Abstract: Data sets such as databases are often distributed over a number of servers, where each server stores a subset of records and an index that enables the server to locate the records in response to queries. However, tight coupling of indexing and storage may limit load-balancing, fault recovery, and distribution. Instead, the set of servers may be partitioned into a set of storage servers that store the records and a set of index servers of the index over the records. In a set that is decoupled in this manner, load-balancing may involve provisioning and locating index servers independently of the provisioning and locating of the storage servers in view of the particular sensitivities and tolerances of various applications. Additionally, the index servers may also utilize a data layout that is selected and adapted independent of the data layout of the storage servers and/or the schema of the data stored thereby.

Abstract: Databases are often provided according to various organizational models (e.g., document-oriented storage, key/value stores, and relational database), and are accessed through various access models (e.g., SQL, XPath, and schemaless queries). As data is shared across sources and applications, the dependency of a data service upon a particular organizational and/or access models may become confining. Instead, data services may store data in a base representation format, such as an atom-record-sequence model. New data received in a native item format may be converted into the base representation format for storage, and converted into a requested format to fulfill data requests. Queries may be translated from a native query format into a base query format that is applicable to the base representation format of the data set, e.g., via translation into an query intermediate language (such as JavaScript) and compilation into opcodes that are executed by a virtual machine within the database engine.

Abstract: Workloads are often performed by a server set according to a service level agreement, and are often provisioned and load-balanced by dedicating selected computational resources (e.g., servers and bandwidth) for application to the workload. However, resource-based provisioning may not accurately reflect the computational resource expenditure of the workload, leading to overprovisioning or underprovisioning of servers for the workload. Instead, the workload may be evaluated according to a service unit as a measurement of a volume of computational resources consumed by a workload unit, including performance dimensions specified in the service level agreement. The service level agreement may indicate a service unit rate for the workload. The workload may therefore be allocated to a subset of servers in portions according to a service unit rate, where the sum of the service unit rates for the portions allocated to the servers satisfies the service unit rate specified in the service level agreement.

Abstract: Data sets such as databases are often distributed over a number of servers, where each server stores a subset of records and an index that enables the server to locate the records in response to queries. However, tight coupling of indexing and storage may limit load-balancing, fault recovery, and distribution. Instead, the set of servers may be partitioned into a set of storage servers that store the records and a set of index servers of the index over the records. In a set that is decoupled in this manner, load-balancing may involve provisioning and locating index servers independently of the provisioning and locating of the storage servers in view of the particular sensitivities and tolerances of various applications. Additionally, the index servers may also utilize a data layout that is selected and adapted independent of the data layout of the storage servers and/or the schema of the data stored thereby.

Abstract: Databases are often provided according to various organizational models (e.g., document-oriented storage, key/value stores, and relational database), and are accessed through various access models (e.g., SQL, XPath, and schemaless queries). As data is shared across sources and applications, the dependency of a data service upon a particular organizational and/or access models may become confining. Instead, data services may store data in a base representation format, such as an atom-record-sequence model. New data received in a native item format may be converted into the base representation format for storage, and converted into a requested format to fulfill data requests. Queries may be translated from a native query format into a base query format that is applicable to the base representation format of the data set, e.g., via translation into an query intermediate language (such as JavaScript) and compilation into opcodes that are executed by a virtual machine within the database engine.

Abstract: Workloads are often performed by a server set according to a service level agreement, and are often provisioned and load-balanced by dedicating selected computational resources (e.g., servers and bandwidth) for application to the workload. However, resource-based provisioning may not accurately reflect the computational resource expenditure of the workload, leading to overprovisioning or underprovisioning of servers for the workload. Instead, the workload may be evaluated according to a service unit as a measurement of a volume of computational resources consumed by a workload unit, including performance dimensions specified in the service level agreement. The service level agreement may indicate a service unit rate for the workload. The workload may therefore be allocated to a subset of servers in portions according to a service unit rate, where the sum of the service unit rates for the portions allocated to the servers satisfies the service unit rate specified in the service level agreement.

Abstract: Processing services are often provisioned by defining and adjusting the performance capabilities of individual servers, and in multitenancy scenarios, servers may allocate computational resources to ensure that a first client workload does not impact a second client workload. However, a reduced performance capability of a server may create a processing jam with respect to an upstream server of the process path of the workload, where the processing rate mismatch creates a risk of failing to fulfill the performance guarantee for the workload. Instead, the downstream server may monitor and compare its performance capability with the performance guarantee. If a performance guarantee failure risk arises, the server may transmit a performance capability alert to the upstream server, which may rate-limit the processing of the workload. Rate-limiting by the first server in the server path may limit workload intake to a volume for which the process path can fulfill the performance guarantee.

Abstract: Embodiments are directed to implementing a dynamically changeable system model that is customizable per version, programmatically generating system models at runtime and to extending a programmatically generated system model. In an embodiment, a computer system determines that a dynamically changeable system model corresponds to a managed system. The dynamically changeable system model includes various managed system objects. The computer system indicates for the dynamically changeable system model which managed system objects are available in each version of the managed system. The available managed system objects are stored in a data store of the dynamically changeable system model.

Abstract: Data-tier application components (DACs) and methods for managing database applications are disclosed. According to one particular embodiment, a DAC includes a single unit of management that packages metadata related to a database object. The metadata related to the database object includes an identifier of the database object, a database runtime resource identifier of a database runtime resource operable to manipulate the database object, and a policy related to execution of the database runtime resource.

Abstract: Embodiments are directed to combining service operations with various managed system objects to form a new dynamic programming interface combination and determining valid dynamic programming interface combinations. A computer system determines which service operations are offered by a selected managed system. The selected managed system is configured to provide various services comprising multiple different service operations. The computer system determines that managed system objects of the managed system are to be combined with at least one of the service operations. The computer system also combines the service operation with the managed system object, so that a new dynamic programming interface combination is created. The new dynamic programming interface combination is configured for use by the services offered by the managed system.

Abstract: Embodiments are directed to implementing a dynamically changeable system model that is customizable per version, programmatically generating system models at runtime and to extending a programmatically generated system model. In an embodiment, a computer system determines that a dynamically changeable system model corresponds to a managed system. The dynamically changeable system model includes various managed system objects. The computer system indicates for the dynamically changeable system model which managed system objects are available in each version of the managed system. The available managed system objects are stored in a data store of the dynamically changeable system model.

Abstract: Data-tier application components (DACs) and methods for managing database applications are disclosed. According to one particular embodiment, a DAC includes a single unit of management that packages metadata related to a database object. The metadata related to the database object includes an identifier of the database object, a database runtime resource identifier of a database runtime resource operable to manipulate the database object, and a policy related to execution of the database runtime resource.