Abstract: A system and method can support resettable acknowledgements for synchronizing data between clusters in a distributed data grid. The system can use one or more unique identifiers (IDs) to support message passing between different clusters in the distributed data grid. A first cluster can receive a first replication message from a second cluster, wherein the replication message indicates that the replication message is from a new cluster. Then, the system can reset the first cluster to preserve idempotence in possessing one or more replication messages that are received from the second cluster, following the first replication message.

Abstract: A system and method can support partition level journaling for synchronizing data between clusters in a distributed data grid. The system can associate a journal cache with one or more user caches in a local cluster, wherein said one or more user caches are split into a plurality of partitions. Furthermore, the system can capture one or more data changes that are applied to different partitions of said one or more user caches, and can store said one or more data changes in the journal cache that supports synchronization with remote clusters.

Abstract: A system and method can support failover during synchronization between autonomous clusters in a distributed data grid. The system allows a cluster member in a source cluster to take over as an owner of a partition in a source cluster, when another cluster member in the source cluster becomes unavailable. Then, a cluster member in the destination cluster can receive one or more replication messages from said cluster member in the source cluster, wherein said one or more replication messages include one or more data changes. Furthermore, the cluster member in the destination cluster may ignore said one or more replication messages, if said one or more replication messages have already been received and successfully processed in the destination cluster.

Abstract: A system and method can support parallel asynchronous synchronization between autonomous clusters in a distributed data grid. The system can track one or more data changes, which are applied on one or more user caches in a source cluster, at a partition level. Furthermore, one or more cluster members in the source cluster can send one or more replication messages to one or more destination clusters, wherein said one or more replication messages include the one or more data changes. Then, the one or more destination clusters can process the received one or more data changes.

Abstract: A system and method can support failover during synchronization between autonomous clusters in a distributed data grid. The system allows a cluster member in a source cluster to take over as an owner of a partition in a source cluster, when another cluster member in the source cluster becomes unavailable. Then, a cluster member in the destination cluster can receive one or more replication messages from said cluster member in the source cluster, wherein said one or more replication messages include one or more data changes. Furthermore, the cluster member in the destination cluster may ignore said one or more replication messages, if said one or more replication messages have already been received and successfully processed in the destination cluster.

Abstract: A system and method can support resettable acknowledgements for synchronizing data between clusters in a distributed data grid. The system can use one or more unique identifiers (IDs) to support message passing between different clusters in the distributed data grid. A first cluster can receive a first replication message from a second cluster, wherein the replication message indicates that the replication message is from a new cluster. Then, the system can reset the first cluster to preserve idempotence in possessing one or more replication messages that are received from the second cluster, following the first replication message.

Abstract: A system and method can support parallel asynchronous synchronization between autonomous clusters in a distributed data grid. The system can track one or more data changes, which are applied on one or more user caches in a source cluster, at a partition level. Furthermore, one or more cluster members in the source cluster can send one or more replication messages to one or more destination clusters, wherein said one or more replication messages include the one or more data changes. Then, the one or more destination clusters can process the received one or more data changes.

Abstract: A system and method can support partition level journaling for synchronizing data between clusters in a distributed data grid. The system can associate a journal cache with one or more user caches in a local cluster, wherein said one or more user caches are split into a plurality of partitions. Furthermore, the system can capture one or more data changes that are applied to different partitions of said one or more user caches, and can store said one or more data changes in the journal cache that supports synchronization with remote clusters.

Abstract: On a computer cluster, a distributed object, called a console, manages all interactions with users and manages error reporting. The console provides a simple synchronous call interface that does not use any network semantics. This allows all layers of the software to use the console. User interaction and error reporting is enhanced by an error stack, included in the console. The error stack can be maintained on a per client context basis. When an error occurs, each layer of software can add details to the error stack. The result is the relaying meaningful error messages to the user.

Abstract: A method and apparatus for configuring a software application on a cluster is provided. A configuration coordinator executing on a configuration manager communicates with one or more configuration slaves executing on a set of nodes that are operating as a cluster. The configuration coordinator sends messages to the one or more configuration slaves to initiate a configuration operation for a software application. Each configuration slave automatically performs a series of actions to configure the node on which it resides. When all the nodes complete the configuration operation for the software, the process is complete. While performing the series of actions, the configuration slaves generate logs that reflect their progress in performing the series of actions. If a problem occurs during performance of the series of actions, the configuration slave that encounters the problem indicates to the configuration coordinator that an error occurred.