Abstract: Information technology resource forecasting based on time series analysis is described. A system creates multiple forecasts for an information technology resource by applying corresponding multiple time series models to first data associated with the information technology resource. The system selects a model of the multiple time series models by comparing the multiple forecasts for the information technology resource to second data associated with the information technology resource. The system outputs a forecast that is created by applying the selected model to third data associated with the information technology resource.

Abstract: Described is a system and method that provides a data protection risk assessment for the overall functioning of a backup and recovery system. Accordingly, the system may provide a single overall risk assessment score that provide an operator with an “at-a-glance” overview of the entire system. Moreover, the system may account for changes that occur over time based on leveraging statistical methods to automatically generate assessment scores for various components (e.g. application, server, network, load, etc.). In order to determine a risk assessment score, the system may utilize a predictive model based on historical data. Accordingly, residual values for newly observed data may be determined using the predictive model and the system may identify potentially anomalous or high risk indicators.

Abstract: An alert configuration system facilitates accurate and reliable configuration of alerts for data protection policy in a data protection system, including eliminating or reducing manual configuration of data protection policy. The system identifies risks through trend analysis and behavioral statistics as applied to historical data, and automatically configures alerts for the identified risks so that alerts are generated upon detection of the identified risks. After detecting differences between tracked values for a data protection system and predicted values obtained through trend analysis and behavioral statistics as applied to the historical data, the alert configuration system automatically adjusts the configuration of alerts for data protection policy in accordance with the predicted values.

Abstract: One embodiment is related to a method for setting a tenant context for an application in a multi-tenancy environment, comprising: identifying a tenant identity for a tenant request, wherein the tenant identity is included in the tenant request; and setting a proper context for a first service of the application based on the identified tenant identity.

Abstract: Data compression optimization based on client clusters is described. A system identifies a cluster of similar client devices in a group of client devices, by comparing data compression factors that correspond to each client device in the group of client devices. The system identifies a relationship between data compression factors corresponding to the cluster and data compression ratios corresponding to the cluster. The system identifies a client device, in the cluster, which corresponds to a data compression ratio that is inefficient relative to other compression ratios corresponding to other client devices in the cluster. The system outputs a data compression recommendation for the client device, based on data compression factors corresponding to the client device and the identified relationship between the data compression factors corresponding to the cluster and the data compression ratios corresponding to the cluster.

Abstract: Detection of a cause of an error occurring in a data center is provided. A time period between a failure event in the data center and a previous successful event is determined. A set of devices involved in the failure event is generated using a data protection advisor (DPA). Data collected for the set of devices during the determined time period is scanned to detect at least one configuration change made during the determined time period. Based on a result of the scanned collected data, the at least one configuration change is displayed as a potential root cause of the error.

Abstract: Embodiments include detecting anomalies in an IT environment using model competition and business patterns by collecting time series data for events for the network including devices and interfaces. An analytics module uses competing time series models with customizable business patterns to find the best fit model. It analyzes the residuals of the best fitting model to find the outliers relative to normal zone data points. A user may classify a detected outlier as normal, in which case, the tracking and investigation mechanism suggests alternate business patterns to be matched against this outlier. A user interface displays a dashboard to present the user with anomalies in the chosen time series, such as in interactive graphical format.

Abstract: In one embodiment, systems and methods are provided for configuring multiple network interfaces based on a network profile. In one embodiment, a user interface module manages the creation, modification, and deletion of active and inactive profiles, which may be stored to a configuration file accessible to computers with network interfaces belonging to the respective profiles, such as homogeneous or heterogeneous nodes in a clustered network of computers. In one embodiment, a configuration module reads a configuration file with embedded network profiles and builds the appropriate network interfaces according to the interface parameters specified in the network profiles.

Abstract: In one embodiment, systems and methods are provided for configuring multiple network interfaces based on a network profile. In one embodiment, a user interface module manages the creation, modification, and deletion of active and inactive profiles, which may be stored to a configuration file accessible to computers with network interfaces belonging to the respective profiles, such as homogeneous or heterogeneous nodes in a clustered network of computers. In one embodiment, a configuration module reads a configuration file with embedded network profiles and builds the appropriate network interfaces according to the interface parameters specified in the network profiles.