Amazon Technologies, Inc.

Grant Alexander MacDonald McAlister

Milovan Milovanovic

Swaminathan Sivasubramanian

Luis Felipe Cabrera

Stefano Stefani

James Robert Hamilton

Timothy Andrew Rath

Jakub Kulesza

Chiranjeeb Buragohain

Rande Anthony Blackman

Murali Brahmadesam

Raman Mittal

Raymond S Bradford

Ramesh Shankar

Minsoo Oh

Yi Wen Wong

Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Cloning and recovery of data volumes

Data loss thresholds are enforced when performing updates to mirrored data sets. When an update is received for a data set that is mirrored to other copies of the data set, an evaluation of the difference between the data set and the other copies of the data set may be performed. If the evaluation determines that the difference fails to satisfy a threshold for acceptable data loss at the other copies upon a failure of the data set, a data loss mitigation action may be applied to performance of the update until the difference satisfies the threshold.

Enforcing data loss thresholds for performing updates to mirrored data sets

A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.

System and method for implementing a scalable data storage service

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Seattle, WA, United States of America

Grant Alexander MacDonald McAlister