Amazon Technologies, Inc.

Eric Paul Wei

Diwakar Gupta

Juan-Pierre Longmore

James Alfred Gordon Greenfield

Anuj Prateek

Albert Park Niemoller

Andrew Bruce Dickinson

Mihir Sadruddin Surani

Andrew James Lusk

James A G Greenfield

Colin John Whittaker

Paul C Schattauer

Bradley D Roberts

Varun Madan

Christopher S Vasquez

Pooja Madan

James Stanford Gilmore

Eric Jason Brandwine

Rudresh Amin

Bradley Joseph Gussin

Chen Yang

Daniel Robert Fuller

Noel O'Flaherty

James Ag Greenfield

Daniel Bien

Donald Patrick McGarry

Christopher Robert Hartman

Colin J Whittaker

When a request to transition use of a first data store to a second data store is identified (e.g., when a new regional computing stack is to be brought online in a network), tables in the second data store are created that correspond to respective ones of tables of the first data store. Data items are then accessed from the first data store and translated into a format interpretable by a remote data storage service. Thereafter, a network-based application programming interface (API) call is performed to store the data items in the remote data storage service using the data items in the second format. The data items as stored in the remote storage service are accessed and imported into the second data store.

Database migration for new regions and disparate customer accounts

Machine learning automatic pipeline management for automated software deployment is described. An adjustment to computing capacity for a region of a multi-region computing network is identified. A service to be deployed in the region of the multi-region computing network is further identified. Configuration settings for deployment of the service in the region is generated using past deployment data for the service in other regions of the multi-region computing network. A continuous code delivery service is directed to add a stage to a software deployment pipeline for the region. The stage may be configured using the at least one configuration setting.

Machine learning pipeline management for automated software deployment

Availability zone and region recovery are described. For an availability zone (AZ), a recovery availability zone (rAZ) may be identified based on available computing capacity of the recovery availability zone and geographic proximity of the availability zone relative to the recovery availability zone. In an instance in which the availability zone is impacted in which at least one of hardware and software of the availability zone is not fully operational, a virtual private cloud (VPC) is generated that establishes a peered connection between the availability zone and the recovery availability zone. A service is executed in the recovery availability zone, permitting any other services executing in the availability zone to invoke the service and become partially or fully operational.

Availability zone recovery using virtual private clouds

Disclosed are various embodiments for centralized and dynamically generated service configurations for data center and other region builds. A computing environment may be configured to receive requests to deploy a new computing stack or service from different geographical regions at a central service. For the individual ones of the requests, the computing environment may identify computing resources of the computing environment required to deploy the new computing stack or service, determine an order of creation of the computing resources, and create at least one virtual process that automatically allocates the computing resources for the new computing stack based on a predetermined order of creation.

Centralized and dynamically generated service configurations for data center and region builds

Satellite virtual private clouds (VPCs) are described. A primary VPC is executed having one or more core services hosted therein that are required by one or more satellite VPCs. A satellite VPC is executed that is logically independent of the primary VPC networked environment. A peered connection between the primary VPC and the satellite VPC is established. The peered connection permits the satellite VPC networked environment to access the at least one core service hosted in the primary VPC. A customer account may be associated with a suitable permission to perform isolated development in the satellite VPC networked environment without impacting any service hosted by the primary VPC networked environment.

Satellite virtual private cloud network environments

For a network service to be deployed in one of a plurality of regional computing stacks, the network service may be partitioned into a region-specific portion and a region-agnostic portion. A first data transfer of the region-agnostic portion of the network service and a second data transfer of the region-specific portion may be performed separate from one another. Configuration settings of the network service as previously deployed in one or more of the regional computing devices may be accessed, and the region-specific portion may be configured using region-specific configuration settings as modified or confirmed by an administrator. The region-specific portion and the region-agnostic portion are deployed in one of the regional computing stacks as part of a networked computing environment.

Homogeneous pre-built isolated computing stacks for data center builds

Disclosed are various embodiments for automating data center builds through the use of service proxies. A proxy is configured in a testing computing environment to receive service calls for a plurality of first services in the testing computing environment. The proxy forwards the service calls to at least one corresponding instance of the plurality of first services not in the testing computing environment. One or more second services in the testing computing environment that generate the service calls for the plurality of first services are then tested. The service calls are handled by the proxy during testing.

Service proxies for automating data center builds

Launching data stores when new computing infrastructure is deployed is described. A proxy data storage service may be provided that receives instances of an application programming interface (API) call to store data and determines one of a first data store or a second data store to store the data. For instance, in response to receipt of a first instance of the API call, the proxy data storage service may store data in a first data store. However, after a provisioning of the second data store, the proxy data storage service may store data in the second data store in response to receipt of a second instance of the API call. In an instance in which the data stored in the second data store also exists in the first data store, the data is deleted from the first data store until an eventual migration of data is achieved.

Vectored data store for seeding and building data stores in new regions

Techniques are disclosed for a client-and-server architecture where the client makes scheduled execution of instances to the server. The server may then launch occurrences as indicated by one of these API calls at each of the scheduled times. The server may also implement operations to selectively execute particular occurrences, such as executing a new occurrence only when no other occurrences are still running. In other embodiments, the server may implement pricing information in a determination of whether to execute a particular occurrence.

Scheduled execution of instances

This document describes techniques for performance testing computing resources in a service provider network. In an example embodiment, a performance manager periodically tests the performance of computing devices in the service provider network using selected computing assets of each computing device, and updates, based on the performance, a ranking value that establishes precedence for allocation of resource instances of the computing device. A placement manager assigns resource instances from the computing devices based on the ranking values.

Web-based computing system with continuous burn-in testing

Disclosed are various embodiments for allocating computing resources. A request to allocate a computing resource in a collection of networked computing devices is obtained. It is determined whether the request can be fulfilled according to a current configuration of the networked computing devices. A reconfiguration of one or more of the networked computing devices to a different configuration is initiated in order to fulfill the request. The reconfiguration is initiated when a value associated with the request exceeds a cost associated with fulfilling the request. The reconfiguration is initiated in response to determining that the request cannot be fulfilled according to the current configuration.

Allocating computing resources

A system includes one or more computer systems that include one or more processors and memory. The memory includes instructions, that, upon being executed by the one or more processors, cause the system to determine a plurality of increased capacity configuration options for a first pool of servers, generate an assessment value for each of the plurality of increased capacity configuration options, and implement a first configuration option of the plurality of increase capacity configuration options having a greatest health increase assessment value.

Event driven virtual machine instance pool balancing

A system includes one or more computer systems that include one or more processors and memory. The memory includes instructions, that, upon being executed by the one or more processors, cause the system to generate forecast demand data for a first pool of servers configured to host virtual machine instances, generate forecast capacity data that forecasts a number of slots available to run virtual machine instances for the first pool of servers, and generate a first pool health index value based on a comparison of the forecast demand data with the forecast capacity data.

Capacity pool health index

A virtual computer system service receives a request to migrate a virtual machine instance from a first physical host to another physical host. The virtual computer system service identifies a configuration of the first physical host and obtains a data structure that specifies compatibility values for pairings of physical host configurations. The virtual computer system uses the configuration of the first physical host and the data structure to select a compatible physical host configuration. Using this compatible physical host configuration, the virtual computer system service selects a set of physical hosts that have this compatible physical host configuration. The set of physical hosts is used to select a second physical host onto which the virtual machine instance is migrated.

Fingerprint-based capacity management of physical hosts

A technology is described for assigning a logical private network address to a computing instance. An example method may include obtaining a preserved logical private network address associated with a customer account so that the preserved logical private network address may be assigned as a logical private network address to a computing instance located in a computing service environment. The logical private network address may be used for network communications within a physical host containing the computing instance and the logical private network address may translate to a physical private network address used for network communications outside of the physical host and within the computing service environment. A network address record for the computing instance may be identified that associates the logical private network address with the physical private network address, and the network address record may be updated by setting the preserved logical private network address associated with the customer account as the logical private network address.

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Seattle, WA, United States of America

Eric Paul Wei