A method includes determining to move an extent from a source-tier in a storage system to a destination-tier in the storage system, wherein a set of tracks of the extent is presently being accessed. In response to determining that a parameter of the extent exceeds a migration threshold, a destination-tier cache is populated with tracks as they are removed from a read-stack associated with the source-tier and/or a write-stack associated with the source-tier using a predetermined read-to-write ratio.

To deliver up-to-date, coherent user data to applications upon request, the disclosed technology includes systems and methods for caching data and metadata after it has been synchronously loaded—for future retrieval with a page load time close to zero milliseconds. To provide this experience, data needs to be stored as locally to a user as possible, in the cache on the local device or in an edge cache located geographically nearby, for use in responding to requests. Applications which maintain caches of API results can be notified of their invalidation, and can detect the invalidation, propagate the invalidation to any further client tiers with the appropriate derivative type mapping, and refresh their cached values so that clients need not synchronously make the API requests again—insuring that the client has access to the most up-to-date copy of data as inexpensively as possible—in terms of bandwidth and latency.

A method, system, and program product for implementing intelligent cache preloading is provided. The method includes monitoring current usage of a system of record (SOR) system. Historical data associated with historical usage of the SOR system is retrieved and analyzed based on the current usage. A ranked list of data items configured to be loaded within a cache structure of the cache system is generated and currently requested data items from the SOR system are loaded into the cache structure via a throttling process. A malfunction associated with operation of the SOR system is detected and access to the currently requested data items is enabled. The currently requested data items are organized within the cache structure in accordance with an order of the ranked list and access to the currently requested data items is enabled, during the malfunction, in accordance with the order of the ranked list.

A multi-tenant, elastically scalable cache as a service is disclosed. Embodiments of the cache service eliminate the need for applications to manage their own cache tier. The multi-tenant cache service is implemented by maintaining/creating multiple named caches in a cache cluster and mapping each tenant's cache to a named cache in the cluster. Strict quotas are enforced on cache sizes This allows caches with different replication attributes to co-exist on the same cache server, allows migration of a cache from one cluster to another for load balancing purposes, and allows a cache to inflate/deflate to meet business needs. A network load balancer is used to route cache items to servers.

To deliver up-to-date, coherent user data to applications upon request, the disclosed technology includes systems and methods for caching data and metadata after it has been synchronously loaded—for future retrieval with a page load time close to zero milliseconds. To provide this experience, data needs to be stored as locally to a user as possible, in the cache on the local device or in an edge cache located geographically nearby, for use in responding to requests. Applications which maintain caches of API results can be notified of their invalidation, and can detect the invalidation, propagate the invalidation to any further client tiers with the appropriate derivative type mapping, and refresh their cached values so that clients need not synchronously make the API requests again—ensuring that the client has access to the most up-to-date copy of data as inexpensively as possible in terms of bandwidth and latency.

A method for demoting a selected storage element from a cache memory includes storing favored and non-favored storage elements within a higher performance portion and lower performance portion of the cache memory. The method maintains a plurality of favored LRU lists and a non-favored LRU list for the higher and lower performance portions of the cache memory. Each favored LRU list contains entries associated with the favored storage elements that have the same unique residency multiplier. The non-favored LRU list includes entries associated with the non-favored storage elements. The method demotes a selected favored or non-favored storage element from the higher and lower performance portions of the cache memory according to a cache demotion policy that provides a preference to favored storage elements over non-favored storage elements based on a computed cache life expectancy, residency time, and the unique residency multiplier. A corresponding storage controller and computer program product are also disclosed.

A method for demoting a selected storage element from a cache memory includes storing favored and non-favored storage elements within a higher performance portion and lower performance portion of the cache memory. The favored storage elements are retained in the cache memory longer than the non-favored storage elements. The method maintains a first favored LRU list and a first non-favored LRU list, associated with the favored and non-favored storage elements stored within the higher performance portion of the cache. The method selects a favored or non-favored storage element to be demoted from the higher performance portion of the cache memory according to life expectancy and residency of the oldest favored and non-favored storage elements in the first LRU lists. The method demotes the selected from the higher performance portion of the cache to the lower performance portion of the cache, or to the data storage devices, according to a cache demotion policy. A corresponding storage controller and computer program product are also disclosed.

Embodiments of the present disclosure provide a method, device, and computer program product for managing cache. There is provided a method of managing a cache, comprising: receiving a current operation request from a user, data requested by the current operation request being to be duplicated to the cache; obtaining a plurality of historical operation requests of the user, the plurality of historical operation requests being received prior to the current operation request; determining a predicted operation request for the user based on the plurality of historical operation requests and the current operation request; and in accordance with determining that a type of an operation associated with the predicted operation request belongs to predetermined types, adjusting data in the cache based on the predicted operation request. With the embodiments of the present disclosure, it can be determined dynamically and intelligently which data should be cached, the speed of processing user's operation requests can be increased, and the memory space occupied by the cache can be reduced, thereby improving the system performance.

A data storage array is configured for m-way resiliency across a first plurality of storage nodes. The m-way resiliency causes the data storage array to direct each top-level write to at least m storage nodes within the first plurality, for committing data to a corresponding capacity region allocated on each storage node to which each write operation is directed. Based on the data storage array being configured for m-way resiliency, an extra-resilient cache is allocated across a second plurality of storage nodes comprising at least s storage nodes (where s>m), including allocating a corresponding cache region on each of the second plurality for use by the extra-resilient cache. Based on determining that a particular top-level write has not been acknowledged by at least n of the first plurality of storage nodes (where n≤m), the particular top-level write is redirected to the extra-resilient cache.

A content delivery network may provide content items to requesting devices using a popularity-based distribution hierarchy. A central analysis system may determine popularity data for a content item stored in a first caching device. The central analysis system may determine that a change in the popularity data is beyond a threshold value. The central analysis system may then transmit an instruction to move the content item from the first caching device to a second caching device in a different tier of caching devices than the first caching device. The central analysis system may update a content index to indicate that the content item has been moved to the second caching device. A user device may be redirected to request the content item directly from the second caching device.