12 results about "Application performance management" patented technology

The present disclosure pertains to systems, computer program products, and methods for an automated mesh service-based deployment intelligence system. This system is designed to streamline the deployment of software by integrating a processing device and a non-transitory storage device. The storage device contains instructions that, when executed by the processing device, enable the ingestion of data from various sources such as monitoring systems, databases, and application performance management tools. Once ingested, the data is stored and processed to discern deployment patterns and detect any anomalies. Utilizing a machine learning model, the system anticipates potential deployment issues by analyzing this data. It then orchestrates the deployment of software artifacts accordingly, taking into account the insights gained from the machine learning model. Furthermore, the system is capable of real-time optimization of the deployment process to preemptively resolve any predicted issues, thereby enhancing the efficiency and reliability of software deployment operations.

A system for evaluating and managing system performance of one or more customer systems, the system comprising: a repository for storing one or more objects; a gateway communicatively coupled to a customer system, the customer system separated from a wide area network by a firewall, and including one or more computer systems and databases within a customer premises, the gateway comprising a plurality of adapters configured to translate commands and data with system applications within a customer system without deploying agents within the customer system; a plurality of active objects configured to implement a plurality of workflows; one or more processors communicatively coupled to the memory and the gateway, the firewall being disposed between the gateway and the one or more processors, the one or more processors and the gateway being configured to: detect an alert that a monitoring policy related to a monitored event for the customer system has been violated, automatically generate and implement a corrective action workflow, and deploy the corrective action workflow through at least one of the plurality of active objects, wherein the corrective action workflows are assigned metadata via inputs and intelligent toolset to classify and categorize the metadata, and wherein the corrective action workflows are catalogued in a library and converted into model parameters, and wherein the detection of the alert is based on an inference.

Systems and methods for application performance management across one or more networks are disclosed. A system includes a plurality of geographically distributed computing devices executing one or more applications. A plurality of collectors are distributed across the one or more networks, each collector being positioned proximate a respective computing device. The collectors may sample, by each of the plurality of collectors, a plurality of trace events received from the applications executing on the computing devices proximate the collector. The collectors may retain in memory sampled trace events that meet a configurable attribute. The collectors may use probabilistic sets and tail-based sampling to determine root events and policies for identifying relevant traces. Benefits can be achieved in bandwidth savings, network cost and cyber security.

The disclosure provides a displaying method and apparatus for application performance management. The method comprises: obtaining data from a target application; mapping the data into a plurality of dimensions; displaying a plurality of layers corresponding to the plurality of dimensions; an displaying, based on a dimension associated with an object supported by the target application, a visualized node corresponding to the object at a corresponding layer of the plurality of layers.

The embodiment of the invention provides an application performance intelligent diagnosis method and system, and belongs to the technical field of application performance detection. The method comprises the following steps: constructing a standardized data set based on performance data collected by an application performance management tool; inputting the standardized data set into a tool capability graph constructed by a model context protocol, and establishing a mapping index from data to a tool; analyzing performance abnormity or a diagnosis request triggered by the standardized data set based on a large language model, selecting and calling a diagnosis tool according to the mapping index, and executing a dynamic diagnosis plan to obtain an analysis result; multiple rounds of reasoning and confidence evaluation are carried out based on the analysis result, the tool calling sequence is adjusted according to the calling characteristics, and the diagnosis plan is updated until a root cause diagnosis conclusion is output; and generating a diagnosis evidence packet based on the root cause diagnosis conclusion, and outputting the diagnosis evidence packet as a final diagnosis result. According to the scheme of the invention, high-precision, traceable and self-adaptive evolution performance root cause intelligent identification is realized in a complex application environment.

Systems, computer program products, and methods for an automated mesh service-based deployment intelligence system are provided. This system is designed to streamline the deployment of software by integrating a processing device and a non-transitory storage device. The storage device contains instructions that, when executed by the processing device, enable the ingestion of data from various sources such as monitoring systems, databases, and application performance management tools. Once ingested, the data is stored and processed to discern deployment patterns and detect any anomalies. Utilizing a machine learning model, the system anticipates potential deployment issues by analyzing this data. It then orchestrates the deployment of software artifacts accordingly, taking into account the insights gained from the machine learning model. Furthermore, the system is capable of real-time optimization of the deployment process to preemptively resolve any predicted issues, thereby enhancing the efficiency and reliability of software deployment operations.

Systems and methods for application performance management across one or more networks are disclosed. A system includes a plurality of geographically distributed computing devices executing one or more applications. A plurality of collectors are distributed across the one or more networks, each collector being positioned proximate a respective computing device. The collectors may sample, by each of the plurality of collectors, a plurality of trace events received from the applications executing on the computing devices proximate the collector. The collectors may retain in memory sampled trace events that meet a configurable attribute. The collectors may use probabilistic sets and tail-based sampling to determine root events and policies for identifying relevant traces. Benefits can be achieved in bandwidth savings, network cost and cyber security.

The invention provides a cloud-based mobile phone application performance management system and method and electronic equipment, and the management system comprises a cloud virtualization module which is used for obtaining a virtual mobile phone instance group comprising a plurality of cloud virtual mobile phone instances based on cloud server resources; the dynamic priority module is used for acquiring task execution sequence information based on the data flow information of the mobile phone application and the resource demand of each task in the mobile phone application; the real-time monitoring module is used for acquiring abnormal performance state information of the mobile phone application based on the task execution sequence information and the performance parameters of the mobile phone application; and the task scheduling module is used for obtaining a task optimization scheduling scheme of the mobile phone application based on the abnormal performance state information, the task execution sequence information and the virtual mobile phone instance group. According to the method and the device, the running fluency, stability and efficiency of the mobile phone application can be remarkably improved, and better use experience is brought to a user.

The embodiments of the present disclosure provide a load balancing processing method and apparatus, a storage medium and an electronic device. The method includes: receiving a service request from a service consumer; acquiring performance statistics information of an application programming interface (API) gateway, and determining, according to the performance statistics information, whether the API gateway satisfies a loading condition of a reconfigured load balancing policy; and determining a target service provider instance according to pre-stored application performance management (APM) full information and the reconfigured load balancing policy in cases where the API gateway satisfies the loading condition, the target service provider instance being used for processing the service request.

The application relates to a public cloud multi-tenant performance monitoring method, device, equipment, storage medium and program product. The method comprises the following steps: collecting a plurality of low-level indexes of a cloud application runtime on a host of a target virtual machine node and a target virtual machine; the low-level indexes comprise at least one of CPU utilization, a hardware counter, a host resource state, resource usage characteristics, a hardware event vector and interference intensity; inputting the plurality of low-level indexes into a proxy model for performance evaluation to obtain a first evaluation result; the first evaluation result comprises a target performance degradation estimation value, a performance degradation reason of the cloud application and a contribution degree of the degradation reason; the target performance degradation estimation value is used for representing a degradation degree of the cloud application; and performing degradation evaluation according to the first evaluation result to obtain a second evaluation result. The above method improves the resource utilization rate and cost efficiency of the public cloud infrastructure, and further enhances the foresight and accuracy of cloud application performance management.

The disclosed computer-implemented method may include receiving telemetry data from a devices corresponding to a computing item and predicting performance factors for the computing item using the received telemetry data. The method may also include generate a weighting scheme and applying the weighting scheme to the performance factors to determine a performance metric for the computing item. Various other methods, systems, and computer-readable media are also disclosed.