Abstract: Embodiments of the disclosure provide techniques for measuring congestion and controlling quality of service to a shared resource. A module that interfaces with the shared resource monitors the usage of the shared resource by accessing clients. Upon detecting that the rate of usage of the shared resource has exceeded a maximum rate supported by the shared resource, the module determines and transmits a congestion metric to clients that are currently attempting to access the shared resource. Clients, in turn determine a delay period based on the congestion metric prior to attempting another access of the shared resource.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: Embodiments of the disclosure provide techniques for partitioning a resource object into multiple resource components of a cluster of host computer nodes in a distributed resources system. The distributed resources system translates high-level policy requirements into a resource configuration that the system accommodates. The system determines an allocation based on the policy requirements and identifies resource configurations that are available. Upon selecting a resource configuration, the distributed resources system assigns the allocation and associated values to the selected configuration and publishes the new configuration to other host computer nodes in the cluster.

Abstract: Embodiments presented herein techniques for balancing a multidimensional set of resources of different types within a distributed resources system. Each host computer providing the resources publishes a status on current resource usage by guest clients. Upon identifying a local imbalance, the host computer determines a source workload to migrate to or from the resources container to minimize the variance in resource usage. Additionally, when placing a new resource workload, the host computer selects a resources container that minimizes the variance to further balance resource usage.

Abstract: Embodiments of the disclosure provide techniques managing a log-structured solid state drive (SSD) format in a distributed storage system. SSDs in the distributed storage system maintains a journal of logical changes to storage objects to persist prepared and committed changes in the latency path. The journal includes metadata entries that describe changes and reference data pages. Dense data structures (such as a logical block addressing table) index the metadata entries. To reduce the amount of overhead in I/O operations, the distributed storage system maintains the dense data structures in memory rather than on disk.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: Embodiments presented herein techniques for balancing a multidimensional set of resources of different types within a distributed resources system. Each host computer providing the resources publishes a status on current resource usage by guest clients. Upon identifying a local imbalance, the host computer determines a source workload to migrate to or from the resources container to minimize the variance in resource usage. Additionally, when placing a new resource workload, the host computer selects a resources container that minimizes the variance to further balance resource usage.

Abstract: Embodiments of the disclosure provide techniques for partitioning a resource object into multiple resource components of a cluster of host computer nodes in a distributed resources system. The distributed resources system translates high-level policy requirements into a resource configuration that the system accommodates. The system determines an allocation based on the policy requirements and identifies resource configurations that are available. Upon selecting a resource configuration, the distributed resources system assigns the allocation and associated values to the selected configuration and publishes the new configuration to other host computer nodes in the cluster.

Abstract: Embodiments presented herein techniques for balancing a multidimensional set of resources of different types within a distributed resources system. Each host computer providing the resources publishes a status on current resource usage by guest clients. Upon identifying a local imbalance, the host computer determines a source workload to migrate to or from the resources container to minimize the variance in resource usage. Additionally, when placing a new resource workload, the host computer selects a resources container that minimizes the variance to further balance resource usage.

Abstract: Embodiments of the disclosure provide techniques for partitioning a resource object into multiple resource components of a cluster of host computer nodes in a distributed resources system. The distributed resources system translates high-level policy requirements into a resource configuration that the system accommodates. The system determines an allocation based on the policy requirements and identifies resource configurations that are available. Upon selecting a resource configuration, the distributed resources system assigns the allocation and associated values to the selected configuration and publishes the new configuration to other host computer nodes in the cluster.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: Embodiments of the disclosure provide techniques for measuring congestion and controlling quality of service to a shared resource. A module that interfaces with the shared resource monitors the usage of the shared resource by accessing clients. Upon detecting that the rate of usage of the shared resource has exceeded a maximum rate supported by the shared resource, the module determines and transmits a congestion metric to clients that are currently attempting to access the shared resource. Clients, in turn determine a delay period based on the congestion metric prior to attempting another access of the shared resource.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: Embodiments of the disclosure provide techniques for measuring congestion and controlling quality of service to a shared resource. A module that interfaces with the shared resource monitors the usage of the shared resource by accessing clients. Upon detecting that the rate of usage of the shared resource has exceeded a maximum rate supported by the shared resource, the module determines and transmits a congestion metric to clients that are currently attempting to access the shared resource. Clients, in turn determine a delay period based on the congestion metric prior to attempting another access of the shared resource.

Abstract: Embodiments of the disclosure provide techniques for updating a distributed transaction log on a previously offline resource object component using distributed transaction logs from active host computer nodes from separate RAID mirror configurations. Each component object maintains a journal (log) where distributed transactions are recorded. If a component object goes offline and subsequently returns (e.g., if the node hosting the component object reboots), the component object is marked as stale. To return the component object to an active state, a distributed resources module retrieves the journals from other resource component objects from other RAID configurations where the data is mirrored. The module filters corresponding data that is missing in the journal of the previously offline corresponding object and merges the filtered data to the journal.

Abstract: Embodiments of the disclosure provide techniques managing a log-structured solid state drive (SSD) format in a distributed storage system. SSDs in the distributed storage system maintains a journal of logical changes to storage objects to persist prepared and committed changes in the latency path. The journal includes metadata entries that describe changes and reference data pages. Dense data structures (such as a logical block addressing table) index the metadata entries. To reduce the amount of overhead in I/O operations, the distributed storage system maintains the dense data structures in memory rather than on disk.

Abstract: Embodiments of the disclosure provide techniques managing a log-structured solid state drive (SSD) format in a distributed storage system. SSDs in the distributed storage system maintains a journal of logical changes to storage objects to persist prepared and committed changes in the latency path. The journal includes metadata entries that describe changes and reference data pages. Dense data structures (such as a logical block addressing table) index the metadata entries. To reduce the amount of overhead in I/O operations, the distributed storage system maintains the dense data structures in memory rather than on disk.

Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.