Amazon Technologies, Inc.

Bohan Liu

Saileshwar Krishnamurthy

Alexandre Olegovich Verbitski

Kamal Kant Gupta

Tengiz Kharatishvili

Anurag Windlass Gupta

Alok Nandan Nikhil

Mushahid Alam

Sandor Loren Maurice

Alexey Kuznetsov

Lawrence Douglas Webley

Debanjan Saha

Joseph Andrew Tucek

Yuhui Yuan

Yoni Shalom

Jagdeep Singh Sidhu

Siyuan Xing

Yibo Zhu

Nicholas Piers O'Shea

Hongbo Song

Yi Ding

Murali Brahmadesam

Saleem Mohideen

Punit Rajgaria

Xiaofeng Bao

Changan Han

Niket Goel

Tiffany Jianto

Proxy-based scaling may be performed for databases. A proxy may be implemented for a database that can establish a connection between the proxy and a database engine to perform a database queries received from a client at the proxy. A scaling event may be detected for the database responsive to which the proxy may establish a connection with a new database engine which may, in some embodiments, have different capabilities or resources that address the features or criteria that triggered the scaling event. Session state may be copied from the database engine to the new database engine so that the new database engine may be able to provide access to the database on behalf of requests received from the client through the proxy.

Proxy-based database scaling

Optimistic concurrency may be implemented for multiple writers to a database. Writes to a database from different writers may succeed unless a conflict is detected at the data store for the database. For detected conflicts, a request to resolve the conflict between writes may be submitted to a primary writer, which may determine and provide a resolution of the conflict to the conflicting writers. The data store may then be updated to commit the selected write identified by the resolution of the conflict.

Optimistic concurrency for a multi-writer database

A service provider network implements seamless scaling via proxy replay of session state. Upon a trigger, such as a determination to scale a server, a scaled server may be spun up and an identifier of the scaled server provided to a first (existing) server. The first server sends the identification of the second server, and session state information for each of the connections between the first server and the request router, to the request router. For each of the connections, the request router establishes a new connection between the request router and the second (scaled) server, and replays the session state information for the connection to the second server. The request router then routes traffic between each existing client connection (e.g., the same existing client connection which carried traffic delivered to the first server) and the corresponding new connection to the second server.

Seamless scaling via proxy replay of session state

A system for updating a database instance with a patch or new binary image. A database instance includes a database engine and a client-side storage layer driver to manage database state information and volume geometry state information associated with client process connections to a volume of a storage layer of a database system during the patching process. The database engine and the client-side storage service driver save database state information and volume geometry state information, execute the new binary image, and restore the updated database engine with the database state information and volume geometry state information. The new binary image may be executed using a fork/exec model, wherein file descriptors used to identify sockets used in existing client connections are preserved, enabling restoration of the client connections without interruption or downtime.

Downtime management during database instance patching

Growing community of inventors

Seattle, WA, United States of America

Bohan Liu