A computing platform may be configured to (i) receive metric data for a metric that was produced by a metric producer, (ii) identify a metric handling rule that applies to the metric, wherein the identified metric handling rule comprises a handling action of storing metric data for the metric in a specified storage location (e.g., a different tier of a multi-tier storage architecture), and (iii) handle the received metric data for the metric in accordance with the identified metric handling rule by storing the received metric data in the specified storage location.
A computing system configured to (i) obtain a set of key-value pairs, wherein each key- value pair corresponds to a respective timestamp in a period of time, (ii) for at least one timestamp in the given period of time: (a) identify a first subset of the key-value pairs corresponding to the timestamp, (b) sort the first subset, and (c) generate a subset of compression values for the sorted first subset, (iii) for at least one key: (a) identify a second subset of the key-value pairs corresponding to the key, (b) sort the second subset, and (c) generate a subset of compression values for the sorted second subset, and (iv) store a set of compression values comprising (a) the subset of compression values that is generated for each of the at least one timestamp and (b) the subset of compression values that is generated for each of the at least one key.
A computing platform may be configured to (i) receive a log entry that was produced by a log producer, wherein the log entry comprises one or more data elements, (ii) produce a restructured representation of the log entry, the restructured representation comprising a sequence of one or more tokens that represent the one or more data elements of the log entry, (iii) based on the restructured representation of the log entry, determine a log identity of the log entry, and (iv) handle the log entry in accordance with a handling rule for the determined log identity.
A computing system configured to (i) present a user interface (UI) for creating a rule related to observability behavior of a software application, (ii) receive a first set of user inputs for creating a first UI element representing a trigger-event condition to be added to the rule, (iii) create the first UI element, (iv) receive a second set of user inputs for creating a second UI element representing an action to be added to the rule, (v) create the second UI element, and (vi) send, to a computing platform associated with a software provider of the software application, a request to deploy the rule and thereby cause the computing platform to deploy the rule to a set of computing devices installed with the software application, wherein the rule is defined to include the trigger-event condition represented by the first UI element and the action represented by the second UI element.
A client device installed with a client application having a graphical user interface (GUI) may be configured to (i) at a given time during a runtime session of the client application, identify a set of GUI elements within the GUI of the client application that is to be represented in a generic visualization of the GUI, (ii) generate a dataset that encodes the generic visualization of the GUI, wherein the generated dataset comprises a respective data structure for each GUI element in the identified set that encodes information for rendering a generic representation of the GUI element, and (iii) after generating the dataset that encodes the generic visualization of the GUI, transmit the generated dataset that encodes the generic visualization of the GUI to a back-end platform associated with a provider of the client application.
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
6.
INTELLIGENTLY GENERATING AND DEPLOYING A METRIC BLOCKLIST WITHIN A DISTRIBUTED COMPUTING SYSTEM TO EFFICIENTLY MANAGE DATA METRIC REQUESTS
The present disclosure relates to systems, non-transitory computer-readable media, and methods for improving the efficiency and flexibility of implementing computer devices by intelligently generating a metric blocklist based on predicted utilization of digital metrics and deploying the metric blocklist at one or more computing devices to limit digital metric requests to distributed databases. In particular, in one or more embodiments, the disclosed systems monitor historical digital metric utilization and apply a prediction model to generate a metric blocklist of digital metrics that are not likely to be utilized by one or more metric requesting devices of a distributed computing system. The disclosed systems can deploy the metric blocklist to computing devices of a distributed computing system to efficiently limit digital requests, processing resources, bandwidth consumption, and storage load with regard to utilization of metric storage devices (e.g., time-series databases).
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
7.
Systems and methods for reducing the cardinality of metrics queries
A computing platform may be configured to (i) perform an analysis of a saved query comprising an expression that specifies a set of one or more unique metrics for which metric data is to be fetched from a metrics management platform when the saved query is run, (ii) determine a strategy for reducing a cardinality level of the saved query based at least in part on the analysis of the saved query, and (iii) cause the saved query to be modified in accordance with the determined strategy for reducing the cardinality level of the saved query.
A computing platform may be configured to (i) receive metric data for a metric that was produced by a metric producer, (ii) identify a metric handling rule that applies to the metric, wherein the identified metric handling rule comprises a handling action of storing metric data for the metric in a specified storage location (e.g., a different tier of a multi-tier storage architecture), and (iii) handle the received metric data for the metric in accordance with the identified metric handling rule by storing the received metric data in the specified storage location.
A computing platform may be configured to (i) receive metric data for a metric that was produced by a metric producer, (ii) identify a metric handling rule that applies to the metric, wherein the identified metric handling rule comprises a handling action of storing metric data for the metric in a specified storage location (e.g., a different tier of a multi-tier storage architecture), and (iii) handle the received metric data for the metric in accordance with the identified metric handling rule by storing the received metric data in the specified storage location.
A computing platform may be configured to (i) perform an analysis of a saved query comprising an expression that specifies a set of one or more unique metrics for which metric data is to be fetched from a metrics management platform when the saved query is run, (ii) determine a strategy for reducing a cardinality level of the saved query based at least in part on the analysis of the saved query, and (iii) cause the saved query to be modified in accordance with the determined strategy for reducing the cardinality level of the saved query.
A computing platform may be configured to (i) perform an analysis of a saved query comprising an expression that specifies a set of one or more unique metrics for which metric data is to be fetched from a metrics management platform when the saved query is run, (ii) determine a strategy for reducing a cardinality level of the saved query based at least in part on the analysis of the saved query, and (iii) cause the saved query to be modified in accordance with the determined strategy for reducing the cardinality level of the saved query.
A computing system configured to (i) obtain a set of key-value pairs, wherein each key-value pair corresponds to a respective timestamp in a period of time, (ii) for at least one timestamp in the given period of time: (a) identify a first subset of the key-value pairs corresponding to the timestamp, (b) sort the first subset, and (c) generate a subset of compression values for the sorted first subset, (iii) for at least one key: (a) identify a second subset of the key-value pairs corresponding to the key, (b) sort the second subset, and (c) generate a subset of compression values for the sorted second subset, and (iv) store a set of compression values comprising (a) the subset of compression values that is generated for each of the at least one timestamp and (b) the subset of compression values that is generated for each of the at least one key.
A computing platform may be configured to (i) receive a log entry that was produced by a log producer, wherein the log entry comprises one or more data elements, (ii) produce a restructured representation of the log entry, the restructured representation comprising a sequence of one or more tokens that represent the one or more data elements of the log entry, (iii) based on the restructured representation of the log entry, determine a log identity of the log entry, and (iv) handle the log entry in accordance with a handling rule for the determined log identity.
A computing platform may be configured to (i) receive a log entry that was produced by a log producer, wherein the log entry comprises one or more data elements, (ii) produce a restructured representation of the log entry, the restructured representation comprising a sequence of one or more tokens that represent the one or more data elements of the log entry, (iii) based on the restructured representation of the log entry, determine a log identity of the log entry, and (iv) handle the log entry in accordance with a handling rule for the determined log identity.
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
H04L 41/069 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant des journaux de notificationsPost-traitement des notifications
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for remote observation of hardware,
computer applications, systems and networks; downloadable
software for collecting, indexing, searching, monitoring and
analyzing data generated by hardware, computer applications,
systems and networks; downloadable software for providing
operational intelligence, business analytics, security
information, troubleshooting, and monitoring based on client
data; downloadable software for collecting, sorting,
searching, processing, encrypting, transmitting, routing,
reporting, visualizing, and analyzing software and computer
hardware data from multiple sources and in structured and
unstructured formats; downloadable software for tracing,
detecting, discovering, testing, monitoring, analyzing,
modeling, diagnosing, notifying and reporting the
performance, availability, dependencies, functionality,
behavior, business impact, user experience, failures and
content of hardware, computer applications, systems and
networks; downloadable software for producing reports,
dashboards, and alerts and notifications from client data;
downloadable software for use in application and server
infrastructure performance management; downloadable software
in the fields of compliance, network security, enterprise
security, and maintenance; downloadable software for
troubleshooting, diagnosing, and protecting computer
software, hardware, networks, virtual machines, and
operational technology; downloadable data reduction and
compression software; downloadable software for
visualization of data; downloadable software for data
storage and access; downloadable software development kits
(sdk). Providing non-downloadable software for remote observation
of hardware, computer applications, systems and networks;
providing non-downloadable software for collecting,
indexing, searching, monitoring and analyzing data generated
by hardware, computer applications, systems and networks;
providing non-downloadable software for providing
operational intelligence, business analytics, security
information, troubleshooting, and monitoring based on client
data; providing non-downloadable software for collecting,
sorting, searching, processing, encrypting, transmitting,
routing, reporting, visualizing, and analyzing software and
computer hardware data from multiple sources and in
structured and unstructured formats; providing
non-downloadable software for tracing, detecting,
discovering, testing, monitoring, analyzing, modeling,
diagnosing, notifying and reporting the performance,
availability, dependencies, functionality, behavior,
business impact, user experience, failures and content of
hardware, computer applications, systems and networks;
providing non-downloadable software for producing reports,
dashboards, and alerts and notifications from client data;
providing non-downloadable software for use in application
and server infrastructure performance management; providing
non-downloadable software in the fields of compliance,
network security, enterprise security, and maintenance;
providing non-downloadable software for troubleshooting,
diagnosing, and protecting computer software, hardware,
networks, virtual machines, and operational technology;
providing non-downloadable data reduction and compression
software; providing non-downloadable software for
visualization of data; providing non-downloadable software
for data storage and access; providing non-downloadable
software development kits (sdk).
16.
SYSTEMS AND METHODS FOR PROVIDING A TIMELINE VIEW OF LOG INFORMATION FOR A CLIENT APPLICATION
A computing platform may be configured with technology for presenting information about a given runtime session of a given client application in the form of a timeline view comprising a time-sorted listing of line items for log events recorded during the given runtime session, wherein each log event's line item includes (i) timing information, (ii) a textual descriptor log event, and (iii) an indication of one or more contextual values associated with the respective log event.
A client device installed with a client application having a graphical user interface (GUI) may be configured to (i) at a given time during a runtime session of the client application, identify a set of GUI elements within the GUI of the client application that is to be represented in a generic visualization of the GUI, (ii) generate a dataset that encodes the generic visualization of the GUI, wherein the generated dataset comprises a respective data structure for each GUI element in the identified set that encodes information for rendering a generic representation of the GUI element, and (iii) after generating the dataset that encodes the generic visualization of the GUI, transmit the generated dataset that encodes the generic visualization of the GUI to a back-end platform associated with a provider of the client application.
A client device installed with a client application comprising a configurable rules engine may be configured to (i) receive configuration data for a given rule related to the client application's observability behavior that comprises (a) a trigger event and (b) a set of one or more actions, (ii) based on the received configuration data, configure the configurable rules engine of the client application to execute the given rule, and (iii) initiate a runtime session of the client application during which the configurable rules engine of the client application executes the given rule by (a) monitoring for the trigger event, (b) while monitoring for the trigger event, detecting an occurrence of the trigger event, and (c) based on detecting the occurrence of the trigger event, causing the set of one or more actions to be carried out.
A computing platform may be configured with technology for presenting information about a given runtime session of a given client application in the form of a timeline view comprising a time-sorted listing of line items for log events recorded during the given runtime session, wherein each log event's line item includes (i) timing information, (ii) a textual descriptor log event, and (iii) an indication of one or more contextual values associated with the respective log event.
A client device installed with a client application having a graphical user interface (GUI) may be configured to (i) at a given time during a runtime session of the client application, identify a set of GUI elements within the GUI of the client application that is to be represented in a generic visualization of the GUI, (ii) generate a dataset that encodes the generic visualization of the GUI, wherein the generated dataset comprises a respective data structure for each GUI element in the identified set that encodes information for rendering a generic representation of the GUI element, and (iii) after generating the dataset that encodes the generic visualization of the GUI, transmit the generated dataset that encodes the generic visualization of the GUI to a back-end platform associated with a provider of the client application.
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
21.
Systems and methods for dynamically configuring a client application
A client device installed with a client application comprising a configurable rules engine may be configured to (i) receive configuration data for a given rule related to the client application's observability behavior that comprises (a) a trigger event and (b) a set of one or more actions, (ii) based on the received configuration data, configure the configurable rules engine of the client application to execute the given rule, and (iii) initiate a runtime session of the client application during which the configurable rules engine of the client application executes the given rule by (a) monitoring for the trigger event, (b) while monitoring for the trigger event, detecting an occurrence of the trigger event, and (c) based on detecting the occurrence of the trigger event, causing the set of one or more actions to be carried out.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable software for remote observation of hardware, computer applications, systems and networks; downloadable software for assisting developers in maintaining and troubleshooting computer software applications of others by collecting, indexing, searching, monitoring and analyzing data generated by hardware, computer applications, systems and networks; downloadable software for providing operational intelligence, business analytics, security information, troubleshooting, and monitoring based on client data; downloadable software for assisting developers in maintaining and troubleshooting computer software applications of others by collecting, sorting, searching, processing, encrypting, transmitting, routing, reporting, visualizing, and analyzing software and computer hardware data from multiple sources and in structured and unstructured formats; downloadable software for tracing, detecting, discovering, testing, monitoring, analyzing, modeling, diagnosing, notifying and reporting the performance, availability, dependencies, functionality, behavior, business impact, user experience, failures and content of hardware, computer applications, systems and networks; downloadable software for producing reports, dashboards, and alerts and notifications from client data; downloadable software for use to assist developers in managing the performance of computer software applications and cloud-based server infrastructure; downloadable software in the fields of data policy compliance of third-party user data, network security, enterprise security, and maintenance; downloadable software for troubleshooting, diagnosing, and protecting computer software, hardware, networks, virtual machines, and operational technology; downloadable data reduction and compression software; downloadable software for the visualization of data being performance and user behaviour analytics from computer software applications; downloadable software for data storage and access; downloadable software development kits (sdk) (1) Providing non-downloadable software for remote observation of hardware, computer applications, systems and networks; providing online non-downloadable software for assisting developers in maintaining and troubleshooting computer software applications of others by collecting, indexing, searching, monitoring and analyzing data generated by hardware, computer applications, systems and networks; providing non-downloadable software for providing operational intelligence, business analytics, security information, troubleshooting, and monitoring based on client data; providing online non-downloadable software for assisting developers in maintaining and troubleshooting computer software applications of others by collecting, sorting, searching, processing, encrypting, transmitting, routing, reporting, visualizing, and analyzing software and computer hardware data from multiple sources and in structured and unstructured formats; providing non-downloadable software for tracing, detecting, discovering, testing, monitoring, analyzing, modeling, diagnosing, notifying and reporting the performance, availability, dependencies, functionality, behavior, business impact, user experience, failures and content of hardware, computer applications, systems and networks; providing non-downloadable software for producing reports, dashboards, and alerts and notifications from client data; providing online non-downloadable software for use to assist developers in managing the performance of computer software applications and cloud-based server infrastructure; providing non-downloadable software in the fields of data policy compliance of third-party user data, network security, enterprise security, and maintenance; providing non-downloadable software for troubleshooting, diagnosing, and protecting computer software, hardware, networks, virtual machines, and operational technology; providing non-downloadable data reduction and compression software; providing non-downloadable software for the visualization of data being performance and user behaviour analytics from computer software applications; providing non-downloadable software for data storage and access; providing non-downloadable software development kits (sdk)
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for remote observation of computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Downloadable software for collecting, indexing, searching, monitoring and analyzing data generated by computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Downloadable software for providing operational intelligence, business analytics, security information, troubleshooting for computer hardware, software, and network issues, and monitoring computer hardware, software, and networks based on client data; Downloadable software for collecting, sorting, searching, processing, encrypting, transmitting, routing, reporting, visualizing, and analyzing software and computer hardware data from multiple sources and in structured and unstructured formats; Downloadable software for tracing, detecting, testing, monitoring, analyzing, modeling, diagnosing, notifying and reporting the performance, availability, dependencies, functionality, behavior, business impact, user experience, failures and content of computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Downloadable software for generating reports, dashboards, and alerts and notifications from client data; Downloadable software for use in application and server infrastructure performance management; Downloadable software for storing and managing electronic data, data visualization, project management in the fields of compliance, network security, enterprise security, and maintenance; Downloadable software for troubleshooting problems with, diagnosing, and protecting computer software, hardware, networks, virtual machines, and operational technology; Downloadable data reduction and compression software; Downloadable software for visualization of data; Downloadable software for data storage and access; Downloadable software development kits (SDK) Providing online non-downloadable software for remote observation of computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Providing online non-downloadable software for collecting, indexing, searching, monitoring and analyzing data generated by computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Providing online non-downloadable software for providing operational intelligence, business analytics, security information, troubleshooting for computer hardware, software, and network issues, and monitoring computer hardware, software, and networks based on client data; Providing online non-downloadable software for collecting, sorting, searching, processing, encrypting, transmitting, routing, reporting, visualizing, and analyzing software and computer hardware data from multiple sources and in structured and unstructured formats; Providing online non-downloadable software for tracing, detecting, testing, monitoring, analyzing, modeling, diagnosing, notifying and reporting the performance, availability, dependencies, functionality, behavior, business impact, user experience, failures and content of computer, computer terminal and mobile devise hardware, computer applications, computer, computer terminal and mobile devise systems and networks; Providing online non-downloadable software for generating reports, dashboards, and alerts and notifications from client data; Providing online non-downloadable software for use in application and server infrastructure performance management; Providing online non-downloadable software for storing and managing electronic data, data visualization, project management in the fields of compliance, network security, enterprise security, and maintenance; Providing online non-downloadable software for troubleshooting problems with, diagnosing, and protecting computer software, hardware, networks, virtual machines, and operational technology; Providing online non-downloadable data reduction and compression software; Providing online non-downloadable software for visualization of data; Providing online non-downloadable software for data storage and access; Providing online non-downloadable software development kits (SDK)
24.
Compressing digital metrics for transmission across a network utilizing a graph-based compression dictionary and time slice delta compression
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate compressed metric data for digital metrics utilizing a graph-based compression dictionary and time slice compression. For instance, the disclosed systems can utilize a dynamically modifiable graph-based compression dictionary to generate compressed metric label identifiers for metric labels of digital metrics. The graph-based compression dictionary can include nodes and edges corresponding to metric label segments and metric label identifier values, respectively. The disclosed systems can traverse the graph-based compression dictionary using a metric label to determine the corresponding compressed metric label identifier. The disclosed systems can further generate delta compression values for the metric values of the digital metrics. For instance, the disclosed systems can compare metric values within a single time slice (e.g., a time stamp) to generate corresponding delta compression values. In some cases, the disclosed systems further compare the metric values across a time window.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
H04L 69/04 - Protocoles de compression de données, p. ex. ROHC
H04L 47/38 - Commande de fluxCommande de la congestion en adaptant le codage ou le taux de compression
H04L 51/06 - Adaptation des messages aux exigences du terminal ou du réseau
25.
INTELLIGENTLY GENERATING AND DEPLOYING A METRIC BLOCKLIST WITHIN A DISTRIBUTED COMPUTING SYSTEM TO EFFICIENTLY MANAGE DATA METRIC REQUESTS
The present disclosure relates to systems, non-transitory computer-readable media, and methods for improving the efficiency and flexibility of implementing computer devices by intelligently generating a metric blocklist based on predicted utilization of digital metrics and deploying the metric blocklist at one or more computing devices to limit digital metric requests to distributed databases. In particular, in one or more embodiments, the disclosed systems monitor historical digital metric utilization and apply a prediction model to generate a metric blocklist of digital metrics that are not likely to be utilized by one or more metric requesting devices of a distributed computing system. The disclosed systems can deploy the metric blocklist to computing devices of a distributed computing system to efficiently limit digital requests, processing resources, bandwidth consumption, and storage load with regard to utilization of metric storage devices (e.g., time-series databases).
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate compressed metric data for digital metrics utilizing a graph-based compression dictionary and time slice compression. For instance, the disclosed systems can utilize a dynamically modifiable graph-based compression dictionary to generate compressed metric label identifiers for metric labels of digital metrics. The graph-based compression dictionary can include nodes and edges corresponding to metric label segments and metric label identifier values, respectively. The disclosed systems can traverse the graph-based compression dictionary using a metric label to determine the corresponding compressed metric label identifier. The disclosed systems can further generate delta compression values for the metric values of the digital metrics. For instance, the disclosed systems can compare metric values within a single time slice (e.g., a time stamp) to generate corresponding delta compression values. In some cases, the disclosed systems further compare the metric values across a time window.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
H04L 69/04 - Protocoles de compression de données, p. ex. ROHC
H04L 47/38 - Commande de fluxCommande de la congestion en adaptant le codage ou le taux de compression
H04L 51/06 - Adaptation des messages aux exigences du terminal ou du réseau
27.
Compressing digital metrics for transmission across a network utilizing a graph-based compression dictionary and time slice delta compression
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate compressed metric data for digital metrics utilizing a graph-based compression dictionary and time slice compression. For instance, the disclosed systems can utilize a dynamically modifiable graph-based compression dictionary to generate compressed metric label identifiers for metric labels of digital metrics. The graph-based compression dictionary can include nodes and edges corresponding to metric label segments and metric label identifier values, respectively. The disclosed systems can traverse the graph-based compression dictionary using a metric label to determine the corresponding compressed metric label identifier. The disclosed systems can further generate delta compression values for the metric values of the digital metrics. For instance, the disclosed systems can compare metric values within a single time slice (e.g., a time stamp) to generate corresponding delta compression values. In some cases, the disclosed systems further compare the metric values across a time window.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
H04L 69/04 - Protocoles de compression de données, p. ex. ROHC
H04L 47/38 - Commande de fluxCommande de la congestion en adaptant le codage ou le taux de compression
H04L 51/06 - Adaptation des messages aux exigences du terminal ou du réseau
