Amazon Technologies, Inc.

Davide Pagano

Ippokratis Pandis

Gaurav Saxena

Naresh Chainani

Balakrishnan Narayanaswamy

Eric Ray Hotinger

Martin Grund

Mohammad Rezaur Rahman

Fabian Oliver Nagel

Bruce William McGaughy

Chao Duan

Arvind Jayasundar

Yousuf Hussain Syed Mohammad

William Michael McCreedy

Mikhail Krestyaninov

Kathiravan Kalimuthu

Luxiang Yin

Bin Zhang

Hitenkumar Sonani

A database service may distribute resources across different geographic locations or other infrastructures to increase availability of the resources and may provide multiple locations to access resources and isolate failure of resources to a respective location or infrastructure. The processing resources in differing fault tolerance zones may be able to continue operating in the event of an outage impacting an entire fault tolerance zone. The database service may generate a supporting processing cluster in the differing fault tolerance zone that handles at least a portion of the access requests of an initial processing cluster. The database service may provision the supporting processing cluster in a separate fault tolerance zone that has a similar capacity and may provision and maintain the cluster in order to preclude the potential of not having sufficient capacity to recover upon failure of a single fault tolerance zone.

Access requests processing and failover handling across multiple fault tolerance zones

Scaling of query processing resources for efficient utilization and performance is implemented for a database service. A query is received via a network endpoint associated with a database managed by a database service. Respective response times predicted for the query using different query processing configurations available to perform the query are determined. Those query processing configurations with response times that exceed a variability threshold determined for the query may be excluded. A remaining query processing configuration may then be selected to perform the query.

Scaling query processing resources for efficient utilization and performance

Techniques for rapid secure authentication and communications through multitenant components in a provider network are described. A main database cluster can request a burst cluster from a burst service, which can provide the main cluster with a shared secret associated with only a selected burst cluster. The main cluster can use the shared secret to encrypt a value that can be passed, via a proxy, to the selected burst cluster in a connection request. The selected burst cluster can validate that the connection request was truly originated by the main cluster by validating the encrypted value using the shared secret.

Rapid secure authentication and communications through multitenant components in provider networks

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Fremont, CA, United States of America

Davide Pagano