Abstract: A method comprises receiving a representative workload of a computing system, where the representative workload comprises at least one composite transaction. In certain embodiments, the representative workload is a historical workload of a computing system. In general, a composite transaction refers to a transaction that comprises a plurality of transactions. For instance, a given transaction for serving a client's request for information (e.g., a web page) may include embedded therein a plurality of requests/responses for objects (e.g., images, etc.) that form the information (e.g., that form the requested web page). The method further comprises determining, based at least in part on a statistical regression-based analysis, a resource cost for the at least one composite transaction, where the resource cost reflects an amount of utilization of at least one resource of the computing system, such as CPU utilization, in serving the at least one composite transaction.

Abstract: One embodiment is a method that backups up objects to a storage device. A number of objects that are concurrently backed up to the storage device is limited.

Abstract: According to at least one embodiment, a method comprises receiving, into a capacity planning system, workload information representing an expected workload of client accesses of streaming media files from a site. The method further comprises receiving, into the capacity planning system, at least one service parameter that defines a desired service characteristic to be provided by a heterogeneous cluster of servers under the expected workload. The capacity planning system evaluates whether the heterogeneous cluster, having a plurality of different server configurations included therein, is capable of supporting the expecting workload in compliance with the at least one service parameter.

Abstract: According to at least one embodiment, a method comprises receiving a session trace log identifying a plurality of sessions accessing streaming media files from a media server. The method further comprises deriving from the session trace log a segment trace log that identifies for each of a plurality of time intervals the segments of the streaming media files accessed, and using the segment trace log to develop an analytical cache performance model. According to at least one embodiment, a method comprises receiving workload information representing client accesses of streaming media files from a media server, and using an analytical cache performance model to compute a cache hit ratio for the media server under the received workload.

Abstract: Embodiments are directed to methods and apparatus that backup filesystems to a storage device. A backup simulation is used to determine a number of agents to backup the filesystems.

Abstract: One embodiment is a method that backups up filesystems to a storage device. Filesystems having a longer previous backup time are backed up before filesystems having a shorter previous backup time.

Abstract: To model a computing entity, information relating to transactions associated with the computing entity is received. The received information forms a collection of information. The collection is segmented into a plurality of segments, and at least one anomalous segment is identified. A model of the computing entity is built.

Abstract: A method and system for handing-off TCP states in a communication network. Specifically, the present invention allows for handing-off TCP states between nodes in an associated network that is optimized for rare handoff of TCP states. The handoff occurs between dynamically loadable modules that wrap around the TCP/IP stack located at a front-end node and a selected back-end web server. A handoff protocol implemented by the loadable modules works within the kernel level of the existing TCP/IP code. As such, no changes to the existing TCP/IP code is necessary. The loadable modules at the front-end are able to select a back-end web server depending on the content of the web request, coordinate handing off TCP states, and forward packets to the back-end web server. Loadable modules at the selected back-end modify response packets going out to reflect the proper TCP state of the front-end node.

Abstract: Described herein is a method for detecting an error in a prediction of resource usage of an application running in a virtual environment, comprising: providing a plurality of benchmark sets, executing the plurality of benchmark sets in a native hardware system in which the application natively resides, executing the plurality of benchmark sets in the virtual environment, collecting first traces of first resource utilization metrics in the native hardware system based on the execution of each of the plurality of benchmark sets in the native hardware system, collecting second traces of second resource utilization metrics in the virtual environment based on the execution of each of the plurality of benchmark sets in the virtual environment, generating at least one initial prediction model that maps the first traces of first resource utilization metrics to the second traces of second resource utilization metrics, computing a plurality of mean squared errors (MSE's) based on the at least one initial prediction mod

Abstract: To identify similar files in an environment having multiple client computers, a first client computer receives, from a coordinator computer, a request to find files located at the first client computer that are similar to at least one comparison file, wherein the request has also been sent to other client computers by the coordinator computer to request that the other client computers also find files that are similar to the at least one comparison file. In response to the request, the first client computer compares signatures of the files located at the first client computer with a signature of the at least one comparison file to identify at least a subset of the files located at the first client computer that are similar to the at least one comparison file according to a comparison metric. The first client computer sends, to the coordinator computer, a response relating to the comparing.

Abstract: According to at least one embodiment, a method comprises observing communication from a virtual machine (VM) to a domain in which a device driver for a shared resource resides. The method further comprises determining, based on the observed communication, CPU utilization of the domain that is attributable to the VM. According to at least one embodiment, a system comprises a Central Processing Unit (CPU), Virtual Machines (VMs), and a domain in which a device driver for a shared resource resides, wherein the domain is operable to receive requests from the VMs for access to the shared resource. The system further comprises a CPU utilization monitor operable to determine an amount of CPU utilization of the domain in processing the received requests that is attributable to each of the VMs.

Abstract: Systems and methods for managing admission of requests to a streaming media server are provided. In certain embodiments, a method comprises receiving a new request for a streaming file to be served by a media server, and determining a cost to the media server for serving the requested streaming file, wherein the cost corresponds to the media server's resources to be consumed in serving the requested streaming file. The method further comprises determining, based at least in part on the cost, whether to admit the new request for service by the media server. In certain embodiments, a method comprises receiving, at a time Tcur, a new request for a streaming file to be served by a media server, and creating a segment-based model of the media server's memory as of time Tcur. And, based at least in part on the segment-based model of the media server's memory, determining whether to accept the received request for service by the media server.

Abstract: Methods and systems for managing admission of requests to hosting services that share resources are provided. In certain embodiments, a method comprises allowing each of a plurality of hosting services access to any of a set of shared resources for serving their respective streaming files to clients. The method further comprises managing admission of client requests for streaming files to each of the plurality of hosting services to ensure that a desired amount of usage of the shared resources is available to each hosting service.

Abstract: A method comprises receiving a representative workload of a computing system, where the representative workload comprises a plurality of composite transactions. In certain embodiments, the representative workload is a historical workload of a computing system. In general, a composite transaction refers to a transaction that comprises a plurality of embedded transactions. The method further comprises determining a subset of the plurality of composite transactions for which a corresponding resource cost is to be determined; and determining, based at least in part on a statistical regression-based analysis, a resource cost for the composite transaction(s) in the determined subset, where the resource cost reflects an amount of utilization of at least one resource of the computing system in serving the composite transaction(s).

Abstract: According to at least one embodiment, a method comprises observing communication from a virtual machine (VM) to an isolated driver domain. The method further comprises determining, based on the observed communication, CPU utilization of the isolated driver domain that is attributable to the VM. According to at least one embodiment, a system comprises a Central Processing Unit (CPU), Virtual Machines (VMs), and a first isolated driver domain in which a first device driver for a first shared resource resides, wherein the first isolated driver domain is operable to receive requests from the VMs for access to the first shared resource. The system further comprises a CPU utilization monitor operable to determine an amount of CPU utilization of the first isolated driver domain in processing the received requests that is attributable to a VM requesting access to the first shared resource.

Abstract: A system for managing resources automatically among nodes includes a node controller configured to dynamically manage allocation of node resources to individual workloads, where each of the nodes is contained in one of a plurality of pods. The system also includes a pod controller configured to manage live migration of workloads between nodes within one of the plurality of pods, where the plurality of pods are contained in a pod set. The system further includes a pod set controller configured to manage capacity planning for the pods contained in the pod set. The node controller, the pod controller and the pod set controller are interfaced with each other to enable the controllers to meet common service policies in an automated manner. The node controller, the pod controller and the pod set controller are also interfaced with a common user interface to receive service policy information.

Abstract: Embodiments of the present invention recite a system and computer-implemented method for sizing enterprise-application systems. In one embodiment of the present invention, a ratio of a plurality of pre-defined benchmarks is determined. The workload of the ratio-of pre-defined benchmarks corresponds to a desired workload of an enterprise application system. The ratio of the plurality of pre-defined benchmarks is then used as a second benchmark for testing the enterprise application system.

Abstract: One embodiment is a method that determines application performance signatures occurring at an application server in a multi-tier architecture. The method then analyzes the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application.

Abstract: One embodiment collects performance data for an application server that processes transactions received from a client computer to a database server. An application log is created from the performance data and used for capacity planning in a multi-tiered architecture.

Abstract: Described herein is a method for optimizing a prediction of resource usage of multiple applications running in a virtual environment, comprising: providing a predetermined set of benchmarks; executing the predetermined set of benchmarks in a native hardware system in which the application natively resides; executing the predetermined set of benchmarks in the virtual environment; collecting first traces of first resource utilization metrics in the native hardware system based on the execution of the predetermined set of benchmarks in the native hardware system; collecting second traces of second 10 resource utilization metrics in the virtual environment based on the execution of the predetermined set of benchmarks in the virtual environment; generating a first prediction model that maps a first selected set of the first traces of a selected one of the first resource utilization metrics to the second traces of resource utilization metrics; generating a second prediction model that maps a second different select