Abstract: A server includes a data cache for storing data objects requested by mobile devices, desktop devices, and server devices, each of which may execute a different configuration of an application. When a cache miss occurs, the cache may begin loading portions of a requested data object from various data sources. The cache itself may be divided into multiple partitions, and each of the partitions may be assigned to a specific attribute, such as an application configuration. Portions of the data object may be loaded into corresponding cache partitions based on the attributes of each. Although part of a single cache, each of the partitions may be independently assigned different cache replacement policies. Performance metrics for each of the partitions may be monitored and used to update the cache replacement policy for each partition at runtime without interrupting response traffic.

Abstract: A server includes a data cache for storing data objects requested by users logged in under different user roles. Different user roles may have different permissions to access individual fields within a data object. When a cache miss occurs, the cache may begin loading portions of a requested data object from various data sources. Instead of waiting for the entire object to load to change the object state to “valid,” the cache may incrementally update the state through various levels of validity based on the user role of the request. When a portion of the data object used by a low-level user role is received, the object state can be upgraded to be valid for that user role while data for higher-level user roles continues to load. The portion of the data object can then be sent to the low-level user roles without waiting for the rest of the data object to load.

Abstract: A server includes a data cache for storing data objects requested by users logged in under different user roles. Different user roles may have different permissions to access individual fields within a data object. When a cache miss occurs, the cache may begin loading portions of a requested data object from various data sources. Instead of waiting for the entire object to load to change the object state to “valid,” the cache may incrementally update the state through various levels of validity based on the user role of the request. When a portion of the data object used by a low-level user role is received, the object state can be upgraded to be valid for that user role while data for higher-level user roles continues to load. The portion of the data object can then be sent to the low-level user roles without waiting for the rest of the data object to load.

Abstract: A messaging service may be distributed in a cluster of nodes such that each node includes an instance of the messaging service. To ensure that messages are not lost in the messaging service through a load balancer, addresses for each of the nodes may be accessed, and messages may be retrieved from individual instances of the messaging service by addressing the nodes directly and bypassing the load balancer. To retrieve messages, a client may cycle through the node addresses and retrieve messages until each corresponding message queue is empty. Once a message queue is empty, the client may stop sending requests to the corresponding node until the message queues on the other nodes have been emptied. Various request patterns may be used to cycle through node addresses, including Round Robin patterns and patterns that correspond to traffic patterns seen by the load balancer.

Abstract: A server includes a data cache for storing data objects requested by mobile devices, desktop devices, and server devices, each of which may execute a different configuration of an application. When a cache miss occurs, the cache may begin loading portions of a requested data object from various data sources. The cache itself may be divided into multiple partitions, and each of the partitions may be assigned to a specific attribute, such as an application configuration. Portions of the data object may be loaded into corresponding cache partitions based on the attributes of each. Although part of a single cache, each of the partitions may be independently assigned different cache replacement policies. Performance metrics for each of the partitions may be monitored and used to update the cache replacement policy for each partition at runtime without interrupting response traffic.