressure, it can cause more load on your server. An expiration removes keys proactively instead of waiting until there's memory pressure. If you want the system to allow any key to be evicted if under memory pressure, then you may want to consider the allkeys-lru policy. If no keys have a TTL value, then the system won't evict any keys. The default policy for Azure Cache for Redis is volatile-lru, which means that only keys that have a TTL value set with a command like EXPIRE are eligible for eviction. Choose an eviction policy that works for your application.
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