Methods, systems, and computer programs are presented for estimating downtime and recovery time after a disaster. One method includes an operation for calculating component fragility functions for components of a facility that are vulnerable to damage after a disaster. Further, the method includes calculating component recovery functions for the components of the facility. The component recovery functions indicate a probability of recovery after a disaster over time. The method further includes operations for calculating a facility fragility function and a facility recovery function based on the component fragility functions and the component recovery functions, and for determining a downtime for the facility for a given intensity associated with the disaster. Further, the method includes an operation for causing presentation of the downtime for the facility on a user interface (UI).

Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

Various aspects of the disclosure relate to test automation systems with pre-compilers to validate various steps associated with a test script. An artificial intelligence (AI)-based pre-compiler may use natural language processing (NLP) to validate various steps associated with a test script associated with an application. Other aspects of this disclosure relate to automated encryption and mocking of test input data associated with test scripts.

A method for exchange of equipment performance data includes the steps of: obtaining performance data of a communicatively-insulated device; converting the performance data into a scannable code; capturing an image of the scannable code; decoding the scannable code using a communicatively-enabled device to extract an address string encoded in the scannable code, the address string comprising an address of a remote server and the performance data; initiating, by the communicatively-enabled device, a communications link with the remote server using the address string thereby to provide the performance data to the remote server; performing, by the remote server, analytics on the performance data; and sending historic device performance data and/or analytical results to a remote computing device and/or sending a link to the historic device performance data and/or analytical results to the remote computing device; wherein the communicatively-insulated device is packaging equipment and wherein obtaining the performance data comprises: running a calibration phantom through the packaging equipment; scanning the calibration phantom with a calibration unit; and using the calibration unit to generate a system status report identifying one or more operational parameters of the packaging equipment.

A system is configured to detect a small, but meaningful, anomaly within one or more metrics associated with a platform. The system displays visuals of the metrics so that a user monitoring the platform can effectively notice a problem associated with the anomaly and take appropriate action to remediate the problem. A first visual includes a radar-based visual that renders an object representing data for a set of metrics being monitored. A second visual includes a tree map visual that includes sections where each section is associated with an attribute used to compose the set of metrics. Via the display of the visuals, the techniques provide an improved way of representing a large number of metrics (e.g., hundreds, thousands, etc.) being monitored for a platform. Moreover, the techniques are configured to expose useful information associated with the platform in a manner that can be effectively interpreted by a user.

In one aspect, an example methodology implementing the disclosed techniques can include, by a baseboard management controller (BMC), responsive to a virtual console of a server being launched on a client device via the BMC, collecting one or more environment parameters of the client device and collecting one or more environmental parameters of the server. The method can also include, by the BMC, determining an appropriate display configuration for the server based on an analysis of the one or more environment parameters of the client device and the one or more environmental parameters of the server and configuring a display configuration of the server in accordance with the determined appropriate display configuration.

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

A facility management system comprises a server, a biometric identification unit, and a processing circuit. The server is configured to store a list of registered users, and biometric information and access rights pertaining to each registered users. The biometric identification unit is associated with the building equipment. The biometric identification unit is enabled to facilitate a user desiring access to the associated building equipment to scan at least one biometric parameter, and subsequent to scanning of the biometric parameter the biometric identification unit is configured to generate a scanned biometric information. The processing circuit is communicatively coupled with the server and the biometric identification unit, and is configured to: authenticate the user based on the biometric information and the scanned biometric information; determine the access rights for the authenticated user; and subsequently provide access to the authenticated user to operate the associated building equipment based on the determined access rights.

Various systems and methods are provided for analyzing the effect(s) that a configuration change to one device has on other connected devices. In one embodiment, the disclosed functionality includes determining connectivity information associated with a data center, where the data center comprises at least a first device and a second device; discovering one or more changes to a configuration of the first device; determining, based at least in part on the connectivity information, that the second device is impacted by the one or more changes to the configuration of the first device; and determining one or more impacts to the second device as a result of the one or more changes, where each of the one or more impacts indicates a positive impact to the second device, a negative impact to the second device, or no impact to the second device.

The present approach relates to event monitoring and management of an instance using a generated service map, allowing monitoring of CIs (e.g., applications) and connections that are currently active in a user's specific instance. A self-monitoring solution is generated for a user (e.g., via an application) that depicts status, configuration, and errors related to the user's instance. In certain implementations, the present techniques involve applying internal knowledge of the working of a user's instance and applications to perform the self-monitoring, and determine when an alert should be generated. Further, the present techniques may involve making a determination to provide a user with a self-help solution in addition or based on the self-monitoring of the user's instance.