Abstract: Methods, systems, and computer-readable media for automatically configuring an inventory of hardware to interact seamlessly with a datacenter are provided. Initially, customer-specific specifications are collected from a user, which are automatically supplemented with platform-specific specifications. These specifications are used to select the hardware inventory from a set of predefined hardware clusters, where each of the predefined hardware clusters represents compatible configurations of hardware assets and logical assets that have been demonstrated to function congruently. A cluster-configuration file is derived from data held within a stock-keeping unit (SKU) that describes the selected hardware inventory. The cluster-configuration file is populated with abstract symbolic representations that act as placeholders for expected values that are presently unknown. Network resources are assigned by automated conversion of the abstract symbolic representations into concrete values.

Abstract: Building binary packages for software products, particularly large-scale software products, is a highly computation intensive process. Thus, it is desirable to distribute the workload over a large number of computing nodes so as to have the build process complete in an optimal period of time. One environment providing compute resources that can be utilized for a highly available and dynamically scalable distributed build process is an elastic compute cloud. In such an environment, virtual machines can be instantiated and destroyed as the resource requirements of the build process dictate. This has the advantage that dedicated hardware is unneeded, and excess capacity on the hardware employed can be employed for other computation tasks when the build process is idle. Presented herein are systems, methods and computer storage media for distributing a highly available and scalable build service, suitable for use in an elastic compute environment or other distributed environment.

Abstract: In various embodiments, methods and systems for modeling or representing hardware inventory based on a topology definition is provided. A topology definition having physical elements and logical elements corresponding to a physical topology layer and a logical topology layer is received. An instance definition for a rack, cluster, or datacenter for a hardware management operation is received. The instance identifies a physical topology and a logical topology for the operation. A hardware management service is executed, based on the topology definition and the instance definition, to manage the hardware inventory of the topology definition. Hardware management of the hardware inventory corresponding to the separately defined physical elements and logical elements is performed with attributes that are defined in the schema.

Abstract: A computer-implemented method for managing a release of a software product includes obtaining a request for the release, the request including workflow action parameter data to define a release pipeline involving a plurality of software engineering systems configured to process data indicative of the software product, and executing, with a processor, a workflow to implement the release pipeline in accordance with the workflow action parameter data. Executing the workflow includes sending a series of instructions to the plurality of software engineering systems. A successive instruction in the series of instructions is sent based on whether a gating rule for the release is met.

Abstract: In various embodiments, methods and systems for modeling or representing hardware inventory based on a topology definition is provided. A topology definition having physical elements and logical elements corresponding to a physical topology layer and a logical topology layer is received. An instance definition for a rack, cluster, or datacenter for a hardware management operation is received. The instance identifies a physical topology and a logical topology for the operation. A hardware management service is executed, based on the topology definition and the instance definition, to manage the hardware inventory of the topology definition. Hardware management of the hardware inventory corresponding to the separately defined physical elements and logical elements is performed with attributes that are defined in the schema.

Abstract: A computer-implemented method for managing a release of a software product includes obtaining a request for the release, the request including workflow action parameter data to define a release pipeline involving a plurality of software engineering systems configured to process data indicative of the software product, and executing, with a processor, a workflow to implement the release pipeline in accordance with the workflow action parameter data. Executing the workflow includes sending a series of instructions to the plurality of software engineering systems. A successive instruction in the series of instructions is sent based on whether a gating rule for the release is met.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for automated standalone bootstrapping of hardware inventory that includes a provisioning workflow of discovering, validating, and configuring hardware inventory. In an exemplary embodiment, an in-rack computing device, such as a chassis manager or selected blade, initializes an intra-rack communication network with a hardware inventory of the rack. The in-rack computing device initiates intra-rack communication with the hardware inventory in the rack, using the intra-rack communication network, to discover at least a set of computing units in a hardware inventory. Intra-rack communications that include traffic received from the set of computing units.

Abstract: Methods, media, and systems for secure provisioning of servers within a cloud computing environment are provided for herein. In some embodiments, a management service can delegate provisioning of a server of the cloud computing environment to an imaging service. In response, the imaging service can generate an operating system image for the server and can utilize disk encryption to protect to operating system image. In embodiments, a volume encryption key of the disk encryption can be encrypted utilizing a public key of a trusted platform manager of the server, to produce an encrypted volume encryption key that is protected by the trusted platform module of the server. The encrypted operating system image and the encrypted volume encryption key can then be transmitted to the server to cause the server to be provisioned with the operating system image. Other embodiments may be described and/or claimed herein.

Abstract: In embodiments, methods and systems for implementing an infrastructure management system that supports hardware failure remediation are provided. A determination is made that a failure of a hardware component has occurred. The hardware component is part of a hardware composite. A remediation attribute of the hardware composite is accessed. The remediation attribute indicates a minimum operational bar for the hardware composite. The minimum operational bar is based on health metrics or optional and required components of the hardware composite. The bar supports determining whether the hardware composite should operate in a degraded state. A determination is made that the hardware composite if operating without the hardware component that has failed meets the minimum operational bar for the hardware composite. Operation of the hardware composite in the degraded state is initiated.

Abstract: Various methods and systems for implementing dependency management for an infrastructure are provided. A dependency service manager of the dependency management system includes a plurality of dependency management system components that facilitate automatically discovering and analyzing data to generate dependency data. The dependency data includes dependencies and dependents of dependency service tenants which are tenant services of the infrastructure. The dependency data is generated based on data retrieved by a plurality of collectors. A collector from the plurality of collectors is an agent that retrieves data associated with dependency service tenants based on a corresponding collection time attribute of the collector. A collector accesses data for generating the dependency data at one of the following collection times: design time, deployment time and runtime.

Abstract: Methods, systems, and computer-readable media for automatically configuring an inventory of hardware to interact seamlessly with a cloud-computing fabric of a data center are provided. Initially, hardware devices within the hardware inventory are located by sending and receiving communications to network devices via serial-based connections and network-based connections, respectively. Information collected during hardware-device location is cross-referenced against a template file for purposes of validation. This information is also employed to generate an infrastructure state of the hardware inventory. The infrastructure state is shared with a controller of the fabric to integrate the hardware inventory therein.

Abstract: Building binary packages for software products, particularly large-scale software products, is a highly computation intensive process. Thus, it is desirable to distribute the workload over a large number of computing nodes so as to have the build process complete in an optimal period of time. One environment providing compute resources that can be utilized for a highly available and dynamically scalable distributed build process is an elastic compute cloud. In such an environment, virtual machines can be instantiated and destroyed as the resource requirements of the build process dictate. This has the advantage that dedicated hardware is unneeded, and excess capacity on the hardware employed can be employed for other computation tasks when the build process is idle. Presented herein are systems, methods and computer storage media for distributing a highly available and scalable build service, suitable for use in an elastic compute environment or other distributed environment.

Abstract: Methods, systems, and computer-readable media for automatically configuring an inventory of hardware to interact seamlessly with a computing fabric of a data center are provided. Initially, a communicative coupling between a user device and computing units of the hardware inventory is established. The communicated coupling allows an engine running on the user device to provision the computing units with software that allows the hardware inventory to function as a fabric-computing cluster (FCC) of the data center. Provisioning involves deploying a computing fabric to the computing units, and deploying core infrastructure services to run on top of the computing fabric. The computing fabric enables the computing units to interact as a unified logical system, while the core infrastructure services represent operating-system-level components that provide underlying support of applications running on the FCC.

Abstract: In various embodiments, methods and systems for modeling or representing hardware inventory based on a topology definition is provided. A topology definition having physical elements and logical elements corresponding to a physical topology layer and a logical topology layer is received. An instance definition for a rack, cluster, or datacenter for a hardware management operation is received. The instance identifies a physical topology and a logical topology for the operation. A hardware management service is executed, based on the topology definition and the instance definition, to manage the hardware inventory of the topology definition. Hardware management of the hardware inventory corresponding to the separately defined physical elements and logical elements is performed with attributes that are defined in the schema.

Abstract: Building binary packages for software products, particularly large-scale software products, is a highly computation intensive process. Thus, it is desirable to distribute the workload over a large number of computing nodes so as to have the build process complete in an optimal period of time. One environment providing compute resources that can be utilized for a highly available and dynamically scalable distributed build process is an elastic compute cloud. In such an environment, virtual machines can be instantiated and destroyed as the resource requirements of the build process dictate. This has the advantage that dedicated hardware is unneeded, and excess capacity on the hardware employed can be employed for other computation tasks when the build process is idle. Presented herein are systems, methods and computer storage media for distributing a highly available and scalable build service, suitable for use in an elastic compute environment or other distributed environment.

Abstract: A method for optimization of a software build includes collecting first data representative of inputs for a build process obtained by a set of data accessing operations implemented during a first execution of the build process, the set including a file accessing operation and a non-file accessing operation. A redirection routine embedded within the build process captures the inputs. The first data is compared with second data representative of the inputs obtained in connection with a second execution of the build process. If the first and second data do not match, the second data is recorded in a data store and output data generated by the second execution of the build process is stored. If the first and second data match, output data generated by the first execution of the build process is used as an output for the second execution of the build process.

Abstract: A method for nonintrusive network load generation may include determining available resources in a distributed computing system, where the distributed computing system includes a plurality of computing devices and a target deployment. Based on an amount of available resources between the target deployment and a plurality of source computing devices, the plurality of source computing devices may be selected to generate a network load directed from the plurality of source computing devices to the target deployment. The plurality of source computing devices may be a subset of the plurality of computing devices in the distributed computing system. A network-traffic generator service may be provided to the plurality of source computing devices in order to generate the network load directed from the plurality of source computing devices to the target deployment. The performance of the distributed computing system in response to the generated network load may be monitored.

Abstract: Methods, systems, and computer-readable media for automatically validating and configuring an inventory of hardware to interact seamlessly with a cloud-computing fabric of a data center are provided. Initially, devices internal to the hardware inventory are located by sending and receiving messages via out-of-band communication channels and network communication channels, respectively. Locating the internal devices involves establishing communication from a user device to the hardware inventory and selecting at least one of the internal devices for conducting a discovery process thereon. The discovery process involves receiving a first network identifier via the out-of-band communication channel and receiving a second network identifier via the network communication channel. When the first and second network identifiers match, the interconnection of the selected device is validated. Otherwise, one or more remedial measures are initiated with respect to the selected device.

Abstract: Methods, systems, and computer-readable media for automatically validating and configuring an inventory of hardware to interact seamlessly with a cloud-computing fabric of a data center are provided. Initially, devices internal to the hardware inventory are located by sending and receiving messages via out-of-band communication channels and network communication channels, respectively. Locating the internal devices involves establishing communication from a user device to the hardware inventory and selecting at least one of the internal devices for conducting a discovery process thereon. The discovery process involves receiving a first network identifier via the out-of-band communication channel and receiving a second network identifier via the network communication channel. When the first and second network identifiers match, the interconnection of the selected device is validated. Otherwise, one or more remedial measures are initiated with respect to the selected device.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for automated standalone bootstrapping of hardware inventory that includes a provisioning workflow of discovering, validating, and configuring hardware inventory. In an exemplary embodiment, an in-rack computing device, such as a chassis manager or selected blade, initializes an intra-rack communication network with a hardware inventory of the rack. The in-rack computing device initiates intra-rack communication with the hardware inventory in the rack, using the intra-rack communication network, to discover at least a set of computing units in a hardware inventory. Intra-rack communications that include traffic received from the set of computing units.