Abstract: One variation of a system for implementing a key-value data store includes one or more processors, storage media and instructions stored in the storage media which, when executed by the system cause the system to: receive a request store a particular key-value item; request a first networked distributed data storage system to store the particular key-value item; based on a determination that a set of one or more offload criteria is satisfied: retrieve a first set of key-value items from the first networked distributed data storage system, and request a second networked distributed data storage system to store the first set of key-value items in a first set of one or more data objects. The first networked distributed data storage system can have a lower data write latency and a higher data storage cost than the second networked distributed data storage system.

Abstract: One variation of a system for implementing a key-value data store includes one or more processors, storage media and instructions stored in the storage media which, when executed by the system cause the system to: receive a request store a particular key-value item; request a first networked distributed data storage system to store the particular key-value item; based on a determination that a set of one or more offload criteria is satisfied: retrieve a first set of key-value items from the first networked distributed data storage system, and request a second networked distributed data storage system to store the first set of key-value items in a first set of one or more data objects. The first networked distributed data storage system can have a lower data write latency and a higher data storage cost than the second networked distributed data storage system.

Abstract: A facility comprising systems and method for automatically triggering the collection of comprehensive monitoring information in a distributed processing system. The facility compares the overall performance of distributed processing system to one or more performance metrics and, in response to determining that one or more performance metrics is not satisfied, triggers one or more of the nodes within the distributed processing system to increase one or more of its monitoring rate or its distribution rate. The facility collects and analyzes the collected information to provide resources that can be used to assess and diagnose failures within the distributed processing system. In this manner, the facility reacts to performance anomalies by triggering nodes within in the system to provide comprehensive performance information over a trigger period for diagnostic purposes.

Abstract: A facility comprising systems and method for automatically triggering the collection of comprehensive monitoring information in a distributed processing system. The facility compares the overall performance of distributed processing system to one or more performance metrics and, in response to determining that one or more performance metrics is not satisfied, triggers one or more of the nodes within the distributed processing system to increase one or more of its monitoring rate or its distribution rate. The facility collects and analyzes the collected information to provide resources that can be used to assess and diagnose failures within the distributed processing system. In this manner, the facility reacts to performance anomalies by triggering nodes within in the system to provide comprehensive performance information over a trigger period for diagnostic purposes.

Abstract: A facility comprising systems and method for automatically triggering the collection of comprehensive monitoring information in a distributed processing system. The facility compares the overall performance of distributed processing system to one or more performance metrics and, in response to determining that one or more performance metrics is not satisfied, triggers one or more of the nodes within the distributed processing system to increase one or more of its monitoring rate or its distribution rate. The facility collects and analyzes the collected information to provide resources that can be used to assess and diagnose failures within the distributed processing system. In this manner, the facility reacts to performance anomalies by triggering nodes within in the system to provide comprehensive performance information over a trigger period for diagnostic purposes.