A server system including a first server to execute first role, other server to execute at other role, spare server and management layer server. The management layer server is configured to allocate first group of users to access first server and other group of users to access other server, receive status information sent by first server and status information sent by other server, analyse status information to determine an operational status of first server and operational status of other server, update role of spare server to first role when operational status of first server indicates failed state and reallocate first group of users to the spare server, and update a role of another spare server to the other role when the operational status of the other server indicates a failed state and reallocate the other group of users to the other spare server.

To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

A system for container migration includes containers running instances of an application running on a cluster, an orchestrator with a controller, a memory, and a processor in communication with the memory. The processor executes to monitor a vitality metric of the application. The vitality metric indicates that the application is in either a live state or a dead state. Additionally, horizontal scaling for the application is disabled and the application is scaled-down until the vitality metric indicates that the application is in the dead state. Responsive to the vitality metric indicating that the application is in the dead state, the application is scaled-up until the vitality metric indicates that the application is in the live state. Also, responsive to the vitality metric indication transitioning from the dead state to the live state, the application is migrated to a different cluster while the horizontal scaling of the application is disabled.

A computer-implemented system for dynamic aggregation of data and minimization of data loss is disclosed. The system may be configured to perform instructions for: aggregating information from a plurality of networked systems by collecting a set of data from the networked systems, the set of data comprising data associated with a predetermined period of time and comprising one or more central variables that are included in data associated with more than one networked systems of the plurality of networked systems and one or more associated variables that describe one or more aspects of the central variables; retrieving one or more data transformation rules based on a relational map among the central variables and the associated variables; and aggregating the first set of data into one or more master data structures corresponding to the central variables based on the data transformation rules.

A method for execution by a query processing system includes determining a query request that indicates a plurality of operators, where the plurality of operators includes at least one relational algebra operator and further includes at least one non-relational operator. A query operator execution flow is generated from the query request that indicates a serialized ordering of the plurality of operators. A query resultant of the query is generated by facilitating execution of the query via a set of nodes of a database system that each perform a plurality of operator executions in accordance with the query operator execution flow, where a subset of the set of nodes each execute at least one operator execution corresponding to the at least one non-relational operator in accordance with the execution of the query.

Aspects of the present disclosure involve a system and method for performing operations comprising providing to a client device, a messaging application comprising multiple features; accessing a configuration rule that associates a device property rule with a feature; determining at a first point in time, that a property of the client device matches the device property rule associated with the configuration rule; in response to determining that the property of the client device matches the device property rule associated with the configuration rule, enabling the feature on the client device at the first point in time; receiving an updated property of the client device at a second point in time; and in response to determining that the updated property of the client device fails to match the device property rule associated with the configuration rule at the second point in time, disabling the feature on the client device.

A system for monitoring a plurality of machines of a facility is disclosed. The system comprises a plurality of data network devices configured to communicate with one another via at least one network. The data network devices are configured to collect machine data from the plurality of machines and distribute the machine data via the at least one network. The system further comprises data display devices configured to provide a graphical user interface that enables a user to view and analyze the machine data that is collected and distributed by the data network devices.

Requests are received for handling by a cloud computing environment which are then executed by the cloud computing environment. While each request is executing, performance metrics associated with the request are monitored. A vector is subsequently generated that encapsulates information associated with the request including the text within the request and the corresponding monitored performance metrics. Each request is then assigned (after it has been executed) to either a normal request cluster or an abnormal request cluster based on which cluster has a nearest mean relative to the corresponding vector. In addition, data can be provided that characterizes requests assigned to the abnormal request cluster. Related apparatus, systems, techniques and articles are also described.

A patient record gateway of an electronic health record system can be validated using a conformance statement that defines capabilities and characteristics of patient record servers associated with the gateway. Part of validating the patient record gateway includes performing a configuration test of the patient record gateway using the conformance statement.

A technique includes accessing, by at least one hardware processor, a recorded request and a recorded response associated with an integration test involving a first computer system and a second computer system. The recorded request was previously issued by the first computer system to the second computer system to cause the second computer system to provide the recorded response. The technique includes, in a virtualized integration test involving the second computer system and initiated using the recorded request, comparing, by the hardware processor(s), the recorded response to a request produced by the second computer system in the virtualized integration test. The technique includes identifying, by the hardware processor(s), an action taken by the second computer system as being likely to be associated with a regression based on the comparison.