Abstract: In one embodiment, a method may comprise receiving a query to search for one or more entities of the data center, the query including one or more query tokens. The method may then identify one or more entity-type nodes corresponding to the query, and rank the entity-type nodes based on a score determined for each of the identified entity-type nodes. For at least a portion of the ranked entity-type nodes, the method may generate a structured query associated with each of the entity-type nodes based at least in part of one or more activity-type nodes connected to each of the entity-type nodes. Then, the method may retrieve, based on the structured queries, results from one or more databases.

Abstract: Systems for distributed data storage. A method embodiment commences upon capturing a history of storage I/O activity over a recent time period. A predictive model is derived from the captured storage I/O activity, and the predictive model is then used for predicting future storage I/O activity. A set of snapshot planning parameters comprising objectives (e.g., to minimize costs or to maximize likelihood completing a snapshot activity by a prescribed time) and/or constraints (e.g., don't wait more than one day to start a snapshot) are applied to the predicted storage I/O characteristics to generate a set of feasible snapshot plans. One of the feasible snapshot plans is selected for scheduling so as to begin the planned snapshot activity at a prescribed time. The snapshot planning parameters are normalized based on the predicted storage I/O characteristics.

Abstract: Systems for distributed resource system management. A first computing system operates in a first computing environment. A predictive model is trained in the first computing environment to form a trained resource performance predictive model that comprises a set of trained model parameters to capture at least computing and storage IO parameters that are responsive to execution of one or more workloads that consume computing and storage resources in the first computing environment. When the trained resource performance predictive model is deployed to a second computing environment, various computing system configuration differences, and/or workload differences and/or other differences between the first computing environment and the second computing environment are detected and measured.

Abstract: A system for implementing seasonal time series analysis and forecasting using a distributed tournament selection process. Time series analysis is initiated by a prediction or runway event trigger. Prediction events include a determination of the availability of one or more resources at a given point in time or over a given time period. A runway event may include a determination of when a resource is below a minimum threshold level of availability. Training of the prediction models is based data taken from different time periods, accounting for any combination of time periods and/or for differing sampling frequencies or ranges. Processes for prosecuting a tournament to identify winning models are parallelized to achieve low latency tournament results. Ranking of each model and/or some combination of models is based on how precisely and/or conclusively the models match a determined set of training data.

Abstract: A method for time series analysis of time-oriented usage data pertaining to computing resources of a computing system. A method embodiment commences upon collecting time series datasets, individual ones of the time series datasets comprising time-oriented usage data of a respective individual computing resource. A plurality of prediction models are trained using portions of time-oriented data. The trained models are evaluated to determine quantitative measures pertaining to predictive accuracy. One of the trained models is selected and then applied over another time series dataset of the individual resource to generate a plurality of individual resource usage predictions. The individual resource usage predictions are used to calculate seasonally-adjusted resource usage demand amounts over a future time period. The resource usage demand amounts are compared to availability of the resource to form a runway that refers to a future time period when the resource is predicted to be demanded to its capacity.

Abstract: Systems for computing cluster management. One embodiment commences upon receiving a set of observed workload parameters corresponding to one or more observable workloads that run in a computing cluster. While the workloads are running, workload stimulus and cluster response observations are taken and used to generate a workload resource usage predictive model based on mappings or correlations between the observable workloads parameters and observed resource usage measurements. A set of planned workloads are applied to the workload resource usage predictive model to predict a set of corresponding predicted resource usage demands. The predicted resource usage demands are then mapped to a set of recommended hardware to form resource deployment recommendations that satisfy at least some of the corresponding resource usage demands while also observing a set of hardware model compatibility constraints.

Abstract: Resource allocation techniques for distributed data storage. A set of distributed storage system historical resource usage measurements are collected and stored using distributed storage system measurement techniques. The resource usage metrics are associated with and/or derived from processing entities in the distributed storage computing system. An analysis module determines a training window time period corresponding to a portion of the collected distributed storage system historical resource usage measurements. The training window time period is determined so as to provide an earlier time boundary and a later time boundary that defines a periodically recurring portion of the distributed storage system historical resource usage measurements. A latest cycle of those periodically recurring measurements are then used to train a predictive model, which in turn is used to produce distributed storage system predicted resource usage characteristics.

Abstract: A system and method include receiving, by a search system of a virtual computing system, a search query via a search console, converting the search query into a structured query, and retrieving search results based on the structured query. The system and method further include activating a subset of widgets that satisfy a condition based on the search results and determining a view for each activated widget. Each widget is configured to display a particular type of the search results and the view for each widget is based upon a number of the search results of the particular type that the widget is configured to display. The system and method additionally include displaying the activated widget on the search console according to the view of that widget.

Abstract: Systems for alerting in computing systems. A method commences by defining a plurality of analysis zones bounded by respective ranges of system metric values, which ranges in turn correspond a plurality of system behavior classifications. System observations are taken while the computing system is running. A system observation comprising a measured metric value is classified into one or more of the behavior classifications. Based on the classification, one or more alert analysis processes are invoked to analyze the system observation and make a remediation recommendation. An alert or remediation is raised or suppressed based on one or more zone-based analysis outcomes. An alert is raised when anomalous behavior is detected. The system makes ongoing observations to learn how and when to classify a measured metric value into normal or anomalous behaviors. As changes occur in the system configuration, the analysis zones are adjusted to reflect changing bounds of the zones.

Abstract: In one embodiment, a system includes a cluster of host machines implementing a virtualization environment. Each host machine a hypervisor, a user virtual machine (UVM), a connection manager, an I/O controller, and a virtual disk. The virtual environment may include storage devices and may be accessible by all of the I/O controllers. A management module of the virtualization environment may display a graphical user interface that includes an alert rule configuration interface, which may be operable to configure one or more alert policies each associated with an operating status of a component of the virtualization environment. The management module may receive inputs associated with the alert policies. The management module may update the alert policies in accordance with the inputs.

Abstract: A system and method include receiving, by a troubleshooting system of a virtual computing system, a search query for troubleshooting a problem associated with a component of the virtual computing system. The search query is received via a troubleshooting interface of the troubleshooting system. The system and method also include parsing the search query, including associating a troubleshooting category with the parsed search query, determining possible causes of the problem from the troubleshooting category, and ranking the possible causes based on a pre-determined criteria. The system and method additionally include displaying a subset of highest ranked possible causes of the problem on the troubleshooting interface.

Abstract: A system and method include receiving, by a navigation and search system of a virtual computing system, a user input via a navigation interface of the navigation and search system. The system and method also include retrieving a page corresponding to the user input, parsing the user input and associating one or more keywords with the user input for obtaining a structured query, including associating the page with the structured query, and displaying the page in the navigation interface. The system and method further include populating the structured query into a search interface of the navigation and search system. Either the user input via the navigation interface or the structured query via the search interface are usable to navigate to the page.

Abstract: An illustrative embodiment disclosed herein is a method by a data analytics chip, including finding a contention within a first predetermined amount of time, sorting user virtual machines based on consumption of each of the user virtual machines, and identifying a first subset of the user virtual machines. The first subset of the plurality of user virtual machines satisfies consumption criteria.

Abstract: Systems and methods for “what-if” scenario planning of a distributed data storage system. A scenario planning engine has a user interface to facilitate user interactions to describe “what if” scenarios. A method comprises steps to collect system performance measurements pertaining to measurable characteristics of the distributed storage system. A predictive model is generated and formatted for use as a predictor of one or more predictive model parameters that are derived from the collected system performance measurements and/or any calculated predictions and/or correlations. A user can vary a set of scenario input parameters so as to characterize one or more “what if” scenarios. The user-defined scenario input parameters are formatted and used as predictive model inputs. The predictive model is used to simulate predicted system performance parameters corresponding to respective “what-if” planning scenarios.

Abstract: Systems and methods for scheduling storage management tasks over predicted user tasks in a distributed storage system. A method commences upon receiving a set of historical stimulus records that characterize management tasks that are run in the storage system. A corresponding set of historical response records comprising system metrics associated with execution of the system tasks is also received. A learning model is formed from the stimulus records and the response records and formatted to be used as a predictor. A set of forecasted user tasks is input as new stimulus records to the predictor to determine a set of forecasted system metrics that would result from running the forecasted user tasks. Management tasks are selected so as not to impact the forecasted user tasks. Management tasks can be selected based on non-contentions resource usage between historical management task resource usage and predictions of resource usage by the user tasks.

Abstract: A system and method include receiving, by a search computing system of a virtual computing system, a search query via a search interface, converting the search query into a structured query that identifies at least one primary entity within the virtual computing system, and determining at least one related entity from the at least one primary entity. The system and method further include generating search results from the at least one primary entity and the at least one related entity, ranking the at least one primary entity and the at least one related entity by popularity, ranking the search results based on a criteria for each of the at least one primary entity and the at least one related entity while maintaining the popularity ranking, and displaying the ranked search results on the search interface.

Abstract: A system and method include receiving, by a virtual computing system, a search query via a search interface of a search computing system, converting the search query into a primary structured query that identifies a primary entity within the virtual computing system and an activity type associated with the primary entity. The system and method also include generating a subquery from the primary structured query, including associating the activity type of the primary entity with the subquery, such that the subquery identifies a related entity of the primary entity, generating search results from the primary entity and the related entity corresponding to the activity type included in the primary structured query and the subquery, and displaying the search results on the search interface for monitoring components of a datacenter.

Abstract: A system and method includes receiving, by a search computing system of a virtual computing system, a search query, converting the search query into a structured query, and identifying at least one of a configured metric, a learned metric, and a correlation from the structured query. The configured metric, learned metric, and correlation are based upon a particular metric associated with a component of the virtual computing system. The configured metric is obtained by applying filters to the particular metric, the learned metric is based upon a frequency of presence of the particular metric in the search query, and the correlation is based upon a pattern formed by the search query in conjunction with a subset of prior search queries. The system and method further include displaying data related to the particular metric, such that the data is based upon the configured metric, the learned metric, and the correlation.

Abstract: Systems and methods for scheduling storage management tasks over predicted user tasks in a distributed storage system. A method commences upon receiving a set of historical stimulus records that characterize management tasks that are run in the storage system. A corresponding set of historical response records comprising system metrics associated with execution of the system tasks is also received. A learning model is formed from the stimulus records and the response records and formatted to be used as a predictor. A set of forecasted user tasks is input as new stimulus records to the predictor to determine a set of forecasted system metrics that would result from running the forecasted user tasks. Management tasks are selected so as not to impact the forecasted user tasks. Management tasks can be selected based on non-contentions resource usage between historical management task resource usage and predictions of resource usage by the user tasks.

Abstract: A system and method for generating and executing rules in a virtual computing system includes creating, by a rules computing system of the virtual computing system, a rule based upon one or more search queries entered into a search interface of the virtual computing system. The system and method also include executing, by the rules computing system, the rule periodically for identifying violations of the rule, and issuing, by the rules computing system, an alert for the violations of the rule on the search interface.