Amazon Technologies, Inc.

Rahul Sharma Pathak

Jason Douglas Denton

Abhishek Rajnikant Sinha

Xing Wu

Turkay Mert Hocanin

Jian Fang

Luca Natali

Bhargava Ram Kalathuru

Pratik Bhagwat Gawande

Sumeetkumar Veniklal Maru

Yuanyuan Yue

Yufeng Jiang

Armen Tangamyan

Anthony A Virtuoso

Andrew Edward Caldwell

Marc Howard Beitchman

Anurag Windlass Gupta

Mehul A Shah

Jonathan Andrew Fritz

Stefano Stefani

Rui Liu

Ashok Kumar

Dallas Lamont Willett

Robin Alan Golden

Santosh Chandrachood

Anoop Kochummen Johnson

Ramkumar Kamalapuram Sugavanam

Linchi Zhang

Sachin Suresh Bhat

Bijay Singh Bisht

Nachimuthu Govindasamy

Aditya Krishnan

Rajul Mittal

Gitesh Tyagi

Eric Mills

Wesley Blumenthal

Jalpan Randeri

Yishan Yang

Udit Mehrotra

Sneha Bharadwaj

Ajay Baliram Jadhav

Konstantin Milyutin

Vignesh Rajamani

Barry Russell

Akila Tennakoon

Seth Thomas Denney

Montana Norman Wong

Carey Michael Crook

Mahmoud Salem

Yugandhar Maram

Shiyu Sun

Yu Yan

Aditya Manohar

Matt Bachman

Jeff Thomas Carter

Balaji Kannan

Nivetha Purusothaman

Parag Pramod Chaudhari

Techniques for adaptive sleep virtual machine management are described. A service of a provider network receives a parameter indicating that a first virtual machine can be slept and determines to sleep the first virtual machine based at least in part on the parameter. A state of the first virtual machine is captured, and the first virtual machine is terminated. The service determines to resume the captured state of the first virtual machine based at least in part on an indication. A second virtual machine is launched using the captured state of the first virtual machine and resumes execution of the captured state of the first virtual machine. A proxy server sends traffic to the first virtual machine before the termination of the first virtual machine and to the second virtual machine after the resumption of execution of the captured state of the first virtual machine by the second virtual machine.

Adaptive sleep virtual machines in a cloud provider network

Techniques for a distributed data processing application service in a cloud provider network are described. A virtual machine bundle is obtained, the virtual machine bundle including a copy of a memory and one or more registers of a paused virtual machine executing a distributed data processing application runtime. A request to launch a virtual machine to execute a distributed data processing application runtime is received, the request to launch the virtual machine including a bundle identifier that identifies the virtual machine bundle. The virtual machine is launched based at least in part on the virtual machine bundle. The virtual machine sends a message to register the virtual machine with a cluster of virtual machines.

Distributed data processing application service in a provider network

Interruptible computing resources for executing queries may be selected. When queries are received, the probability that query can complete execution at interruptible computing resources may be determined. Computing resources to process the query may be selected based on the probability. For queries that are performed on computing resources that are interrupted, interruption handling techniques may retry the query on other computing resources or complete the query on other computing resources, in some embodiments.

Selecting interruptible resources for query execution

A multi-framework blockchain service may be implemented with a common interface to manage different types of blockchain networks. Requests to create a blockchain network may be received via an interface for the control plane that triggers the creation of the blockchain network according to an identified workflow. Various operations to change the blockchain network, including membership changes, node additions, governance changes, analytics changes, and monitoring changes may be allowed or denied by the control plane according to a distributed governance policy in effect for the blockchain network.

Multi-framework managed blockchain service

Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.

Managed query service

Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.

Tracking query execution status for selectively routing queries

Techniques are described for an interactive query service that enables users to query data stored at a federated collection of data sources. An interactive query service provides interfaces that enable users to configure the interactive query service to query any number of heterogeneous data sources pertinent to a user. In general, the configuration of a data source can include identification of: a data source type, access configurations related to accessing the data source, and in some cases metadata describing a structure of the data stored by the data source (for example, a data catalog describing schemas, tables, columns, partitions, datatypes, or other metadata associated with the stored data). Once configured, an interactive query service can receive and execute queries that involve data stored at any combination of a user's data sources, where the queries may be expressed using a standard query language such as the Structured Query Language (SQL).

Enabling federated query access to Heterogeneous data sources

The configuration of computing resources for executing queries may be selected. A comparison of the configuration of computing resources that executed previous queries may be made to select the configuration of computing resources for a received query. A historical query execution model maybe applied, in some embodiments, to determine a resource configuration for computing resources to execute a query. The computing resources may be selected from available computing resources according to the determined resource configuration.

Selecting resource configurations for query execution

Optimized query plans may be generated independent of the query engine that performs the optimized query plan. A request to generate an optimized query plan for a query may be received and a type of engine for performing the query may be identified. An initial plan may be generated in an engine-specific format for the type of engine that is translated into an optimization plan format. An analysis of the initial plan optimization plan format may be performed to generate an optimized query plan. The optimized query plan may be translated into the engine-specific format and sent in response to the request for the optimized query plan.

Engine independent query plan optimization

Available capacity of resources hosted in different networks may be evaluated to select resources for the performance of a query. A query may be received via an interface for one network. The available capacity of the one network and other networks may be evaluated to select resources hosted in another network to perform the query instead of the resources in the one network. The query may then be routed to the resources in the other network and result of the query performed at the resources in the other network provided.

Selecting resources hosted in different networks to perform queries according to available capacity

Techniques for providing an on-demand development environment are described. A service of a provider network receives a request to launch a development environment, such as a notebook, from an electronic device. The service obtains an identification of a computing cluster hosted by the provider network. The service obtains an identification of a compute instance hosted within the provider network, the compute instance executing a software environment to host one or more development environments. The service causes the compute instance to launch a development environment. The service sends a message to configure the launched development environment to execute a computer program written in the development environment using the computing cluster. The service generates a token to secure communications between the electronic device and the development environment and sends the token to an originator of the request.

On-demand development environment

A network-based data discovery and consumption coordination service may provide data set listings for purchase offered by respective data vendors. The data discovery and consumption coordination service may provide listings in response to search requests based on various search criteria, as well as various filtering techniques based on user reviews, ratings, and other user purchase history for data set listings. The data discovery and consumption coordination service may receive a purchase request via a network-based interface for the service. Data consumption resources which may consume a purchased data set may also be identified via the network-based interface for the data discovery and consumption coordination service. The data discovery and consumption coordination service may direct the transfer of the data set for the purchased data set listing to the identified data consumption resource.

Network-based data discovery and consumption coordination service

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Seattle, WA, United States of America

Rahul Sharma Pathak