Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria.

Abstract: A method of encoding knowledge is disclosed, which can be used to automatically detect problems in software application deployments. The method includes accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem. An encoded representation of the knowledge source is generated according to a predefined knowledge encoding methodology. The encoded representation is adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of the software application to detect whether the conditions and the problem exist therein.

Abstract: A rule stored in a tangible computer-readable memory is adapted to be programmatically applied by a computer to automatically detect occurrences of a particular problem in a deployment of a software application. The rule comprises a plurality of atomic gates and a plurality of operator gates. The atomic gates have predicates for detecting occurrences of a plurality of conditions in the software application deployment. The operator gates are configured to detect predefined logical combinations of outputs of the atomic gates to generate a rule output that indicates whether the problem is currently detected in the deployment. The rule contains a plurality of free logical variables which can be assigned values. The free logical variables are configured for use in input pattern matching and output binding substitutions to supply information to a remedy for the problem. Each substitution comprises an assignment of a value to a variable.

Abstract: Computer systems and methods are disclosed for managing a deployment of a software application. One system includes an application model describing the deployment, the application model comprising a representation of physical and logical objects in a domain of the deployment, configuration data about the objects, and information about relationships between the objects. The system also includes a root cause analysis module configured to identify one or more problematic objects of the application model, and to use pattern-recognition on the application model to find root cause candidates that may be a root cause of one or more problems associated with the problematic objects. The root cause analysis module can be further configured to apply diagnostic unit tests on one or more objects associated with the root cause candidates, the diagnostic unit tests configured to narrow down a list of possible root causes of the problems.

Abstract: A system for managing a deployment of a software application is disclosed. The system includes a telemetry component that collects data values of state metrics associated with the deployment, an application model that represents the deployment, a repository of encoded knowledge describing known problems associated with the software application, and an analysis subsystem that programmatically maps logical combinations of features associated with the deployment to known problems. The application model includes a representation of physical and logical objects in a domain of the deployment, and configuration data about the objects. The analysis subsystem is adapted to query the application model for information about the deployment. The application model can implement a discovery process to construct itself by using an abstract model of a generalized deployment of the software application, the discovery process including obtaining information from the managed deployment.

Abstract: A system for monitoring and analyzing a deployment of a software application is disclosed. The system includes a monitoring component that collects streams of data values of time-variant state metrics associated with the deployment, and a feature detector that analyzes the streams to identify features known to be associated with potential problems. Detected features can include deviations of a signal from a normalcy band, a rising or descending trend in signal behavior, deviations from seasonal or cyclical normalcy bands, and the like.

Abstract: Computer-implemented systems and methods for managing a deployment of a software application are disclosed. A method includes identifying problems with the deployment, each problem having a severity rating. For each identified problem, one or more associated remedies are identified, each remedy having a severity rating based on the severity rating of the problem with which the remedy is associated. The method further includes ranking the remedies based on the remedies' severity ratings. The remedies can be executed in order of rank. Also disclosed are systems and methods of preventing simultaneous execution of certain types of remedies, either on the deployment in general or on a set of components of the deployment. Also disclosed are methods for logging the results of executed remedies and their effect on deployment health.

Abstract: Systems and methods for managing a deployment of a software application are disclosed. One system comprises a machine-readable repository of rules describing problems associated with the software application, a monitoring component that collects state metrics from the deployment, and a problem detector that programmatically uses the rules to map combinations of the collected state metrics to problems.

Abstract: Systems and methods for obtaining information about a deployment of a software application are disclosed. One system comprises a plurality of deployment servers running components of the software application deployment, a plurality of monitors associated with the deployment servers, and an analysis subsystem that generates requests for state metrics from the deployment, based on rules describing known problems with the software application. The analysis subsystem transmits each request for state metrics to a monitor associated with a deployment server that is associated with the request. The monitors are configured to receive the requests for state metrics from the analysis subsystem and collect the state metrics from one of the components of the software application deployment. The monitors, which can reside on the deployment servers or locally with respect to the analysis subsystem, can transmit the collected state metrics back to the analysis subsystem.

Abstract: A system for monitoring and analyzing the operation of a deployment of a software application is disclosed. The system includes a monitoring component, a repository that stores a plurality of rules, and an analysis engine. The monitoring component collects data values of each of a plurality of state metrics associated with the deployment of the software application. At least some of the rules in the repository map respective combinations of states associated with the state metrics to corresponding problems. The analysis engine programmatically detects instances of said problems, at least in-part, by using the rules to analyze the state metric data values collected by the monitoring component. The rules can also include remedies associated with the detected problems, and the system may include remedy selection and execution modules.

Abstract: A method of encoding knowledge is disclosed, which can be used to automatically detect problems in software application deployments. The method includes accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem. An encoded representation of the knowledge source is generated according to a predefined knowledge encoding methodology. The encoded representation is adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of the software application to detect whether the conditions and the problem exist therein.