Abstract:
A database service may provide multi-tenant and single-tenant environments in which tables may be maintained on behalf of clients. The service (or underlying system) may create database instances and tables in either or both types of environments (e.g., by default or according to various parameter values specified in requests to create the instances or tables). When receiving and servicing requests directed to a table hosted in a single-tenant environment, the system may elide at least some of the authentication or metering operations that would be performed when servicing requests directed to tables hosted in a multi-tenant environment. Tables may be moved from a single-tenant environment to a multi-tenant environment, or vice versa, automatically by the system (e.g., dependent on an observed, expected, or desired throughput) or in response to an explicit request from a client to do so (e.g., to increase throughput or reduce cost).
Abstract:
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.
Abstract:
Replicated instances in a database environment provide for automatic failover and recovery. A monitoring component can periodically communicate with a primary and a secondary replica for an instance, with each capable of residing in a separate data zone or geographic location to provide a level of reliability and availability. A database running on the primary instance can have information synchronously replicated to the secondary replica at a block level, such that the primary and secondary replicas are in sync. In the event that the monitoring component is not able to communicate with one of the replicas, the monitoring component can attempt to determine whether those replicas can communicate with each other, as well as whether the replicas have the same data generation version. Depending on the state information, the monitoring component can automatically perform a recovery operation, such as to failover to the secondary replica or perform secondary replica recovery.
Abstract:
A block storage service provides block-level storage to a plurality of distinct computing instances for a plurality of distinct users. For each of one or more of the plurality of distinct computing instances, information about data being stored in the block storage service is determined. Based on the information about the data being stored in the block storage service, a block storage transaction enhancement for the data being stored in the block storage service is determined. The block storage service performs the selected block storage transaction enhancement with respect to the data being stored in the block storage service.
Abstract:
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.
Abstract:
A distributed system for collecting and processing packet routing information is provided. A service provider, such as a content delivery network service provider, can maintain multiple Points of Presence (“POPs”). Routing computing devices associated with each POP can forward information about the packet routing information to a packet routing management component. The packet routing component can process the information provided by the various POPs. The packet routing component can then update, or otherwise modify, packet routing information used by one or more of the POPs. Accordingly, the packet routing management component can then selectively distribute the updated or modified packet routing information, including the distribution to all POPs, the targeted distribution to specific POPs and the creation of centrally accessible routing information.
Abstract:
Methods and apparatus for resource silos at network-accessible services are disclosed. A subset of resources used for a database service, including at least one resource from each of a plurality of data centers, is selected for membership in a resource silo based on grouping criteria. A silo routing layer node identifies the resource silo as the target silo to which a client work request is to be directed. The client work request is sent to a front-end resource of the target silo either by the client, or by the silo routing layer node on behalf of the client. The front-end resource of the target silo transmits a representation of the work request to a back-end resource of the target silo, where a work operation corresponding to request is performed.
Abstract:
Replicated instances in a database environment provide for automatic failover and recovery. A monitoring component can periodically communicate with a primary and a secondary replica for an instance, with each capable of residing in a separate data zone or geographic location to provide a level of reliability and availability. A database running on the primary instance can have information synchronously replicated to the secondary replica at a block level, such that the primary and secondary replicas are in sync. In the event that the monitoring component is not able to communicate with one of the replicas, the monitoring component can attempt to determine whether those replicas can communicate with each other, as well as whether the replicas have the same data generation version. Depending on the state information, the monitoring component can automatically perform a recovery operation, such as to failover to the secondary replica or perform secondary replica recovery.
Abstract:
The values of various operating and/or configuration parameters of a data environment are managed using a set of self-service Web services and interfaces of a separate control environment. A customer can submit a Web services call into an externally-facing application programming interface (API) or other such externally-facing interface of the control environment. The API receiving the call, as well as information extracted from the call, can be used to determine appropriate adjustments to be performed in the data environment. A workflow can be instantiated that includes tasks used to validate and/or apply the adjustments to the target resources, such as databases, data instances, data stores, instance classes, etc. Various real-time functions such as monitoring and auto-scaling also can be performed via the control plane.
Abstract:
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.