A plurality of permissions associated with the on-demand computing services environment may be identified. Each of the permissions may identify a respective one or more actions permitted to be performed within the on-demand computing services environment. Each of the permissions may be granted to a respective one or more user accounts within the on-demand computing services environment. A degree of overlap between a first group of the user accounts granted a first one of the permissions and a second group of the user accounts granted a second one of the permissions may be determined. When the degree of overlap exceeds a designated threshold, a designated permission set that includes the first permission and the second permission may be created.
Embodiments described herein provide a document summarization framework that employs an ensemble of summarization models, each of which is a modified version of a base summarization model to control hallucination. For example, a base summarization model may first be trained on a full training data set. The trained base summarization model is then fine-tuned using a first filtered subset of the training data which contains noisy data, resulting in an “anti-expert” model. The parameters of the anti-expert model are subtracted from the parameters of the trained base model to produce a final summarization model which yields robust factual performance.
Database systems and methods are provided for securing actions associated with graphical user interface (GUI) elements within an instance of a web application using a web application firewall. One method of securing an action associated with a GUI element within a GUI display of an instance of a web application involves monitoring a location associated with the GUI element associated with the action within the GUI display of the instance of the web application, detecting an event associated with the GUI element within the location of the GUI display, capturing event metadata associated with the event within a context of the instance of the web application, authenticating the event when the event metadata corresponds to authentication configuration metadata associated with the GUI element, and providing event data corresponding to the event to the GUI element to initiate the action in response to authenticating the event.
An utterance modification system may receive a first utterance from a first user during an interactive conversation session between the first user and a second user. The utterance modification system may further receive a second utterance from the second user that is in a speech-based format. The utterance modification system may then transmit a prompt that includes the second utterance in a text-based format and a set of prompt parameters to a large language model (LLM). In response, the utterance modification system may receive a third utterance from the LLM that may be based on the second utterance and associated with a target user tone. Further, the utterance modification system may transmit the third utterance to the first user in a speech-based format.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
5.
MECHANISMS FOR UTILIZING ADDITIONAL DATABASE FUNCTIONALITY IN A LINKED DATABASE SYSTEM
Techniques are disclosed that pertain to linked database systems. A computer system implements a first database system that manages a table storing data for a tenant. The computer system may receive an indication to provision, at a second database system having a database management engine of a different type than a database management engine of the first database system, data of the tenant stored in the table. The computer system provisions the data in data structures at the second database system and permits the tenant to perform, on the data, a first set of operations at the first database system and a second set of operations at the second database system. The second set of operations includes functionality not included in the first set of operations. The computer system may receive a result of processing by the tenant using the second database system and store the result in the table.
A computing device of a data processing system may receive an indication from a user to create a communication process flow that includes a set of actions that control electronic communications between an entity and a set of users. The computing device may further receive one or more user inputs that indicate at least two first action variations of a first action of the set of actions and at least two second action variations of a second action of the set of actions. The system may then generate the communication process flow to include a set of paths for a set of combinations of the at least two first action variations and the at least two second action variations based on receiving the one or more user inputs. The system may then execute the communication process flow that includes the set of paths for the set of users.
Techniques are described herein for a method of determining a similarity of each neuron in a layer of neurons of a neural network model to each other neuron in the layer of neurons. The method further includes determining a redundant set of neurons and a non-redundant set of neurons based on the similarity of each neuron in the layer. The method further includes fine tuning the set of non-redundant neurons using a first set of training data. The method further includes training the set of redundant neurons using a second set of training data.
A computing device of a data processing system may receive an indication of a creation of a communication process flow object that includes a set of paths for a set of actions that control electronic communications between an entity and a set of users. The computing device may receive a first user input indicating a goal for the set of paths where the goal is based on data stored within an external data platform. The computing device may then route at least a subset of the set of users via one or more paths of the set of paths based on a result of the one or more paths satisfying the goal for the set of paths of the communication process flow. Further, the computing device may distribute a subset of the electronic communications to the subset of the set of users in accordance with the one or more paths.
A plurality of permissions associated with the on-demand computing services environment may be identified. Each of the permissions may identify a respective one or more actions permitted to be performed within the on-demand computing services environment. Each of the permissions may be granted to a respective one or more user accounts within the on-demand computing services environment. A degree of overlap between a first group of the user accounts granted a first one of the permissions and a second group of the user accounts granted a second one of the permissions may be determined. When the degree of overlap exceeds a designated threshold, a designated permission set that includes the first permission and the second permission may be created.
An application server may receive, from a client and at an interface for accessing a large language model, a prompt for a response from the large language model. The application server may receive, via a model interface, a streaming output of the large language model, where the streaming output includes a first portion of the response and a threshold number of tokens. The application server may then provide the first portion of the response to a scoring model that determines a first incremental score indicating a first probability that the first portion of the response includes content from one or more content categories. The application server may transmit, to the client and based on the first probability, the first portion of the response, an indication of the first incremental score, or both.
A plurality of permissions associated with the on-demand computing services environment may be identified. Each of the permissions may identify a respective one or more actions permitted to be performed within the on-demand computing services environment. Each of the permissions may be granted to a respective one or more user accounts within the on-demand computing services environment. A degree of overlap between a first group of the user accounts granted a first one of the permissions and a second group of the user accounts granted a second one of the permissions may be determined. When the degree of overlap exceeds a designated threshold, a designated permission set that includes the first permission and the second permission may be created.
Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
To recover from a first database application that is in an unstable condition, a computer system deploys a first instance of a second database application with an override condition that causes the first instance to use a first database catalog used by the first database application. Content of the first database catalog is different than content expected by the second database application. The computer system performs a process to create a second database catalog that includes the content expected by the second database application. The process may include communicating with the first instance to access catalog objects from the first database catalog and insert them into the second database catalog. The computer system then deploys a second instance of the second database application without the override condition to cause the second instance to use the second database catalog that includes the content expected by the second database application.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
19.
Display screen or portion thereof with a graphical user interface
Methods, systems, apparatuses, devices, and computer program products are described. A system may obtain a set of documents associated with a knowledge base for retrieval-augmented generation (RAG). The system may generate multiple representations of the information included in the documents using multiple knowledge extraction pipelines. For example, the system may generate a set of metadata-based vector embeddings based on the documents, a set of knowledge graphs based on the documents, and a set of hierarchical tree representations based on the documents. The system may receive a user query and may retrieve contextual information from the set of vector embeddings, the set of knowledge graphs, and the set of hierarchical tree representations to augment the user query for a large language model (LLM) prompt. The system may input the prompt to the LLM, and the LLM may output a response based on the user query and the contextual information.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for backing up environments. One of the methods includes maintaining, for a cloud computing environment, first data that indicates one or more previously active sandbox environments; determining second data that indicates one or more most recently active sandbox environments; determining, using the second data, a newly added sandbox environment; determining, using a first identifier for the newly added sandbox environment and a second identifier for a prior sandbox environment from the one or more previously active sandbox environments, whether the newly added sandbox environment is likely a refresh of the prior sandbox environment; and performing one or more actions for the newly added sandbox environment using a result of the determination whether the newly added sandbox environment is likely a refresh of the prior sandbox environment.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
Techniques are disclosed relating to query planning and execution. A computer system can receive a database statement that comprises a LIKE predicate that defines a set of pattern parameters. The computer system may generate first and second query paths for a query plan associated with the database statement. The first query path utilizes an index associated with a database table specified by the database statement while the second query path does not utilize the index. The computer system executes the database statement in accordance with the query plan and values that are provided for the set of pattern parameters. As a part of executing the database statement, the computer system may evaluate those values to determine whether they are prefix constants and execute the first query path instead of the second query path if all the values are prefix constants.
Systems and methods for generating an event occurrence feedback report after receipt of an event occurrence completion indicator, the event occurrence completion indicator associated with an event occurrence identifier and received from a third party event scheduling resource, and to present the event occurrence feedback report to a client device associated with an event occurrence creator identifier are provided herein.
A system, method, and computer-readable media for creating a collaboration container in a group-based communication system are provided. A request to create the collaboration container may be received. The collaboration container may comprise a collection of multimedia files. Multiple users may add multimedia files to the collaboration containers. The multimedia files may be stored in a storage order. The multimedia files in the collaboration container may be sorted based on a sort label, such as by multimedia file topic. Upon playback, the multimedia files may be played back in a sort order distinct from the storage order. During playback, a user may comment on a multimedia file of the collaboration container. When subsequent users playback the collaboration container, the comment may be displayed with the associated multimedia file.
H04L 65/402 - Prise en charge des services ou des applications dans laquelle les services impliquent une session principale en temps réel et une ou plusieurs sessions parallèles additionnelles non-temps-réel, p. ex. le téléchargement d’un fichier lors d’une session FTP parallèle, l’introduction d’un courriel ou de services combinés
H04L 65/403 - Dispositions pour la communication multipartite, p. ex. pour les conférences
25.
Display screen or portion thereof with graphical user interface
Disclosed are some implementations of systems, apparatus, methods and computer program products for optimizing database backup transactions. A backup poller in a private subnet tracks a database backup operation and detects a failure of the database backup operation. More particularly, the backup poller detects that a failure occurred at a specific point in the database backup operation. The backup poller instructs a backup decentralizer in a public subnet to continue the database backup operation from the specific point. The backup decentralizer monitors a health of a plurality of service providers and selects a service provider of the plurality of service providers based on the health of the service provider. The backup decentralizer continues the backup operation from the specific point using the selected service provider.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
27.
INTEGRATING AND MANAGING SOCIAL NETWORKING INFORMATION IN AN ON-DEMAND DATABASE SYSTEM
Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
28.
METHOD AND SYSTEM FOR APPLICATION PROGRAMMING INTERFACE BASED CONTAINER SERVICE FOR SUPPORTING MULTIPLE MACHINE LEARNING APPLICATIONS
A method and system for an application programming interface (API) based container service for supporting multiple machine learning (ML) applications is described. In particular, a scoring service container includes a base scorer to interface with a ML serving infrastructure using the API. The scoring service container also includes an application specific scorer, which itself includes a model loader and a scoring function. A model identifier is provided to the model loader, and it provides a model object. At least some parameters in a request from a client application are passed to the scoring function, which produces a scoring. The base scorer returns the scoring according to the API to the ML serving infrastructure for delivery to the client application.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
Disclosed herein are system, method, and computer program product embodiments for using generative AI for prompt comparison. The system may receive a prompt. The prompt may include a request for information. The system may identify a stored prompt based on a similarity value between a received prompt for a large language model (LLM) and the stored prompt, the stored prompt including a response generated by the large language model (LLM). The system may generate a response using the LLM if the similarity value between the received and stored prompts is below a predefined threshold. The system may then modify the response by applying a first rule associated with a first designated phrase, and a second rule associated with a second designated phrase, where the first designated phrase comprises a banned phrase and where the second designated phrase comprises a selected phrase.
A retrieval augmented generation (RAG) based query reformulation pipeline for a Query and Answer (QA) system is described. This pipeline leverages a Directed Acyclic Graph (DAG) and involves several operations, including retrieval of documents and knowledge graph triplets based on the initial query, reranking of retrieved elements based on relevance, refinement and summarization of relevant document chunks and knowledge triplets, reformulation of the initial query, and generation of a natural language response. The response is generated using a large language model (LLM) and is grounded in the knowledge base, which supports factual accuracy and consistency.
Methods, apparatuses, and computer program products are disclosed. The method may include receiving a first request to ingest a document. The method may include generating, using a large language model (LLM), a knowledge graph including a plurality of graph triples, each graph triple including a first node, a second node, and an edge connecting the first node and the second node, where each first node corresponds to a first element type of the document, where each second node corresponds to a second element type of the document, and where each edge corresponds to a third element type of the document. The method may include receiving a second request to generate a generative response with the LLM. The method may include presenting a response to the second request, the response generated by the LLM based at least in part on the knowledge graph.
Methods, systems, apparatuses, devices, and computer program products are described. A system may obtain a set of documents for input into a query response system, generate a set of vector embeddings based on the set of documents and a semantic vector augmentation pipeline, and generate a set of knowledge graphs based on the set of documents and a knowledge graph augmentation pipeline, where each knowledge graph includes a set of multiple knowledge graph triplets. The system may receive a user query and augment the user query to generate an augmented prompt using at least one or more vector embeddings from the set of vector embeddings and one or more knowledge graph triplets from the set of knowledge graphs. The system may provide, to a large language model (LLM), the augmented prompt as an input and may receive, as an output of the LLM, a response to the augmented prompt.
A method of training a neural network model for improved embedding performance is provided. A first plurality of data samples are received via a data interface. A plurality of batches are generated, including a first batch that includes data samples associated with a single first task, and a second batch that includes data samples associated with a single second task. A training process to the neural network model is performed using the plurality of batches. The training includes computing a first loss based on a first loss objective function customized for the first task and a second loss based on a second loss objective function customized for the second task, and updating parameters of the neural network model based on the first loss and the second loss via backpropagation.
A computing services environment may include a database system may store database records for client organizations accessing computing services including a conversational chat assistant. The computing services environment may also include an application server receiving natural language user input for the conversational chat assistant and a generative language model interface providing access to one or more generative language models. The computing services environment may also include an orchestration and planning service configured to analyze the natural language user input via a generative language model of the one or more generative language models to identify a plurality of actions to execute via the computing services environment to fulfill an intent expressed in the natural language user input. The computing services environment may be configured to execute the plurality of actions to determine a natural language response message.
A computing services environment may include a database system storing a plurality of database records for a plurality of client organizations accessing computing services including a conversational chat assistant, an application server receiving user input for the conversational chat assistant, a generative language model interface providing access to one or more generative language models, an orchestration and planning service configured to identify a plurality of actions based on the user input and to execute the plurality of actions to determine a natural language response message, and/or a metadata framework. The metadata framework may specify information related to the conversational chat assistant. The metadata framework may include a definition associated with an action of the plurality of actions. The definition may include one or more inputs, one or more outputs, and one or more operations performed via the computing services environment.
A computing services environment may include a database system storing a plurality of database records for a plurality of client organizations accessing computing services including a conversational chat assistant. The computing services environment may also include an application server may receive user input for the conversational chat assistant, a generative language model interface, an orchestration and planning service configured to identify one or more actions based on the user input, to execute the one or more actions to determine a natural language response message, and to determine a recommended action for selection via a conversational chat interface. The computing services environment may also include a communication interface configured to transmit the natural language response message and a user interface generation instruction executable by the client machine to provide a selection affordance for selecting the recommended action.
A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, a metadata repository storing metadata entries describing and defining interaction data for interacting with agents, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An input prompt including the natural language request message and agent descriptions selected from the plurality of metadata entries may be determined and transmitted to a generative language model. A prompt completion including a selection of the designated agent based on the plurality of agent description may be received from the generative language model. Novel text responsive to the natural language request message may be generated by transmitting a request to the designated agent.
A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, a metadata repository storing metadata entries characterizing a actions capable of being performed via the computing services environment, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An input prompt including the natural language request message and descriptions of actions selected from the metadata entries may be determined and transmitted to a generative language model. A prompt completion including a plan that includes a subset of the actions and a natural language description of the plan may be received from the generative language model and sent to a client machine via the conversational chat interface.
In some embodiments, a method receives a schema registry in a file. The schema registry aggregates schema files for a data model that is associated with a database system used by servers and consumer devices. The schema files is in a first software language that describes objects in the data model, and the schema registry is in a second software language used by the consumer devices. A first function in the schema registry is executed for an object to retrieve an original schema for the object in the schema files to create first software code for the object with the original schema for an application that uses the data model. A second function in the schema registry is executed for the object to generate a new object from the original schema for the object to create second software code for a new object with the original schema for the application.
An entity-level visibility statistic may be determined for a database entity in a database system based on one or more visibility rules providing access to instances of the database entity to one or more user accounts. A user-level visibility statistic quantifying a set of instances of the database entity accessible to a user account via the one or more visibility rules may be determined based at least in part on the entity-level visibility statistic. A request may be received by the user account to execute an input database query retrieving one or more of the instances of the database entity. A database object retrieval query including two or more data security subqueries evaluating accessibility of the one or more instances of the database entity and positioned based at least in part on the user-level visibility statistic may be determined based on the input database query.
A computing services environment may include a database system storing a plurality of database records for client organizations accessing computing services including a conversational chat assistant accessible via various communication channels. The computing services environment may also include a communication interface configured to receive an input message from a client machine via a communication channel, a generative language model interface providing access to one or more generative language models, and an orchestration and planning service. The orchestration and planning service may be configured to analyze the input message to determine a novel text passage via a generative language model, to determine novel text formatting information based on designated text formatting configuration information specifying one or more parameters for formatting text generated for transmission via the communication channel, and to transmit the novel text passage and the novel text formatting information to the client machine via the communication interface.
G06F 40/35 - Représentation du discours ou du dialogue
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
46.
Generative Language Model Dynamic Input Disambiguation In A Database System
A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An information enrichment and disambiguation process may be executed to determine candidate values corresponding to a text portion of the natural language request message. Novel clarification text requesting clarification of the candidate information may be determined and transmitted via the conversational chat interface. Updated information may be determined based on the candidate information and clarification input received via the conversational chat interface. Novel response text responsive to the natural language request message may be determined based on the updated information.
Techniques for providing application contextual information. One or more sets of database context identifiers corresponding to events that occur within the database are generated by the database. The one or more sets of database context identifiers have at least one application context field. A session identifier corresponding to a session to be monitored is sent from the application to the database. Information to be stored in the database with the session identifier is sent to the database. Database logs and application logs are correlated using at least the session identifier.
Disclosed herein are system, method, and computer program product embodiments for the design, architecture, and implementation of various aspects of an API gateway. A computer implemented method may access, by an API portal, a catalog comprising a plurality of APIs. The catalog may be configured to return a subset of the plurality of APIs based on a search. Each API at the catalog may include at least one feature comprising an API type. The method may then download one or more APIs from the plurality of APIs to the API portal. The method may further manage access to the API portal, where the access is associated with one or more users. The method may customize a layout of the API portal, where the layout includes at least one customizable feature comprising a color scheme. The method may then generate logs and metrics corresponding to each API at the API portal.
Embodiments described herein provide a method for building a hierarchical structure of a plurality of neural network models for performing a task. The method includes the following operations. A task instruction is received via a data interface. A first neural network model generates a first sub-task from the task instruction. A second neural network model is selected from the plurality of the neural network models based on the first sub-task. A first connection is built via a first API, between the first neural network model and the second neural network model. The first neural network model generates a first sub-task package in a format compliant with the second neural network model. A first output is received via the first connection from the second neural network model that executes the first sub-task package. The first neural network model generates a second sub-task based on the task instruction and the first output.
In some embodiments, a method determines a first representation for an entity that received a request. Second representations are searched in a prompt store to retrieve a second representation that is determined to match the first representation. A prompt template for a model is associated with the second representation. The method searches for relevant documents for the request in a knowledge base store and retrieves information from a document that is considered relevant to the request. The information provides context for the request. The method inserts at least a portion of the information into the prompt template to generate a prompt that is based on the context and submits the prompt to the model to receive a response. The method responds to the request using the response.
Techniques are disclosed relating to automating authentication decisions for a multi- factor authentication scheme based on computer learning. In disclosed embodiments, a mobile device receives a first request corresponding to a factor in a first multi-factor authentication procedure. Based on user input approving or denying the first request, the mobile device sends a response to the first request and stores values of multiple parameters associated with the first request. The mobile device receives a second request corresponding to a factor in a second multi-factor authentication procedure where the second request is for authentication for a different account than the first request. The mobile device automatically generates an approval response to the second request based on performing a computer learning process on inputs that include values of multiple parameters for the second request and the stored values of the multiple parameters associated with the first request. The approval response is automatically generated and sent without receiving user input to automate the second request.
H04W 12/64 - Sécurité dépendant du contexte dépendant de la localisationSécurité dépendant du contexte dépendant de la proximité utilisant des zones géorepérées
52.
Systems, Methods, And Devices for Automatic Application Programming Interface Model Generation Based on Network Traffic
Systems, methods, and devices facilitate generation of application programming interface (API) objects. Methods may discover, using one or more components of a cloud computing platform, ingress and egress API traffic associated with one or more hosted applications executing on the cloud computing platform. Methods may collecting API traffic data for a service used by the one or more hosted applications, where the API traffic data is associated with calls to the service made by a first client application executing on a device external to the cloud computing platform. Methods may form one or more API objects based on the API traffic data, the one or more API objects being formed based, at least in part, on one or more API specifications. Methods may provide, based on a request from a second client application, the one or more API objects.
Database systems and methods are provided for managing usage of large language models (LLMs). One method involves dividing text data into primary chunks using input criteria associated with an LLM service, generating secondary chunks by merging respective pairs of adjacent primary chunks, and inputting a respective secondary chunk to the LLM service when a semantic similarity between a conversational input to a user interface and the respective secondary chunk of the one or more secondary chunks is greater than a threshold. The LLM service generates response data responsive to the conversational input based at least in part on a subset of the text data associated with the respective secondary chunk, and a response is provided to the conversational input at the user interface based at least in part on the response data generated by the LLM service.
Embodiments described herein provide a unified LLM training pipeline that hands the diversity of various data structures and formats involving LLMs agent trajectories. These pipelines are specifically designed to transform incoming data into a standardized representation, ensuring compatibility across varied formats. Furthermore, the data collection undergoes a filtering process to ensure high-quality trajectories, adding an additional layer of refinement to the dataset. In this way, the training pipeline not only unifies trajectories across environments but also enhances the overall quality and reliability of the collected data for LLM training.
A database system in a computing system may store data records communication contact information for accounts. A communication package repository may store a communication package definition configured by an external entity and defining access information for a communication channel outside of the computing system via an external computing system managed by the external entity. A tenant space may store packages installed for a tenant. A communication interface may expose a communication access service receiving from the external computing system a request to establish communication with the tenant from a remote computing device. An agent client machine interface may create a communication session between the remote computing device and an agent client machine authenticated to an agent account.
A request to establish a communication session from an end point to a tenant of a computing services environment may be received from an external computing system managed by an external entity in accordance with a designated communication package definition configured by the external entity and defining access information for a designated communication channel outside of the computing services environment. An agent account of a plurality of agent accounts associated with the tenant may be determined based on routing configuration information specified in the designated communication package definition. The communication session may be established via the designated communication channel from the end point through the external computing system and the computing services environment to a first client machine authenticated to the agent account. One or more messages may be transmitted from the end point to the first client machine via the communication session.
H04L 67/141 - Configuration des sessions d'application
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
A communication session may be established via a designated communication channel from an end point through an external computing system and the computing services environment to a client machine authenticated to a database system account for an agent of a tenant of the computing services environment. The communication session may be established in accordance with a designated communication package definition configured by an external entity and defining protocol information for the designated communication channel. Messages may be sent from the client machine to the end point through the computing services environment via the communication session in accordance with the designated communication package definition. Transmitting the messages may include receiving an indication of an event detected at an event handler in a user interface component included in a user interface presented at the client machine.
Systems and methods for receiving, at a server that includes a reschedule handler, a request with a service resource by a requestor. The server determines one or more available resources of the service resource to handle the request. At least one match between one or more criteria of the request and the availability of the one or more resources of the service resource is determined. A time slot for the requestor with the service request is scheduled based on the determined at least one match and based on an acceptance of the request by the service resource that is received by the server. The server transmits the scheduled time slot with the service resource to the requestor.
Embodiments described herein provide a Transformer architecture for time series data forecasting. Specifically, the Transformer based time series model may be built on a transformer architecture having one or more multi patch size projection layers in the encoder and the decoder, and an any-variate attention module. The Transformer based time series model may receive multivariate time series and consider all variates as a single sequence. Patches of the input are subsequently projected into vector representations via a multi patch size input projection layer. The output tokens of forecasted time series data are then decoded via the multi patch size output projection layers in the parameters of the mixture distribution.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
63.
UPGRADING MULTI-INSTANCE SOFTWARE USING ENFORCED COMPUTING ZONE ORDER
Techniques for preventing deadlock when upgrading a plurality of instances of a software service that is distributed across multiple different computing zones. Upgrade software executing on a cloud computer system receives an upgrade request to upgrade the plurality of instances. Respective upgrade processes are initiated in parallel. Node acquisition portions of the respective upgrade processes have a constraint on parallelization, as they are performed using a common upgrade procedure in which a given instance is upgraded by acquiring nodes in different ones of the computing zones according to a specified order. After acquiring the nodes according to the specified order, an updated instance is deployed to the acquired nodes to update the given instance. The acquiring of the nodes may be performed by node-securing pods in some embodiments, with the specified order enforced with affinity and anti-affinity rules.
Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. Narrative analytics that are linked to communication goal statements can employ a conditional outcome framework that allows the content and structure of resulting narratives to intelligently adapt as a function of the nature of the data under consideration. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired communication goal.
Techniques are described for securing secrets in software build workflows. In some implementations, build instructions call for execution of a first program module and a second program module, where the first program module has been approved to make a privileged request, but the second program module has not. The first program module can be stored in a trusted repository, separately from the second program module. When the first program module is loaded for execution, a cryptographic signature can be validated to determine that the first program module is authentic and as a condition for passing a privileged credential to the first program module. The second program module has no access to the privileged credential. Instead, when the second program module is loaded for execution, a determination can be made whether the second program module makes any privileged requests. Any privileged requests from the second program module will not be fulfilled.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Techniques are disclosed relating to database configuration settings overrides. In some embodiments, a database system stores a set of default configuration settings that control operation of the database system. The database system receives a query requesting data from the database system, and metadata about the query. The database system determines, based on the query and the metadata, that a configuration settings override has been specified for the query, where the configuration settings override indicates that one or more of the default configuration settings are to be replaced with one or more configuration settings specific to the query. In response to the determining that a configuration settings override has been specified, the database system executes the query using the one or more specific configuration settings.
Techniques are disclosed that relate to skip lists. A computer system maintains a skip list having towers of varying depths and entries storing pointers to other towers. A first tower includes an entry at a particular depth storing a pointer to access an entry of a second tower. The pointer includes first similarity information indicating an amount of similarity between a key of the first tower and a key of the second tower. The computer system performs a traversal of the skip list for a search key. The computer system generates second similarity information indicating an amount of similarity between the first tower's key and the search key. Based on a comparison involving the first and second similarity information and without accessing the second tower to obtain information about its key, the computer system determines whether to traverse to the second tower using the pointer or descend the first tower.
Techniques for generating a summary using a machine-learning model native to the operating system running on a user device are discussed herein. The communication platform may receive an instruction to generate a summary to be displayed to a user profile. In such cases, the communication platform may determine whether to generate the summary using on-device systems or using systems in a server of the communication platform (e.g., a device separate from the user device). Based on determining to generate the summary using the on-device systems, the communication platform may identify data to summarize. The communication platform may input the data into a machine-learning model (or large language model (LLM)) residing within the operating system of the user device and receive, as output, a summary. In such cases, the communication platform may cause the summary to be displayed via the user interface of the user device associated with the user profile.
Systems, devices, and techniques are disclosed for network security policy generation and distribution. A security policy written using a Domain Specific Language (DSL) for network security may be received. The security policy may be associated with a service owner and a control plane. A representation of the security policy may be generated from the security policy. A configuration bundle of the service owner may be updated with the representation of the security policy. The security policy may be determined to be approved. A rule set may be generated from the representation of the security policy. A differential between the rule set and a current rule set may be determined. A security component associated with the control plane based on the differential may be configured.
A computer-implemented method is disclosed for predicting, based on a previous usage of a cloud-based computing resource by a number of users of the cloud-based computing resource, a future usage of the cloud-based computing resource. The method includes predicting, based on the predicted future usage of the cloud-based computing resource, an anomaly event at the cloud-based computing resource. The method also includes implementing a first anomaly mitigation action, based on the prediction of the anomaly event at the cloud-based computing resource and re-evaluating a status of the anomaly event at the cloud-based computing resource after the implementation of the first anomaly mitigation action. The method further includes implementing a second anomaly mitigation action at the cloud-based computing resource, based on the re-evaluation of the status of the anomaly event.
H04L 41/069 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant des journaux de notificationsPost-traitement des notifications
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
Methods, systems, apparatuses, devices, and computer program products are described. An application server or a data processing system may generate a set of candidate natural language queries that correspond to a data object (e.g., document, report, assert) based on inputting a set of metadata associated with the data object into a large language model (LLM). The system may embed the candidate natural language queries into a first set of vectors, where a query space may include a collection of the first set of vectors related to the data object. In addition, the system may embed a natural language query received from a user into a second vector. The system may perform a vector-space comparison of the second vector to the first set of vectors or the query space, and retrieve a data object associated with the natural language query based on the comparison.
A method to approximate a segment count for a normalized dataset. The method includes sampling items in the primary database object to generate a sample, executing a segmentation count query on the sample to determine how many items in the sample satisfy a set of segment criteria, determining an error value based on an estimated sample size of the sample, a number of items in the sample that satisfy the set of segment criteria, and a confidence level value, determining a range of counts for the segment count based on the number of items in the sample that satisfy the set of segment criteria, the error value, and a total number of items in the primary database object, and providing the range of counts representing an approximated segment count for the normalized dataset.
Methods, systems, apparatuses, devices, and computer program products are described. An application server or a data processing system may convert a set of metadata associated with a data object (e.g., document, record, asset) from a first structured format into a second serialized format. The set of metadata in the second serialized (e.g., unstructured) format may be input in a large language model (LLM). The LLM may generate a first natural language summary associated with the data object based on the set of metadata. After receiving a natural language query from a user, the LLM may generate a second natural language summary associated with the data object based on the natural language query. The natural language summaries may be vectorized, and the vectorized versions may be compared. Based on the comparison, an indication of the data object corresponding to the natural language query may be displayed.
Techniques are disclosed relating to implementing an end-to-end orchestration for a datacenter on a cloud platform. A datacenter may be orchestrated on a cloud platform according to a declarative specification that describes dependences between datacenter entities (e.g., services) in the datacenter. Some datacenter entities may execution dependencies, which include activities, steps, or events that need to be completed for the datacenter entities to be ready for orchestration. Accordingly, in order for an orchestration workflow to be able to execute from beginning to end without interruption, all the execution dependencies for all the datacenter entities in the orchestration workflow need to be completed. The techniques disclosed include automatically initiating execution of the execution dependencies and waiting for indications that the execution activities are completed before executing the orchestration workflow.
Techniques are disclosed relating to implementing an incremental update to an existing datacenter on a cloud platform. The datacenter may have been built on a cloud platform according to a declarative specification that describes dependencies between datacenter entities in the datacenter. When an update is requested for the datacenter (e.g., by a customer or other entity), the system determines datacenter entities that are being changed in association with the update and execution dependencies associated with the update request. The system then initiates execution of the execution dependences and waits for the execution dependencies to be completed. Once the execution dependencies are completed, the system initiates orchestration of the datacenter in order to update the datacenter on the cloud platform with the addition or removal of datacenter entities on the datacenter.
Techniques are disclosed relating to implementing a statement-level INSTEAD OF trigger. In one embodiment a computer system stores trigger information associated with a statement-level database trigger executable to initiate execution of at least one trigger instruction for a database instead of performing a particular database operation, on a database view, specified by a database operation statement. The computer system receives a first database operation statement specifying performance of the particular database operation on the database view and identifies a set of target rows, within the database view, targeted by the first database operation statement. In addition, the computer system generates a reference table associated with the database view, where the reference table includes rows corresponding to the target rows. The computer system executes the statement-level database trigger instead of executing the database operation statement, where executing the statement-level database trigger includes accessing the reference table.
Embodiments described herein provide bootstrapping language-images pre-training for unified vision-language understanding and generation (BLIP), a unified VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP enables a wider range of downstream tasks, improving on both shortcomings of existing models.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
A computer-implemented method is disclosed for predicting, based on a previous usage of a cloud-based computing resource by a number of users, a future usage of the cloud-based computing resource and then predicting, based on the predicted future usage, an anomaly event at the computing resource. The method also includes identifying a top contributing user that is responsible for the anomaly event and throttling an access of the top contributing user to the computing resource. The method further includes evaluating a speed of data requests received at the computing resource from the top contributing user after the throttling, and a utilization level of the computing resource. The method also includes dynamically adjusting the speed of data requests received at the computing resource, based on the evaluation of the utilization level of the computing resource, to maintain the utilization level of the computing resource within a predetermined target range.
Disclosed herein are system, method, and computer program product embodiments for implementing variable a declarative authentication engine. The system generates a schema that includes a field and has a format defined by an authentication protocol associated with a service. The system then validates a connection request based on comparing the field of the generated schema to a field of the connection request for the service, wherein the connection request is formatted according to the schema and received from a client device. The system then provides the client device access to the service according to the connection request based on a result of the validating.
A method and system for classifying a triage-related message related to a software application security technical problem is provided. A triage-related classification is generated for the triage-related message by applying a processor-implemented machine learning model that has been trained to analyze the text of the triage-related message. The generated triage-related classification is sent to a user for remediating the software application security technical problem.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
Techniques are disclosed relating to database query optimizers. In some embodiments, a system receives, from a query optimizer, a plurality of query plans for a database maintained by the database system. The system retrieves a set of database statistics for the database and generates, via a data synthesizer, a plurality of synthetic datasets, where generating a given synthetic dataset is performed based on a given query plan of the plurality of query plans and the set of database statistics, and includes generating a plurality of synthetic data tuples. The system executes the plurality of query plans on the plurality of synthetic datasets and updates the query optimizer based on results of executing the plurality of query plans on the plurality of synthetic datasets. The disclosed data synthesis may advantageously improve query performance due to more efficient query plans being selected for execution of requested queries.
Techniques are disclosed relating to determining query plans for execution by database systems. In various embodiments, a query optimizer determines a first query plan to implement a query requesting data from a database system. The determining includes selecting one of a plurality of query plans evaluated based on a cost analysis and caching plan fragments of the unselected query plans. The database system can then determine a second query plan for the query by replacing a plan fragment in the first query plan with one of the cached plan fragments of the unselected query plans.
A runtime agent that is executable on a virtual machine may obtain one or more identifiers that correspond to one or more software classes from a first configuration file that is configured for the runtime agent. The runtime agent may monitor for loading of the one or more software classes by a first computer program that is being executed on the virtual machine. Further, the runtime agent may execute one or more actions based on detecting the loading of the one or more software classes by the first computer program where the one or more actions may impact the execution of the first computer program on the virtual machine.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
Techniques for determining video transcoding setting(s) for a video content based on information associated with a video content request and encoding the video contents into one or more encoded video contents based on the video transcoding settings are discussed herein. For example, a communication platform may receive a request associated with a video content. The communication platform may determine, based at least in part on the request, device information associated with one or more receiver devices. The communication platform may determine, based at least in part on the device information associated with the receiver devices provided by the communication platform, one or more video transcoding settings associated with the video content. The communication platform may further send one or more encoded video contents encoded based on the one or more video transcoding settings to the receiver devices.
Techniques are disclosed relating to storing database extents in physical storage nodes. To store the extents, a physical storage node of a computer system first accesses assignment metadata, which includes determining 1) virtual groupings of database extents assigned to the physical storage node and 2) database extents associated with the determined one or more virtual groupings. For a given database extent, a corresponding virtual grouping is determinable by performing a first hashing operation that uses an identifier for the given database extent. The physical storage node then accesses and stores the determined database extents. The physical storage node can now service requests for data of the database system that are stored at the first physical storage node.
Techniques are disclosed relating to migrating database extents between physical storage nodes. A database system stores current and new assignment metadata mapping virtual groupings of database extents physical storage nodes, the new assignment metadata reflecting a data migration of extents between the plurality of physical storage nodes. During the migration, the database system receives 1) read requests, which it responds to by reading data from a first physical storage node identified using the current assignment metadata and 2) write requests, which it responds to by writing data to a second physical storage node identified using the new assignment metadata. Upon the migration being complete, the system identifies physical storage nodes accessed by subsequent read and write requests using the new assignment metadata.
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
87.
SYSTEM AND METHOD FOR GENERATING CRYPTOGRAPHIC SIGNATURE FOR ARTIFICIAL INTELLIGENT GENERATED CONTENT
Embodiments described herein provide a method for content transmission using a cryptographic signature. The method includes: generating, by a neural network model employing a plurality of state parameters and implemented on one or more processors, an output content; generating a string of Hash values based on the output content; creating a cryptographic signature by encrypting the string of Hash values and one or more state parameters of the neural network model using a private key; embedding the cryptographic signature in the output content; and transmitting, via a communication interface, the output content embedded with the cryptographic signature to a destination server.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
88.
Automated Retries for Orchestration of a Datacenter on a Cloud Platform
Techniques are disclosed relating to implementing automated retries during orchestration of a datacenter on a cloud platform. Generating an orchestration workflow for the datacenter may include generating an aggregate pipeline for the orchestration. The aggregate pipeline includes instances of datacenter entity pipelines that include stages for provisioning and deployment of datacenter entities. The disclosed techniques include adding retry stages to the datacenter entity pipelines that are automatically invoked in the event of failure of a datacenter entity pipeline. The retry stages are placed at the end of individual datacenter entity pipelines and conditional expressions are included that invoke retry strategies defined by owners of the datacenter entity.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
89.
DETECTING MISCONFIGURATION OF GUEST ACCOUNT SECURITY PERMISSIONS
Systems, devices, and techniques are disclosed for detecting misconfiguration of guest account security permissions. User personas may be generated from user activity data generated by access using guest accounts to controllers of a cloud computing server system. Clusters of user personas may be generated from the user personas. Anomalous user personas may be identified based on the clusters of user personas. A database query that was made to a database of the cloud computing server system, is associated with an identified user persona, and requested sensitive data may be identified from database query logs. A size of a response from the database to the identified database query may be identified from the database query logs. The size of the response may indicate that the response included the sensitive data. The cloud computing server system may prevent use of the guest account associated with the user persona.
A system may include a communication interface receiving information characterizing a customer of a first database tenant of a plurality of database tenants accessing customer relations management services. The system may also include a database system storing one or more database records including the information characterizing the customer and being stored in a profile corresponding with the customer. The database system may receive a request to determine content to provide to the customer in association with an interaction between the customer and a second database tenant. A recommended content item may be determined based at least in part on the one or more database records. A message including an instruction for presenting the recommended content item in a user interface may be transmitted from the database system to a client machine associated with the customer.
Techniques are disclosed that pertain to upgrading a database application. A computer system may determine to upgrade a database application from a current version associated with a first instance of a database catalog that defines the structure of a database that is managed by that database application. The first instance is associated with a first catalog signature that is indicative of the first instance of the database catalog. The computer system generates a second catalog signature that is indicative of a second instance of the database catalog that is associated with the different version. The computer system compares the first catalog signature and the second catalog signature to determine whether the database catalog changes between the current and different versions. Based on the comparing, the computer system then selects one of multiple upgrade processes performable to upgrade the database application to the different version and performs the selected upgrade process.
Disclosed herein are system, method, and computer program product embodiments for secure user interface (UI) customization in an embedded application. An embodiment operates by generating an embedding code and an application configuration corresponding to an updated version of an embedded code of an embedded web application in response to a determination that the embedded web application was published successfully. The embodiment then stores the embedding code, the application configuration, and a particular version of a web component at an application server. The particular version of the web component is designated for use by the embedded web application during runtime of the embedded web application. The embodiment then configures an application endpoint to prevent the embedded web application from accessing, during runtime of the embedded web application, another version of the web component that is different from the particular version of the web component stored at the application server.
A method for testing connectivity comprises receiving, by one or more computing devices, a request for a connectivity test, and determining, by the one or more computing devices, whether a point-to-point connectivity test or a service-to-service connectivity test is to be performed. The method further comprises initiating, by the one or more computing devices, the connectivity test in response to the request and based on the determining, where initiating the connectivity test comprises invoking a connectivity testing mechanism. The method further comprises displaying, by the one or more computing devices, a location of a connectivity issue based on the connectivity test, and displaying, by the one or more computing devices, a next step to solve the connectivity issue based on the connectivity test.
A method to manage domain-based security profiles in a content delivery network (CDN) is disclosed. The method includes receiving security events detected by one or more security solutions implemented by one or more CDN instances of the CDN, determining, for each of a plurality of domains, a risk score for the domain based on the security events, determining possible next level domains for a CDN instance of the CDN, determining an updated order of an auto-adjusting list maintained by the CDN instance based on risk scores for the domains included in the auto-adjusting list and the possible next level domains for the CDN instance, and sending an update to the CDN instance to cause the CDN instance to update the order of the auto-adjusting list to reflect the updated order, wherein the order of the auto-adjusting list indicates an eviction priority for the domains included in the auto-adjusting list.
A method and apparatus for autonomous container management configuration changes to container clusters during runtime and autonomous configuration-based release orchestration. A release manager manages a staggered feature release that includes staggers, stagger order, and container clusters included in each stagger. A logging service manages logs generated by the container clusters and/or app containers. An update service determines container management configuration changes based on analysis of data provided by the logging service. A shared engine attempts to implement instructions provided by the release manager and the update service at different times. The release manager receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. The release manager, responsive to the indication of success or failure, determines to perform one of a plurality of actions, including attempting to deploy the feature release to the next stagger, and rolling back.
H04L 41/082 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant des mises à jour ou des mises à niveau des fonctionnalités réseau
H04L 41/0859 - Récupération de la configuration du réseauSuivi de l’historique de configuration du réseau en conservant l'historique des différentes générations de configuration ou en revenant aux versions de configuration précédentes
H04L 43/062 - Génération de rapports liés au trafic du réseau
A method and apparatus for autonomous configuration-based release orchestration. A first engine obtains stagger configuration data that includes an indication of container clusters in each stagger and a stagger order, selects a current stagger based on the order, and attempts to deploy the feature release to the current stagger by causing an app config update to be sent to a second engine within each container cluster of the current stagger, and receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. Responsive to the indication of success or failure, the first engine performs one of a plurality of actions that include attempting to deploy the feature release to a next one of the staggers according to the order responsive to the indication indicating success, and causing a roll back of the current stagger responsive to the indication indicating failure.
A method and apparatus for autonomous release orchestration that supports staggered releases across a plurality of container clusters. A representation of a risk level for a current release is obtained. Based on the risk level, a set of one or more attributes of a stagger configuration is determined. An attempt to deploy the current release to the plurality of container clusters in accordance with the stagger configuration is caused.
A method and apparatus for autonomous configuration-based release orchestration that supports staggered feature releases across a plurality of container clusters. A release seeking goal is obtained. An unprocessed stagger is selected as a current stagger based on a stagger order. The current stagger is processed by attempting to cause a deployment of the feature release to the container clusters in the current stagger, receiving an indication of success or failure of the attempted deployment, and determining whether to roll back the current stagger based on the indication. A determination is made whether the release seeking goal can still be met. If the release seeking goal can no longer be met, a release level rollback is caused, and otherwise the selecting, processing, and determining is repeated for the next unprocessed stagger based on the stagger order.
A computer-implemented method is disclosed for predicting a future usage of a cloud-based computing resource based on a previous usage of the resource by users, and predicting an anomaly event at the resource. The method also includes identifying a top contributing user responsible for the anomaly event, throttling an access of the top contributing user, evaluating a speed of data requests received from the top contributing user, and maintaining a utilization level of the resource within a predetermined target range. The method further includes dynamically controlling the speed of data requests based on the evaluation of the speed of data requests and a controlling speed of data request recommended by a first artificial intelligence model. The recommendations of the first artificial intelligence model may be validated by a human reasoning based model configured to monitor and mitigate a risk associated with a counter-intuitive recommendation of the first artificial intelligence model.
A computer system may determine to perform an upgrade operation to deploy a second database application that is a different version than a first database application associated with a first database catalog that stores catalog objects. The computer system performs the upgrade operation, including preparing a second database catalog and deploying the second database application to manage a database based on the second database catalog. To prepare the second database catalog, the computer system may create the second database catalog and store, in the second database catalog, system catalog objects that are associated with the second database application. The computer system may further identify, from the catalog objects stored in the first database catalog, user catalog objects that were created by users of the database and then copy the identified user catalog objects from the first database catalog to the second database catalog.
