Persistent storage may contain a list of discovery commands, the discovery commands respectively associated with lists of network addresses. A discovery validation application, when executed by one or more processors, may be configured to: read, from the persistent storage, the list of discovery commands and the lists of network addresses; for each discovery command in the list of discovery commands, transmit, by way of one or more proxy servers deployed external to the system, the discovery command to each network address in the respectively associated list of network addresses; receive, by way of the one or more proxy servers, discovery results respectively corresponding to each of the discovery commands that were transmitted, wherein the discovery results either indicate success or failure of the discovery commands; and write, to the persistent storage, the discovery results.
H04L 43/0817 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
H04L 41/12 - Discovery or management of network topologies
2.
SUPPORT FOR MULTI-TYPE USERS IN A SINGLE-TYPE COMPUTING SYSTEM
Persistent storage contains a parent table and one or more child tables, the parent table containing: a class field specifying types, and one or more filter fields. One or more processors may: receive a first request to read first information of a first type for a. first entity, determine that, in a first entry' of the parent table for the first entity, the first type is specified in the class field; obtain the first information from a. child table associated with the first type; receive a second request to read second information of a second type for a second entity; determine that, in a second entry' of the parent table for the second entity, the second type is indicated as present by a filter field that is associated with the second type; and obtain the second information from a set of additional fields in the second entry.
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06F 16/22 - Indexing; Data structures therefor; Storage structures
H04L 41/40 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using virtualisation of network functions or resources, e.g. SDN or NFV entities
3.
IMPROVED LOCALIZATION PROCEDURES AND PRIORITIZATION FOR APPLICATIONS
A system includes a database containing database tables. The system also includes one or more processors configured to: (i) determine, for a software application, a set of the database tables containing information used by the software application; (ii) for an item associated with the software application, query the set of the database tables for entries related to the item, wherein the entries are in a first language; (iii) generate, for display, a representation of a first pane and a second pane, wherein the first pane contains the entries, and wherein the second pane contains data input elements for translations of the entries into a second language; (iv) transmit the representation; (v) receive data entered into the data input elements of the second pane; and (vi) store, in the set of the database tables, the data entered into the data input elements as a translation to the second language.
Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.
A disclosed cloud service (CS) enables cross-cloud access to data resources and cross-cloud execution of orchestrations, including automations. The CS includes a peer-to-peer (P2P) cloud orchestrator service (COS) and a cloud broker service (CBS). The COS enables P2P identification and communication routing between different cloud computing environments. The CBS enables cross-cloud access to data and orchestrations (e.g., one or more scripts, workflows, and/or scheduled jobs) from different cloud computing environments. Additionally, the data center may be configured to route all orchestration calls of a data center through the CS, such that the CS can ensure that references to local data and orchestrations are handled within the data center, while references to data and orchestrations of a different data center are suitably routed to be handled by a corresponding CS of the appropriate data center.
An example embodiment may involve a software application executable on computing devices of a remote network management platform and a computation instance associated with a managed network. The computational instance may contain a database storing data of the managed network. The software application may receive, from a client device of the managed network, a natural language query (NLQ), and retrieve Backus-Naur form (BNF) rules and a set of metadata associated with the BNF rules. The metadata may include a text-based description of a schema of the database and abbreviations associated with the BNF rules. The NLQ may be parsed using the BNF rules together with the metadata by applying the metadata during parsing to extend the BNF rules. A query object based on the parsed query may be generated, and the database searched using the query object. A result of the search may be transmitted to the client device.
An example embodiment involves receiving an activity record including activity data, provider data, and description data; applying a first layer of a multi-layer machine learning (ML) model to predict that the activity record relates to software, applying a second layer of the multi-layer ML model to predict a provider name of a software application referenced in the activity record, applying a third layer of the multi-layer ML model to predict an application title of the software application referenced in the activity record, and storing, in a database, a configuration item indicating that the activity record relates to software, where the configuration item contains attributes including the provider name and the application title.
An example embodiment relates to discovering computing devices in a managed network that are involved in blockchain-based mining. The example embodiment may involve a proxy server application that is disposed within the managed network, controlled by a remote network management platform, and configured to: provide, to a computing device disposed within the managed network, one or more instructions to identify one or more applications executing on the computing device; determine, for an application of the one or more applications that were identified, a command string used to invoke the application to execute on the computing device; compare the command string to a plurality of identifiers indicative of blockchain-based mining; determine that the command string includes an identifier from the plurality of identifiers indicative of blockchain-based mining; and based on determining that the command string includes the identifier, store, in a database, an indication that the application is associated with blockchain-based mining.
H04L 12/16 - Arrangements for providing special services to substations
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
A computing system includes a database and a discovery application that initiates discovery of software applications within a managed network by probing the computing devices for applications in stalled thereon. The discovery application executes discovery patterns in an attempt to classify a discovered application and determines that the discovered application is unclassified after executing the discovery patterns. In response to determining that the discovered application is unclassified, the discovery application (i) generates a configuration item representing the discovered application without classification and (ii) selects a characteristic file containing attributes of the discovered application. The discovery application provides the characteristic file to a machine learning (ML) classifier trained using a plurality of characteristic files. The discovery application receives, from the ML classifier, a classification of the discovered application, modifies the configuration item to include the classification of the discovered application, and stores, in the database, the configuration item as modified.
An example embodiment may involve a software application executable on a computing device of a computational instance of a remote network management platform associated with a managed network. The software application may receive, from a client device of the managed network, a natural language query, determine that a first term of the query does not match any term in a list of predetermined terms, and revise the query by (i) applying a set of linguistic rules that modify the first term to generate a replacement term, (ii) determining whether the replacement term matches at least one term in the list, and (iii) after determining that the replacement term matches at least one term in the list, replacing the first term in the query with the replacement term. The software application may then parse the revised query, search the database, and transmit a result to the client device.
An example embodiment may involve a software application executable on a computing device of a computational instance of a remote network management platform associated with a managed network. The computational instance may contain a database from which information associated with the managed network can be delivered to the client device. The software application may receive, from a client device of the managed network, a natural language query, parse the query using context-free grammar rules in Backus-Naur form (BNF), generate a search sentence based on the parsed query, search the database using the search sentence as a search query, and transmit, to the client device, a result of the search query. The context-free grammar rules may include an extended context-free grammar rule that defines a non- terminal symbol and comprises a Boolean NOT operator that eliminates one or more potential definitions of the non-terminal symbol from consideration when parsing the query.
A database contains a corpus of incident reports, a machine learning (ML) model trained to calculate paragraph vectors of the incident reports, and a look-up set table that contains a list of paragraph vectors respectively associated with sets of the incident reports. A plurality of ML worker nodes each store the look-up set table and are configured to execute the ML model. An update thread is configured to: determine that the look-up set table has expired; update the look-up set table by: (i) adding a first set of incident reports received since a most recent update of the look-up set table, and (ii) removing a second set of incident reports containing timestamps that are no longer within a sliding time window; store, in the database, the look- up set table as updated; and transmit, to the ML worker nodes, respective indications that the look-up set table has been updated.
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
Word vectors are multi-dimensional vectors that represent words in a corpus of text and that are embedded in a semantically-encoded vector space. Word vectors can be used for sentiment analysis, comparison of the topic or content of sentences, paragraphs, or other passages of text or other natural language processing tasks. However, the generation of word vectors can be computationally expensive. Accordingly, when a set of word vectors is needed for a particular corpus of text, a set of word vectors previously generated from a corpus of text that is sufficiently similar to the particular corpus of text, with respect to some criteria, may be re-used for the particular corpus of text. Such similarity could include the two corpora of text containing the same or similar sets of words or containing incident reports or other time-coded sets of text from overlapping or otherwise similar periods of time.
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
The present approach relates to systems and methods for tracking a plurality of client actions within a portal running on a client instance and generating an analytics report that includes analytics information indicative of the tracked plurality of user actions and other events. The present approach includes receiving a user criteria specifying a web service integratable with an analytics package. The present approach further includes integrating the analytics package with the specified web service to leverage functionality of the specified web service, such as tracking functionality, to enhance tracking efficiency by causing the analytics package to selectively import analytics information from the web service. Furthermore, the present approach includes generating an analytics report that includes The analytics report may include analytics information indicative of user actions tracked by the analytics package or other analytics information imported from the web service by the analytics package.
An enterprise rule is created for a hosted client instance, the enterprise rule being triggered in response to one or more predetermined computing conditions being satisfied. A decision action element is set for the enterprise rule, the decision action element being executed in response to the enterprise rule being triggered. The decision action element is implemented based on a decision table that includes decision inputs and respective condition logic based on the decision inputs for each of a plurality of decision answers associated with the decision table. The decision table is external to and decoupled from the enterprise rule. First and second decision answer action elements are respectively set for the enterprise rule, the first and second decision answer action elements being set to execute in response to a decision answer served up by the decision table being first and second one of the plurality of decision answers, respectively.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
16.
SYSTEM AND METHOD FOR ANONYMIZED DATA REPOSITORIES
A computing system includes an anonymizer server. The anonymizer server is communicatively coupled to a data repository configured to store a personal identification information (PII) data. The anonymizer server is configured to perform operations including receiving a repository configuration request comprising an anonymized data schema, and creating an anonymized data repository clone based on the anonymized data schema. The anonymizer server is also configured to perform operations including anonymizing the PII data to create an anonymized data by applying a one-way data masking, a one-way data morphing, or a combination thereof, and storing the anonymized data in the anonymized data repository clone.
Word vectors are multi-dimensional vectors that represent words in a corpus of text and that are embedded in a semantically-encoded vector space; paragraph vectors extend word vectors to represent, in the same semantically-encoded space, the overall semantic content and context of a phrase, sentence, paragraph, or other multi-word sample of text. Word and paragraph vectors can be used for sentiment analysis, comparison of the topic or content of samples of text, or other natural language processing tasks. However, the generation of word and paragraph vectors can be computationally expensive. Accordingly, word and paragraph vectors can be determined only for user-specified subsets of fields of incident reports in a database.
A computing system may include a database disposed within a remote network management platform that manages a managed network, and server device(s) associated with the platform and configured to: transmit, to a third-party computing system, a request for general information identifying computing resources of the third-party computing system assigned to the managed network; receive, from the third-party computing system, a response indicating resource names and types of the resources that were identified; based on the response, determine that a first resource is of a first type, and responsively store, in the database, a first representation that has just data fields containing the general information from the response that identifies the first resource; and based on the response, determine that a second resource is of a second type, and responsively store, in the database, a second representation that has data fields arranged to contain specific information about the second resource.
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
G06F 16/00 - Information retrieval; Database structures therefor; File system structures therefor
19.
IMPROVED MACHINE LEARNING CLASSIFICATION WITH MODEL QUALITY PREDICTION
An embodiment may include a machine learning based classifier that maps input observations into respective categories and a database containing a corpus of training data for the classifier. The training data includes a plurality of entries, each entry having an observation respectively associated with a ground truth category thereof. A computing device may be configured to select, from the training data, a plurality of subsets each containing a different number of entries. The computing device may also be configured to, for each particular subset: (i) divide the particular subset into a training portion and a validation portion, (ii) train the classifier with the training portion, (iii) provide the validation portion as input to the classifier as trained, and (iv) based on how entries of the validation portion are mapped to the categories, determine a respective precision for the particular subset.
A computing system may include a plurality of computational instances each containing one or more computing devices and one or more databases. A traffic filtering device may be configured to: receive a first sequence of packets and filter the first sequence of packets to create a second sequence of packets, where the second sequence of packets includes only copies of packets that were transmitted to a particular computational instance. The computing system may further include a simulation compiler device configured to: (i) receive the second sequence of packets, (ii) identify a captured transaction within the second sequence of packets, and (iii) encode the captured transaction as a playback instruction, where the playback instruction can be used to generate a third sequence of packets that, when transmitted to a computational instance used for testing, simulates the captured transaction.
A hosted client instance is provided over a network interface for communicatively coupling with a remote client device, the hosted client instance including a first plurality of application components for performing a plurality of actions associated with the hosted client instance. A metric is set to optimize one or more actions associated with the hosted client instance based on input from a user. One or more application components are detected based on the metric from among a second plurality of application components available on a resource server. The detected one or more application components are ranked based on: (i) a maturity score of each of the detected one or more application components; and (ii) dependency data indicating an operational dependency of each of the detected one or more application components. The ranked one or more application components are presented in a ranked order to a user.
H04L 43/091 - Measuring contribution of individual network components to actual service level
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
G06F 11/32 - Monitoring with visual indication of the functioning of the machine
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
22.
SYSTEMS AND METHODS FOR COMPARING COMPUTER SCRIPTS
The present disclosure relates generally to analyzing and comparing computer scripts, and more specifically, to determining semantic similarities between syntactically different scripts. An example computing system includes a memory configured to store a database, wherein the database is configured to store script canonical form (SCF) representations of scripts, and wherein each SCF representation is a topologically-sorted, labeled, directed graph that includes tables and datasets as nodes, actions as edges, and predicates as labels. The system includes a processor configured to execute instructions stored in the memory to cause the computing system to perform actions including: generating a first SCF representation of a first script, and storing the first SCF representation of the first script in the database.
A computational instance of a remote network management platform includes a database API configured to allow operations to be performed on data within the computational instance. A computing system of the computational instance (i) receives a request from a client device to perform an operation on a server device external to the platform; (ii) determines that the server device is accessible by way of a communication protocol that supports a set of protocol-specific operations; (iii) translates the request from a format of the database API into a format of the communication protocol by mapping the requested operation to a target operation of the protocol-specific operations; (iv) instructs the server device to perform the target operation; (v) receives a response containing a result of the server device performing the target operation; and (vi) translates the result from the format of the communication protocol into the format of the database API.
H04L 67/565 - Conversion or adaptation of application format or content
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
G06F 9/44 - Arrangements for executing specific programs
24.
RESOURCE MANAGEMENT FOR OBJECTS WITHIN A WEB APPLICATION
As a web browser application executing on a computing renders a web application that contains a plurality of objects, the web browser application carries out, respectively for each object, a set of resource-consumption actions involving use of resources of the client device. Further, the web browser application dynamically manages operational states of the objects based on a cumulative resource-consumption of the web application, including (i) determining that the cumulative resource-consumption of the web application exceeds a defined limit, and (ii) responsive to the determining, transitioning at least one of the objects from a first operational state to a second operational state, where the object contributes less to the cumulative resource-consumption of the web application in the second operational state than in the first operational state.
G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
H04L 12/16 - Arrangements for providing special services to substations
A system and method for comparative performance monitoring of software release versions is disclosed. A remote network management platform may include a computational instance for managing a network. Transactions between a server of the computational instance and a client device in the managed network may be logged to a database. Transactions may be carried out by a release version of a set of program code units executing on the server. A software application executing on a computing device may retrieve and analyze a first set of transactions carried out by a first release version of the set of program code units to determine a first set of performance metrics, and do the same for a second set of transactions carried out by a second release version of the set of program code units to determine a second set of performance metrics. A classification filter may be applied to the metrics, and a quantitative comparison of the filtered first and second sets of performance metrics may be displayed on graphical user device.
H04L 41/0859 - Retrieval of network configuration; Tracking network configuration history by keeping history of different configuration generations or by rolling back to previous configuration versions
An example embodiment performed by a scoped software application executable on a computing device of a computational instance within a trust group of computational instances of a remote network management platform may involve obtaining a representation of one or more transactions involving the computational instance. The embodiment may also involve encrypting the representation, using a pre-shared key to which at least some computational instances within the trust group have access. The embodiment may also involve placing the encrypted representation into a data block that also includes: (i) a first output generated by applying a hash function to content from a previous data block of a blockchain-based transaction ledger, and (ii) a second output generated by applying the hash function to the encrypted representation and the first output. The embodiment may also involve distributing copies of the data block to blockchain-based transaction ledgers within each computational instance of the trust group.
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
H04L 9/30 - Public key, i.e. encryption algorithm being computationally infeasible to invert and users' encryption keys not requiring secrecy
A system includes a client instance hosted by a datacenter, wherein the client instance is generated for one or more client networks. The system performs operations comprising generating a graphical user interface, receiving, via the graphical user interface, an input adjusting the selected time period, and updating the graphical user interface in real time in response to the received input. The graphical user interface includes a timeline that spans an entirety of an incident dataset, a selected time period, wherein the selected time period is a portion of the timeline, a plot of incident data from the incident dataset over the selected time period, and a plurality of calculated metrics based on the incident data during the selected time period.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06Q 10/0639 - Performance analysis of employees; Performance analysis of enterprise or organisation operations
28.
METHOD AND SYSTEM FOR AUTOMATED INTENT MINING, CLASSIFICATION AND DISPOSITION
An agent automation system includes a memory configured to store a corpus of utterances and a semantic mining framework and a processor configured to execute instructions of the semantic mining framework to cause the agent automation system to perform actions, wherein the actions include: detecting intents within the corpus of utterances; producing intent vectors for the intents within the corpus; calculating distances between the intent vectors; generating meaning clusters of intent vectors based on the distances; 'detecting stable ranges of cluster radius values for the meaning clusters; and generating an intent/entity model from the meaning clusters and the stable ranges of cluster radius values, wherein the agent automation system is configured to use the intent/entity model to classify intents in received natural language requests.
Disclosed is a computing system configured to receive input declaring structure of a web page, including declarations of component hierarchy and data-binding between components of the web page, and to responsively generate and store, cooperatively in a plurality of tables of a database, a representation of the web page including references to underlying scripts interpretable to define structure and operation of the components. Further, the computing system is configured to thereafter receive, from a client device, a request for such a page and, in response to the request, (i) to query the database in order to ascertain component tree-structure of the page, (ii) based on the ascertained component tree-structure, to construct a markup document that represents the ascertained component tree-structure and includes a component loader operative to load the underlying scripts, and (iii) to output the constructed markup document for rendering by a web browser executing on the client device.
H04L 41/12 - Discovery or management of network topologies
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
31.
GUIDED CONFIGURATION ITEM CLASS CREATION IN A REMOTE NETWORK MANAGEMENT PLATFORM
A system may include a database disposed within a remote network management platform, a server device disposed in the platform, and a client device. The database may contain representations of configuration items, such as computing devices and software applications associated with the managed network. The server device may provide a graphical user interface including a sequence of panes to the client device. The sequence of panes may include an identifier pane, an identification rules pane, and a reconciliation pane. Each pane may include data entry fields that are operable to define a new class of configuration item. The server device may receive, by way of the graphical user interface, a definition of the new class that uniquely identifies configuration items of a particular type using at least the attributes. The server may store, in the database, the definition of the new class.
An example embodiment may include a security enforcement point device disposed within a managed network and a security decision point device disposed within a computational instance of a remote network management platform. The security decision point device may be configured to: receive a message by way of the managed network; parse the message to identify observable indicators of one or more of the security threats, where the observable indicators include at least one of a network addresses, a hyperlink, or a representation of an attached file; remotely query a security threat database for the observable indicators; receive, from the security threat database, an indication that the observable indicators are associated with a particular security threat, and transmit, to the security enforcement point device, a command to update its associated security policy such that the particular security threat is mitigated.
Creating, executing, and managing flow plans by performing at least the following: creating a trigger for a design-time flow plan that activates when one or more computing conditions are met, define a plurality of action instances for the design-time flow plan that execute after the trigger activates, wherein one or more of the action instances comprise a respective sequence of step instances associated with respective inputs and outputs, save the design-time flow plan within a data model, convert the saved design-time flow plan into a run-time flow plan, and execute one or more operations within the run-time flow plan, wherein the execution of the one or more operations within run-time flow plan occurs simultaneously when the data model is updated with a modified design-time flow plan, and wherein the one or more operations includes a dynamic mutable operation.
G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
34.
AUTOMATIC GROUPING OF SIMILAR APPLICATIONS AND DEVICES ON A NETWORK MAP
An embodiment may involve a managed network containing computing devices. The computing devices may be respectively associated with unqualified domain names. One or more server devices may be disposed within a remote network management platform that manages the managed network. These server devices may be configured to: probe the managed network, by way of a proxy server application disposed within the managed network, to obtain information related to applications operating on the computing devices, network connectivity of the computing devices, and representations of the unqualified domain names; obtain a regular expression; determine a subset of the computing devices in the managed network on which a particular application is operating and for which the respectively associated unqualified domain names match the regular expression; and generate a map of the managed network in which the subset of the computing devices is represented as a grouped node instead of individual nodes.
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
H04L 41/0893 - Assignment of logical groups to network elements
H04L 41/12 - Discovery or management of network topologies
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
H04L 67/52 - Network services specially adapted for the location of the user terminal
A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.
A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.
Systems, methods, and media for translating requests to acquire or change goods and services by receiving a request in a service catalog. The received request is received in a format that is not suitable for a target vendor. The received request is then translated into a format suitable for the target vendor. The translated received request is then transmitted to the vendor using the translated format.
A network system may include a plurality of trainer devices and a computing system disposed within a remote network management platform. The computing system may be configured to: receive, from a client device of a managed network, information indicating (i) training data that is to be used as basis for generating a machine learning (ML) model and (ii) a target variable to be predicted using the ML model; transmit an ML training request for reception by one of the plurality of trainer devices; provide the training data to a particular trainer device executing a particular ML trainer process that is serving the ML training request; receive, from the particular trainer device, the ML model that is generated based on the provided training data and according to the particular ML trainer process; predict the target variable using the ML model; and transmit, to the client device, information indicating the target variable.
A computer network discovery system may involve a computing system and a database disposed within a remote network management platform, and a proxy server application disposed within an enterprise network. The computing system may be configured to: transmit first instructions causing the proxy server application to obtain configuration and operational information for virtual machines; store the configuration and operational information for the virtual machines in a first set of tables of the database; transmit second instructions causing the server device to obtain configuration and operational information for services; and store the configuration and operational information for the services in a second set of tables of the database, where the first set and the second set of tables have tables in common that store at least part of the configuration and operational information for the virtual machines and the services.
H04L 67/51 - Discovery or management thereof, e.g. service location protocol [SLP] or web services
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
H04L 41/12 - Discovery or management of network topologies
H04L 41/122 - Discovery or management of network topologies of virtualised topologies e.g. software-defined networks [SDN] or network function virtualisation [NFV]
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
H04L 67/53 - Network services using third party service providers
40.
USER INTERFACE FOR AUTOMATED FLOWS WITHIN A CLOUD BASED DEVELOPMENTAL PLATFORM
Creating, executing, and managing flow plans by performing at least the following: presenting on a display an operational view of an executing flow plan within an operational view user interface that includes: a flow plan graphical outline associated with the executing flow plan, wherein the flow plan graphical outline comprises a trigger instance graphical element for a trigger instance, at least one action instance graphical element for at least one action instance, and at least one step instance graphical element for at least one step instance; one or more state indicators adjacent to the flow plan graphical outline that provide an overall state of the trigger instance, the action instance, and the step instance; and one or more metrics relating to executing the trigger instance, the action instance, and the step instance.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
41.
IDENTIFYING CLUSTERS FOR SERVICE MANAGEMENT OPERATIONS
Client instance data including a plurality of incidents is obtained, each incident including a plurality of fields. A target field and an evaluation field are selected from among the plural fields. The plurality of incidents are grouped into a plurality of clusters based on a degree of a natural language text similarity of respective target fields in the plurality of incidents. A quality value is determined for each of the plurality of clusters based on the degree of the natural language text similarity of respective target fields in grouped incidents of the cluster from among the plurality of incidents, and based on respective evaluation fields. Each of the plurality of clusters is ranked based on the respective quality value of the cluster and a number of the grouped incidents of the cluster. At least one of the ranked plurality of clusters is identified to perform a service management operation.
ASTRACT Creating, executing, and managing flow plans by performing at least the following: presenting on a display an operational view of an executing flow plan within an operational view user interface that includes: a flow plan graphical outline associated with the executing flow plan, wherein the flow plan graphical outline comprises a trigger instance graphical element for a trigger instance, at least one action instance graphical element for at least one action instance, and at least one step instance graphical element for at least one step instance; one or more state indicators adjacent to the flow plan graphical outline that provide an overall state of the trigger instance, the action instance, and the step instance; and one or more metrics relating to executing the trigger instance, the action instance, and the step instance. Date Recue/Date Received 2021-03-05
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
43.
SYSTEMS AND METHODS FOR BLUEPRINT-BASED CLOUD MANAGEMENT
Systems, methods, and media for translating requests to acquire or change goods and services by receiving a request in a service catalog. The received request is received in a format that is not suitable for a target vendor. The received request is then translated into a format suitable for the target vendor. The translated received request is then transmitted to the vendor using the translated format.
G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
G06F 9/44 - Arrangements for executing specific programs
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
A method includes receiving hierarchy data indicating a capability hierarchy associated with a customer network, the capability hierarchy indicating that a first capability is a sub-capability of a second capability. The method further includes receiving application data from a MID server of the customer network, the application data associated with an application utilized by the customer network for the first capability. The method further includes determining, based on the application data, an application score indicating an effectiveness level of the application for the first capability. The method further includes determining, based on the application score, a first capability score associated with the first capability. The method further includes determining, based on the first capability score and the capability hierarchy, a second capability score of the second capability, the second capability score indicating a health metric of the second capability within the customer network.
H04L 43/0817 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
H04L 43/045 - Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
A network system may include a plurality of trainer devices and a computing system disposed within a remote network management platform. The computing system may be configured to: receive, from a client device of a managed network, information indicating (i) training data that is to be used as basis for generating a machine learning (ML) model and (ii) a target variable to be predicted using the ML model; transmit an ML training request for reception by one of the plurality of trainer devices; provide the training data to a particular trainer device executing a particular ML trainer process that is serving the ML training request; receive, from the particular trainer device, the ML model that is generated based on the provided training data and according to the particular ML trainer process; predict the target variable using the ML model; and transmit, to the client device, information indicating the target variable.
An anomaly detection module may include a time-series analyzer that classifies current time-series data into at least one of a plurality of classifications based upon historical data and may construct a statistical model representative of the current time-series data based upon the at least one of the plurality of classifications. An anomaly detector monitors a stream of the current time-series data and identifies statistical outliers of the stream of the current time-series data, based upon the statistical model and may determine an anomalous score for the statistical outliers by tracking a history of the statistical outliers; wherein the anomalous score comprises a representation of a magnitude of deviation between the current time-series data and the statistical model over multiple measurements of the current time-series data, over a particular time interval, or both.
Creating and executing flow plans by performing at least the following: obtaining a run-time flow plan that comprises a trigger, a first operation, and a second operation, wherein the first operation precedes the second operation within the run-time flow plan and one or more input values of the second operation are linked to the first operation, determining whether one or more conditions of the trigger are met, execute the first operation based at least on the determination that the one or more conditions of the trigger are met, monitoring whether the second operation is ready for execution based at least on a determination that the one or more input values of a second action operation are ready, and executing the second action operation when the second action operation has been identified as ready for execution.
Creating and executing flow plans by performing at least the following: obtaining a run-time flow plan that comprises a trigger, a first operation, and a second operation, wherein the first operation precedes the second operation within the run-time flow plan and one or more input values of the second operation are linked to the first operation, determining whether one or more conditions of the trigger are met, execute the first operation based at least on the determination that the one or more conditions of the trigger are met, monitoring whether the second operation is ready for execution based at least on a determination that the one or more input values of a second action operation are ready, and executing the second action operation when the second action operation has been identified as ready for execution.
Systems and methods for using a mathematical model based on historical natural language inputs to automatically complete form fields are disclosed. An incident report may be defined with a set of required parameter fields such as category, priority, assignment, and classification. Incident report submission forms may also have other free text input fields providing information about a problem in the natural vocabulary of the person reporting the problem. Automatic completion of these so-called parameter fields may be based on analysis of the natural language inputs and use of machine learning techniques to determine appropriate values for the parameter fields. The machine learning techniques may include parsing the natural language input to determine a mathematical representation and application of the mathematical representation to "match" historically similar input. Once matched the parameter values from the historically similar input may be used instead of generic default values.
Systems and methods for using a mathematical model based on historical information to automatically schedule and monitor work flows are disclosed. Prediction methods that use some variables to predict unknown or future values of other variables may assist in reducing manual intervention when addressing incident reports or other task-based work items. For example, work items that are expected to conform to a supervised model built from historical customer information. Given a collection of records in a training set, each record contains a set of attributes with one of the attributes being the class. If a model can be found for the class attribute as a function of the values of the other attributes, then previously unseen records may be assigned a class as accurately as possible based on the model. A test data set is used to determine model accuracy prior to allowing general use of the model.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
51.
MODEL BUILDING ARCHITECTURE AND SMART ROUTING OF WORK ITEMS
Systems and methods for using a mathematical model based on historical information to automatically schedule and monitor work flows are disclosed. Prediction methods that use some variables to predict unknown or future values of other variables may assist in reducing manual intervention when addressing incident reports or other task-based work items. For example, work items that are expected to conform to a supervised model built from historical customer information. Given a collection of records in a training set, each record contains a set of attributes with one of the attributes being the class. If a model can be found for the class attribute as a function of the values of the other attributes, then previously unseen records may be assigned a class as accurately as possible based on the model. A test data set is used to determine model accuracy prior to allowing general use of the model.
G06F 40/40 - Processing or translation of natural language
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
The present approach improves the query performance of a database in a manner that is transparent to a user. In one aspect, this approach creates separate partition tables that are not directly accessible to a user of the database. A client-facing aspect of the database is a logical model which may correspond to a single, main table with which the user interacts. Thus, queries or operations may be generated on the client side in the context of the logical model. A database or query layer can then, transparent to the user, translate the user generated requests into query language that addresses the proper partitions to generate a result set or otherwise perform a database operation.
The present approach improves the query performance of a database in a manner that is transparent to a user. This approach provides a logical model of a database that is referenced by client code as a single table, maintains partition tables not referenced by client code, and stores respective subsets of database data. Each partition table includes database data for a subset of fields. One or more fields are duplicated and synchronized between two or more partition tables to reduce a number ofjoins performed on the partition tables. The partition tables are generated and maintained based on an index quantity limitation such that new partition tables are added when the index quantity limitation is reached. This approach also resolves client code referencing the logical model to identify at least one partition table and executes resolved client code using identified partition tables to perform the operations on the database
A system and method including organizing blueprints into a blueprint chain, the blueprint chain connecting the blueprints in an order, wherein a blueprint in the blueprint chain includes resources connected to form a schematic of a portion of an application, wherein a first resource of the blueprint is associated with a first provider and a second resource of the blueprint is associated with a second provider, identifying at least one cloud account suitable for provisioning the blueprint chain, wherein the at least one cloud account includes the first provider and the second provider, and generating an orchestration to provision an instance of the application, the orchestration including a plurality of provisioning steps based on the blueprint chain and a selected one of the at least one cloud account, wherein an ordering of the plurality of provisioning steps depends on the order of the blueprints in the blueprint chain.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
A source control system is used for the distributed incremental updating of trays that include all of the dependencies needed for an application to execute within a computing environment. An application of a first version of a tray is executed on a server responsive to the first version of the tray being retrieved from a source control system. Tray management software of the first version of the tray receives a request to update the tray to a second version. The tray management software requests a changeset including file differences between the first and second versions of the tray from the source control system. Responsive to a determination by the tray management software that there are no pending requests preventing an update, the tray is updated from the first version to the second version by updating files in the tray according to the changeset.
In an operating system with access control functionality, a request for a function that requires kernel space access can be initiated by an application and executed in the kernel space using a management mechanism having access to the kernel space. An application container within which the application executes includes a signaling mechanism permitted to access a message bus external to the application container using an access control policy of the operating system. The signaling mechanism signals that a message associated with the request is to be processed with kernel space access. An access control policy of the operating system permits the signaling mechanism to access a message bus used to transmit the message to the management mechanism. The management mechanism executes the function in the kernel space responsive to receiving the message from the message bus and determining that the function requires kernel space access.
The unauthorized access of database nodes by application nodes within an electronic computing and communications system can be prevented using an access table that stores access table records indicating that at least some of the application nodes are authorized to access at least some of the database nodes. The access table records can be generated by identifying connections between application nodes and database nodes within a configuration management database. Responsive to receiving a request to access a database node sent from a first application node, the access table can be queried to determine whether an access table record indicating that the first application node is authorized to access the database node is stored in the access table. If that access table record is not stored in the access table, the request is denied. Otherwise, the request is allowed.
Workflows 407 can be refactored using a visual workflow model, such as within a virtual programming environment. A selection of a group of activities in an existing workflow 407 can be received. The group of activities can be duplicated into a new workflow 407. Thereafter, the group of activities can be parsed to identify at least one input variable used by the activities of the group and at least one output variable resulting from those activities. The input variables and output variables are then duplicated as inputs and outputs to the new workflow 407. The previously selected group of activities can be replaced in the existing workflow 407 with an activity based on the new workflow 407. The input variables and output variables are then mapped to the respective inputs and outputs of that activity.
Systems and methods for the identification and reconciliation of network resource information are herein disclosed. In an implementation, a system includes instructions stored in memory for processing a request received from a data source to update a record of a network resource by receiving data relating to an attribute of a network resource of a computer network from a first data source, wherein the network resource is associated with a configuration item of a configuration management database, the configuration item including data relating to the attribute from a second source; determining that the first data source is authoritative for the attribute based on a priority of the first data source, a priority of the second data source, and a staleness period of the second data source; and processing the request by updating the attribute based on the data.
Systems and methods for the deployment of network resource information based on a containment structure are herein disclosed as comprising, in an implementation, determining, using a configuration item representative of a resource within the configuration management database, a first set of properties associated with a resource type, wherein the first set of properties comprises a subset of the global property set, determining a second set of properties based on deployment rules, such as a containment relationship defining properties included within a parent configuration item of the configuration management database, wherein the second set of properties comprises a subset of the first set of properties, provisioning the resource with the second set of properties, and communicating the provisioned resource for activation within the computer network. In an implementation, a deployment agent can be configured to provision a resource with the second set of properties.
In a multi-stage network discovery system, a target device is identified by a logical address and associated with a configuration item (CI) record stored in a configuration management database (CMDB). A receiver module receives first probe data from a first probe running against the target device, the first probe data comprising constant attribute data of the target device, stores at least part of the first probe data in a first part of the CI record, receives subsequent probe data from at least one subsequent probe against the target device using the logical address, the subsequent probe data comprising the constant attribute data of the target device, determines that the constant attribute data from the subsequent probe matches the constant attribute data from the CI record, and in response to the determination, stores the subsequent data obtained from the second probe in a second part of the CI record.
H04L 41/0869 - Validating the configuration within one network element
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
62.
METHOD AND APPARATUS FOR REDUCING SECURITY RISK IN A NETWORKED COMPUTER SYSTEM ARCHITECTURE
An apparatus and associated method are provided for reducing a security risk in a networked computer system architecture. The method comprises receiving at a security computer external vulnerability data from an external source regarding vulnerabilities associated with an attack vector for configuration item (CI) data related to a (CI) device, of the networked computer system. The security computer accesses a configuration management database (CMDB) and the CI data related to the physical device is read. Trust zone data associated with the CI device is determined utilizing the CMDB, and the security computer performs a vulnerability calculation for the CI device utilizing the external vulnerability data and associated trust zone data. This is also done for a second CI device. The vulnerability calculations for both are compared and this comparison serves as a basis for prioritizing an action to be taken on the CI device or associated other network components.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
63.
METHOD AND APPARATUS FOR REDUCING SECURITY RISK IN A NETWORKED COMPUTER SYSTEM ARCHITECTURE
An apparatus and associated method are provided for reducing a security risk in a networked computer system architecture. The method comprises receiving at a security computer external vulnerability data from an external source regarding vulner abilities associated with an attack vector for configuration item (CI) data related to a (CI) device, of the networked computer system. The security computer accesses a configuration management database (CMDB) and the CI data related to the physical device is read. Trust zone data associated with the CI device is determined utilizing the CMDB, and the security computer performs a vulnerability calculation for the CI device utilizing the external vulnerability data and associated trust zone data. This is also done for a second CI device. The vulnerability calculations for both are compared and this comparison serves as a basis for prioritizing an action to be taken on the CI device or associated other network components.
An apparatus and related method are provided for generating a graphical display region for display of a plurality of pixels of a display device, comprising generating a timeline axis for display in the graphical display region, receiving requester event data for a plurality of requester events from a requester device relating to a request and storing the requester event data, including a time of occurrence for each requester event, and fulfiller event data for fulfiller events from a fulfiller device and storing the fulfiller event data, calculating a time scale for the timeline axis such that requester events and fulfiller events are displayable at a position along the timeline axis proportional to their respective time of occurrence, and a respective axial position for requester indicia representing the requester events and fulfiller indicia representing the fulfiller events at a position along the timeline axis proportional to their respective time of occurrence.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04842 - Selection of displayed objects or displayed text elements
Systems and methods for using instrumentation for maintenance of a user-configured program in a cloud computing environment are disclosed. The instrumentation includes intercepting operation data pertaining to the user-configured program, including a start time, an execution time interval, an operation, and an origin of the operation, stripping operation-specific variable data from the operation data, aggregating the stripped operation data based on the start time and the origin to form aggregated operation data, and storing the aggregated operation data within a time series database in the execution time interval based on the start time.
Systems and methods are disclosed for computer network threat assessment For example, methods may include receiving from client networks respective threat data and storing the respective threat data in a security event database, maintaining affiliations for groups of the client networks, detecting correlation between a network threat and one of the groups, identifying an indicator associated with the network threat, and, dependent on the affiliation for the group, identifying a client network and generating a message, which conveys an alert to the client network, comprising the indicator; responsive to the message, receiving, from the client network, a report of detected correlation between the indicator and security event data maintained by the client network, and updating the security event database responsive to the report of detected correlation
Automatic automated electronic computing and communication system event analysis and management includes identifying an event, generating a computer readable representation of the electronic computing and communication system using automated topology enumeration, identifying an element of the electronic computing and communication system based on the representation, identifying a metric for the element, automatically investigating to determine a value for the metric, generating a remediation priority for the element based on a metric weight associated with the metric and a network layer value associated with a network layer associated with a network layer role associated with the element, and generating a graphical representation of the electronic computing and communication system indicating the remediation priority.
H04L 41/0631 - Management of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 41/0654 - Management of faults, events, alarms or notifications using network fault recovery
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
H04L 41/12 - Discovery or management of network topologies
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
68.
DISTRIBUTED COMPUTING SYSTEM WITH RESOURCE MANAGED DATABASE CLONING
In a distributed computing system, cloning operations determine when each of multiple backup database instances most recently experienced an update. If a most recently updated backup database instance was updated within a prescribed time period of one or more other backup database instances, a source instance for cloning is deemed to be one of these database instances satisfying a prescribed proximity criteria relative to a designated database instance. If a difference in update times is greater than the prescribed time period for the two most recent backup database instances, the source instance for cloning is deemed to be the most recently updated backup database instance. The control center conducts cloning to a target instance using the selected backup database instance as a source instance.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/21 - Design, administration or maintenance of databases
G06F 12/16 - Protection against loss of memory contents
69.
DISTRIBUTED COMPUTING SYSTEM WITH RESOURCE MANAGED DATABASE CLONING
In a distributed computing system, cloning operations determine when each of multiple backup database instances most recently experienced an update. If a most recently updated backup database instance was updated within a prescribed time period of one or more other backup database instances, a source instance for cloning is deemed to be one of these database instances satisfying a prescribed proximity criteria relative to a designated database instance. If a difference in update times is greater than the prescribed time period for the two most recent backup database instances, the source instance for cloning is deemed to be the most recently updated backup database instance. The control center conducts cloning to a target instance using the selected backup database instance as a source instance.
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
H04L 12/16 - Arrangements for providing special services to substations
70.
CLASSIFICATION BASED AUTOMATED INSTANCE MANAGEMENT
Systems, apparatuses, and methods for classification based automated instance management are disclosed. Classification based automated instance management may include automatically commissioning an application instance based on a plurality of classification metrics, and automatically monitoring the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include identifying a plurality of instance monitoring policies associated with the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include automatically suspending the application instance plurality of instance monitoring policies and automatically decommissioning the application based on the plurality of instance monitoring policies.
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
G06F 9/44 - Arrangements for executing specific programs
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
Systems, apparatuses, and methods for displaying a visual task board comprising a permitted assignment user interface are disclosed. Displaying a permitted assignment user interface may comprise generating a first card representing a first record, wherein the first record comprises an information element that has a first value of a visualization metric, generating an output for display, the output comprising a first lane representing the first value of the visualization metric and comprising the first card, and, in response to operator input indicating a primary context and on a condition that an association between the primary context and the first record is prohibited, updating the output by generating an updated first card representing the first record and indicating that the association between the first record and the primary context is prohibited, and generating an updated output for display omitting the first card and comprising the updated first card.
A failure resistant distributed computing system includes primary and secondary datacenters each comprising a plurality of computerized servers. A control center selects orchestrations from a predefined list and transmits the orchestrations to the datacenters. Transmitted orchestrations include less than all machine-readable actions necessary to execute the orchestrations. The datacenters execute each received orchestration by referencing a full set of actions corresponding to the received orchestration as previously stored or programmed into the computerized server and executing the referenced full set of actions. At least one of the orchestrations comprises a failover operation from the primary datacenter to the secondary datacenter. Failover shifts performance of task from a set of processing nodes of the primary datacenter to a set of processing nodes of the secondary datacenter, such tasks including managing storage accessible by one or more remote clients and running programs on behalf of remote clients.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
A method is described for providing a failover between a primary datacenter and a standby datacenter. The method comprises detecting that a failover condition exists in the primary datacenter; stopping processing on the primary datacenter; ensuring that each database of the primary datacenter is in read-only mode; ensuring that each database of the standby datacenter is in read/write mode; and redirecting communications from the primary datacenter to the standby datacenter.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
Implementations of a system, method and apparatus described herein execute a discovery process to identify a plurality of computing devices within a computer network and a respective configuration associated with each of the plurality of computing devices. Upon discovery of a first computing device configured by an agent, configuration management of the computer network is searched for a definition used by the agent to configure the first computing device, and the discovery process for the first computing device is modified based on the definition to identify a first plurality of configuration items associated with a current configuration of the first computing device. Finally, a service model database is updated with the first plurality of configuration items.
H04L 41/046 - Network management architectures or arrangements comprising network management agents or mobile agents therefor
H04L 41/083 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for increasing network speed
H04L 41/085 - Retrieval of network configuration; Tracking network configuration history
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
H04L 41/12 - Discovery or management of network topologies
H04L 41/50 - Network service management, e.g. ensuring proper service fulfilment according to agreements
A method of managing power in a computing system is provided. The method comprises: assessing incoming work; assessing service level agreements related to the incoming work; and coordinating with an operating system layer to control hardware of the computing system based on the service level agreements and a power consumption goal.
G06F 1/28 - Supervision thereof, e.g. detecting power-supply failure by out of limits supervision
G06F 9/06 - Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
patents
