A system includes a network interface configured to communicate with a plurality of components across a network. The system also includes a memory system configured to store a plurality of instructions to implement a monitoring system and a processing system configured to communicate with the network interface. The processing device is further configured to execute the instructions to result in accessing one or more monitoring rules that define monitoring criteria associated with the components and monitoring the components to determine whether the monitoring criteria are met. The processing device can also trigger a notification to one or more user systems based on determining that at least one of the monitoring criteria has been met and provide a customization interface to allow user customization of the one or more monitoring rules.

Various methods, apparatuses, and media for notifying a user of an operational state of a web application are provided. Three values that relate to data caching, error occurrence, and data retrieval are used to determine the operational state. The methods may use a software module that is compatible with any React JavaScript application.

An example embodiment involves persistent storage defining a first configuration item representing an application deployed within a network, a second configuration item representing a software program that is deployable within the network, and a relationship between the first configuration item and the second configuration item. One or more processors may be configured to: (i) receive an indication that a change has been applied to the application or has been arranged to be applied to the application; (ii) identify the relationship between the first configuration item and the second configuration item; (iii) based on the relationship between the first configuration item and the second configuration item, determine that the change can affect operation of the software program; and (iv) in response to determining that the change can affect operation of the software program, provide a notification of the change to an agent associated with the software program.

System and methods are provided for detecting, tracking, and managing outages of transaction processors. An indication is received indicating a potential outage associated with a transaction processor computer configured to process transactions of an online retail website. The indication can be received from a threshold monitoring service and/or from a machine-learning detection system. A computing service can be initiated to confirm and track the outage over time. An outage may include a number of situations in which the transaction processor fails to process transactions according to a set of predefined processing parameters. If the outage spans a particular time period, the service can perform a number of remedial actions (e.g., notifying an administrator of the outage, etc.).

A method including receiving, from a user device, a user request to access data associated with a web page; generating, by a processor, a first transaction identification; collecting transaction information, the transaction information comprising server-side metrics; integrating, by the processor, the first transaction identification with the transaction information; transmitting, by the processor, the first transaction identification to the user device; receiving, from the user device, client-side data associated with a second transaction identification; integrating, by the processor, the server-side metrics and the client-side data; and analyzing, by the processor, the integrated server-side metrics and the client-side data.

A method for distributing an application for an edge computing device performed by a computing device according to an embodiment of the present invention includes selecting a cluster including two or more edge devices from among a plurality of edge devices, distributing a first application to a second edge device included in the cluster, modifying routing information such that a service request incoming to a first edge device included in the cluster is transmitted to the second edge device, and replacing the first application running in the first edge device with a second application.

A system analyzes periodically collected data associated with entities, for example, users, servers, or systems. The system determines anomalies associated with populations of entities. The system excludes anomalies from consideration to increase efficiency of execution. The system may rank the anomalies based on relevance scores. The system determines relevance scores based on various factors describing the sets of entities. The system may present information describing the anomalies based on the ranking. The system may use a machine learning based model for predicting likelihoods of outcomes associated with sets of entities. The system generates alerts for reporting the outcomes based on the predictions.

A method and apparatus using machine learning for scheduling server maintenance. In one embodiment of the method, load values for a server are recorded over a period of time, wherein each of the load values is time stamped with a date and time. A first plurality of the load values are classified. The classified first plurality of values are then processed to create a model for predicting a load value of the server. The model is used to generate a first predicted load value of the server for a first date and a first time.

Techniques for enabling secure access to data using data blocks is described. Computing device(s) can provide instruction(s) to a component associated with an entity, wherein the instruction(s) are associated with an identifier corresponding to a data block of a plurality of data blocks. The computing device(s) can receive, from the component, data associated with the component, wherein the data is associated with the identifier and is indicative of a state of the component. The computing device(s) can store the data in the data block and monitor, using rule(s), changes to the state of the component based at least partly on the data in the data block. As a result, techniques described herein enable near real-time—and in some examples, automatic—reporting and/or remediation for correcting changes to the state of the component using data that is securely accessed by use of data blocks.

The integrity of transmitted data can be protected by causing that data to be transmitted twice, and calculating protection information (PI) for the data from each transmission. The PI can include information such as a checksum or signature that should have the same value if the data from each transmission is the same. If the PI values are not the same, an error handling procedure can be activated, such as may retry the transmission. For write operations, the data can be transmitted twice from a source to a storage destination, while for read operations, the data can be transmitted to a recipient then sent back from the recipient to the storage device, with PI calculated for each transmission. A component such as a storage processor can perform at least this comparison step. Such approaches can also be used for network transmission or high performance computing.