Abstract: A method for managing an amount of IO requests transmitted from a host computer to a storage system is described. A current latency value of an IO request most recently removed from an issue queue maintained by a host bus adapter of the host computer in order to transmit IO requests from the host computer to the storage system is periodically determined. An average latency value is the calculated based on the current latency value and a size limit of the issue queue is adjusted based in part on the average latency value. Upon receiving an IO request from one of a plurality of client applications running on the host computer, it can then be determined whether a number of pending IO requests in the issue queue has reached the size limit and the IO request can be transmitted to the issue queue if the number of pending IO request falls within the size limit.

Abstract: A system and method for providing quality of service (QoS) for clients running on host computers to access a common resource uses a resource pool module and a local scheduler in at least one of the host computers. The resource pool module operates to compute an entitlement of each client for the common resource based on a current capacity for the common resource and demands of the clients for the common resource. In addition, the resource pool module operates to assign a portion of the computed current capacity for the common resource to a particular host computer using the computed entitlement of each client running on the particular host computer. The local scheduler operates to allocate the portion of the computed current capacity among the clients running on the particular host computer.

Abstract: Embodiments perform centralized input/output (I/O) path selection for hosts accessing storage devices in distributed resource sharing environments. The path selection accommodates loads along the paths through the fabric and at the storage devices. Topology changes may also be identified and automatically initiated. Some embodiments contemplate the hosts executing a plurality of virtual machines (VMs) accessing logical unit numbers (LUNs) in a storage area network (SAN).

Abstract: Two shared data structures are maintained in a storage unit for coordinating statistic collection among multiple hosts that share the storage unit. The first data structure stores information about the number of hosts that possess slots within the second data structure and identifying information about the slots. The second data structure maintains statistics of each of the multiple hosts. By using this first data structure, hosts can be added to and deleted from the second data structure in an organized manner.

Abstract: An anomaly in a shared input/ouput (IO) resource that is accessed by a plurality hosts or clients is detected when a host that is not bound by any QoS policy presents large workloads to a shared IO resource that is also accessed by hosts or clients that are governed by QoS policy. The anomaly detection triggers a response from the hosts or clients as a way to protect against the effect of the anomaly. The response is an increase in window sizes. The window sizes of the hosts or clients may be increased to the maximum window size or in proportion to their QoS shares.

Abstract: A method for measuring latencies caused by processing performed within a common resource is provided. A current latency value representing a time of residency of an IO request in a queue prior to receipt of acknowledgment from the common resource of completion of the IO request is received from a device comprising the queue, which maintains entries for IO requests that have been dispatched to and are pending at the common resource. An average latency value is calculated based in part on the current latency value. An adjusted capacity size for the queue is calculated based in part on the average latency value and the queue's capacity is set to the adjusted capacity size. IO requests are held in a buffer if the queue's capacity is full to reduce the effect of an amount of work transmitted to the common resource on current latency values provided by the device.

Abstract: A method for managing an amount of IO requests transmitted from a host computer to a storage system is described. A current latency value of an IO request most recently removed from an issue queue maintained by the host computer in order to transmit IO requests from the host computer to the storage system is periodically determined. An average latency value is the calculated based on the current latency value and a size limit of the issue queue is adjusted based in part on the average latency value. Upon receiving an IO request from one of a plurality of client applications running on the host computer, it can then be determined whether a number of pending IO requests in the issue queue has reached the size limit and the IO request can be transmitted to the issue queue if the number of pending IO request falls within the size limit.

Abstract: An anomaly in a shared input/ouput (IO) resource that is accessed by a plurality hosts or clients is detected when a host that is not bound by any QoS policy presents large workloads to a shared IO resource that is also accessed by hosts or clients that are governed by QoS policy. The anomaly detection triggers a response from the hosts or clients as a way to protect against the effect of the anomaly. The response is an increase in window sizes. The window sizes of the hosts or clients may be increased to the maximum window size or in proportion to their QoS shares.

Abstract: To schedule workloads of requesters of a shared storage resource, a scheduler specifies relative fairness for the requesters of the shared storage resource. In response to the workloads of the requesters, the scheduler modifies performance of the scheduler to deviate from the specified relative fairness to improve input/output (I/O) efficiency in processing the workloads at the shared storage resource.

Abstract: A method for managing an amount of IO requests transmitted from a host computer to a storage system is described. A current latency value of an IO request most recently removed from an issue queue maintained by the host computer in order to transmit IO requests from the host computer to the storage system is periodically determined. An average latency value is the calculated based on the current latency value and a size limit of the issue queue is adjusted based in part on the average latency value. Upon receiving an IO request from one of a plurality of client applications running on the host computer, it can then be determined whether a number of pending IO requests in the issue queue has reached the size limit and the IO request can be transmitted to the issue queue if the number of pending IO request falls within the size limit.

Abstract: One or more embodiments of the present invention provide a technique for effectively managing virtualized computing systems with an unlimited number of hardware resources. Host systems included in a virtualized computer system are organized into a scalable, peer-to-peer (P2P) network in which host systems arrange themselves into a network overlay to communicate with one another. The network overlay enables the host systems to perform a variety of operations, which include dividing computing resources of the host systems among a plurality of virtual machines (VMs), load balancing VMs across the host systems, and performing an initial placement of a VM in one of the host systems.

Abstract: One or more embodiments of the present invention provide a technique for effectively managing virtualized computing systems with an unlimited number of hardware resources. Host systems included in a virtualized computer system are organized into a scalable, peer-to-peer (P2P) network in which host systems arrange themselves into a network overlay to communicate with one another. The network overlay enables the host systems to perform a variety of operations, which include dividing computing resources of the host systems among a plurality of virtual machines (VMs), load balancing VMs across the host systems, and performing an initial placement of a VM in one of the host systems.

Abstract: One or more embodiments of the present invention provide a method for performing initial placement and load balancing of a data objects in a distributed system. The distributed system includes hardware resources, e.g., host systems and storage arrays, which are configured to execute and/or store data objects. A data object is initially placed into the distributed system by creating a virtual cluster of hardware resources that are compatible to execute and/or host the data object, and then selecting from the virtual cluster a hardware resource that is optimal for executing and/or hosting the data object. The data object is placed into the selected hardware resource, whereupon a load balancing operation is optionally performed across the virtual cluster. The virtual cluster is subsequently released, and the distributed system is returned to its original state with the data object included therein.

Abstract: A method for measuring latencies caused by processing performed within a common resource is provided. A current latency value representing a time of residency of an IO request in a queue prior to receipt of acknowledgment from the common resource of completion of the IO request is received from a device comprising the queue, which maintains entries for IO requests that have been dispatched to and are pending at the common resource. An average latency value is calculated based in part on the current latency value. An adjusted capacity size for the queue is calculated based in part on the average latency value and the queue's capacity is set to the adjusted capacity size. IO requests are held in a buffer if the queue's capacity is full to reduce the effect of an amount of work transmitted to the common resource on current latency values provided by the device.

Abstract: A method for providing quality of service to a plurality of hosts accessing a common resource is described. The common resource may be a middle-tier or back-end server. A client IO request is received at one host of the plurality of hosts from one of a plurality clients executing as software entities on respective hosts. The host determines whether an issue queue is full. The IO request is issued to the common resource when the issue queue is not full. A current average latency observed at the host and an adjusted window size is calculated, based at least in part on the current average latency. The issue queue is resized to correspond with the adjusted window size.

Abstract: Maximum throughput of a storage unit, and workload and latency values of the storage unit corresponding to a predefined fraction of the maximum throughput are estimated based on workloads and latencies that are monitored on the storage unit. The computed metrics are usable in a variety of different applications including admission control, storage load balancing, and enforcing quality of service in a shared storage environment.

Abstract: A method and system for providing quality of service to a plurality of hosts accessing a common resource is described. According to one embodiment, a plurality of IO requests is received from clients executing as software entities on one of the hosts. An IO request queue for each client is separately managed, and an issue queue is populated based on contents of the IO request queues. When a host issue queue is not full, a new IO request is entered into the host issue queue and is issued to the common resource. A current average latency observed at the host is calculated, and an adjusted window size is calculated at least in part based on the current average latency. The window size of the issue queue is adjusted according to the calculated window size.

Abstract: A method and system for providing quality of service to a plurality of hosts accessing a common resource is described. According to one embodiment, a plurality of IO requests is received from clients executing as software entities on one of the hosts. An IO request queue for each client is separately managed, and an issue queue is populated based on contents of the IO request queues. When a host issue queue is not full, a new IO request is entered into the host issue queue and is issued to the common resource. A current average latency observed at the host is calculated, and an adjusted window size is calculated at least in part based on the current average latency. The window size of the issue queue is adjusted according to the calculated window size.

Abstract: Distributed storage resources are managed based on data collected from online monitoring of workloads on the storage resources and performance characteristics of the storage resources. Load metrics are calculated from the collected data and used to identify workloads that are migration candidates and storage units that are migration destinations, so that load balancing across the distributed storage resources can be achieved.

Abstract: A method and system for providing quality of service to a plurality of hosts accessing a common resource is described. According to one embodiment, a plurality of IO requests is received from clients executing as software entities on one of the hosts. An IO request queue for each client is separately managed, and an issue queue is populated based on contents of the IO request queues. When a host issue queue is not full, a new IO request is entered into the host issue queue and is issued to the common resource. A current average latency observed at the host is calculated, and an adjusted window size is calculated at least in part based on the current average latency. The window size of the issue queue is adjusted according to the calculated window size.