Abstract: Techniques for configuring a software system include generating a hierarchy of entities representing usage of the software system by a set of users, wherein the hierarchy includes a first set of nodes representing a set of tasks, a second set of nodes representing a set of components that implement the tasks, and a set of edges between the first set of nodes and the second set of nodes. The techniques also include updating the hierarchy based on a first set of configurations for the tasks, wherein the updated hierarchy indicates one or more tasks that have been enabled for the users. The techniques further include determining, based on the updated hierarchy, one or more components that implement the task(s). Finally, the techniques include generating, based on the hierarchy, one or more runbooks that execute the task(s) using the component(s).

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A current value for an aggregate power threshold of a plurality of hosts may be identified. During a first time period, an aggregate power consumption of the plurality of hosts may be managed using the current value for the aggregate power threshold. A triggering event indicating a modification to the aggregate power threshold is needed may be detected. A new value for the aggregate power threshold may be determined based on the triggering event. During a second time period, the aggregate power consumption of the plurality of hosts may be managed using the new value for the aggregate power threshold.

Abstract: The present disclosure provides dynamic routing for data flows to a customer network hosted in the cloud. A plurality of compute instances may share a common virtual IP address. Each of the plurality of compute instances may advertise information to a respective network virtualization device (NVD). The information may include the IP address, cost, and/or active/standby status of the compute instance. The NVD may then provide the information to the control plane of a virtual cloud network (VCN), which may aggregate the information from the plurality of compute instances and generate a forwarding table, which may be sent to the NVDs. These techniques may allow a customer to automatically remove a compute instance whose service host has failed. These techniques may also allow a customer to add compute instances and to route data flows according to an active-standby operation, an equal cost active-active operation, or an unequal cost active-active operation.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. Power consumption of power-drawing devices (e.g., hosts, servers, etc.) may be monitored with respect to a power threshold. When the current power consumption corresponding to those devices breaches the power threshold, or at any suitable time, the system may identify a set of reduction actions configured to reduce aggregate power consumption. The power threshold may be updated dynamically based on the operational status of related systems and environmental factors. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: The present disclosure is directed to devices and techniques for auto-qualifying images on new hardware or infrastructure configurations. The systems and methods include initiating an auto-qualification process for pre-testing one or more images registered within a bare metal system having one or more new infrastructure configurations, discovering all of the one or more images registered for use within the bare metal system, booting each of the one or more registered images into an isolated infrastructure having the one or more new infrastructure configurations, probing instances of each of the one or more registered images booted on the isolated infrastructure to determine stability of each of the one or more registered images on the one or more new infrastructure configurations, and marking each of the one or more registered images as stable or unstable.

Abstract: Described herein is a network fabric including a plurality of graphical processing unit (GPU) clusters. The plurality of GPU clusters includes at least a first GPU cluster operating at a first speed and a second GPU cluster operating at a second speed that is different than the first speed. The network fabric includes a plurality of blocks, wherein each block includes: (a) one or more racks that host a GPU cluster, and (b) a plurality of switches arranged in a hierarchical structure that communicatively couple the block to other blocks included in the network fabric. Responsive to receiving a request to execute a workload, allocating one or more GPUs from the plurality of GPU clusters to execute the workload.

Abstract: Techniques for generating smart contract transaction data from a program embedded in the smart contract are disclosed. A distributed ledger system stores a smart contract specifying conditions of a transaction. Based on a user input to initiate the transaction, the system executes the smart contract transaction on the distributed ledger. A node executing the smart contract transaction executes the transaction verification program embedded within the smart contract. The transaction verification program includes instructions for transmitting the parameters of the transaction to a third party.

Abstract: Techniques are disclosed herein for a direct launch for asynchronous actions. An example method can include receiving, by a device, a first workflow request, wherein the device comprises a first launcher in operable communication with a second launcher via a shared queue, and wherein a first duplicate of the first workflow request is stored in the shared queue is to be retrieved by the second launcher upon an elapsing of a threshold time interval. The device can transmit the workflow request to an application for executing the first workflow request, wherein the transmission is prior to the threshold time elapsing. The device can determine whether the application initiated a workflow to process the workflow request. The device can update the first duplicate of the first workflow request stored at the shared queue based at least in part on the determination and prior to the threshold time interval elapsing.

Abstract: A plurality of GPU clusters are communicatively coupled with one another via a plurality of network devices arranged in a hierarchical structure, wherein the GPU clusters includes at least a first GPU cluster operating at a first speed and a second GPU cluster operating at a second speed that is different than the first speed. A routing policy is configured for each network device, wherein the configuring includes establishing a mapping of each incoming port-link of the network device to a unique outgoing port-link of the network device. For a packet transmitted by a GPU of a host machine and received by a first network device, an incoming port-link of the first network device is determined on which the packet was received and based on the configuring, an outgoing port-link is identified that corresponds to the incoming port-link. The packet is forwarded on the outgoing port-link of the network device.

Abstract: A method includes accessing document including sentences, document being associated with configuration flag indicating whether ABSA, SLSA, or both are to be performed; inputting the document into language model that generates chunks of token embeddings for the document; and, based on the configuration flag, performing at least one from among the ABSA and the SLSA by inputting the chunks of token embeddings into a multi-task model. When performing the SLSA, a part of token embeddings in each of the chunks is masked, and the masked token embeddings do not belong to a particular sentence on which the SLSA is performed.

Abstract: In response to a request to replicate resources from a primary region data center to a secondary region data center, an executable configuration file that describes the resources and their configuration is created utilizing information about the resources at the primary region data center. A correspondence table is also updated to include entries for to such resources. Utilizing the correspondence table, the executable configuration file is transformed to create a transformed executable configuration file that references the resources utilizing generic resource identifiers instead of primary region identifiers used within the primary region data center. The transformed executable configuration file is then executed at the secondary region data center to create replicated resources at the secondary region data center.

Abstract: Techniques are described for creating a container environment that implements direct communications between pods. This includes the creation of a management component (such as a control plane) of the container environment, the creation of nodes within an implementation component (such as a data plane) of the container environment, and the attaching of virtualized network interface cards (VNICs) to each node. This also includes creating a custom resource for each node, where the custom resource stores internet protocol (IP) addresses assigned to the node and stored within the VNICs for the node. Pods implemented within these nodes obtain an IP address from the VNICs for their respective node and communicate with each other utilizing the IP addresses via virtual communication devices and the VNICs.

Abstract: Continual learning techniques are described for extending the capabilities of a base model, which is trained to predict a set of existing or base classes, to generate a target model that is capable of making predictions for both the existing or base classes and additionally for making predictions for new or custom classes. The techniques described herein enable the target model to be trained such that the model can make predictions involving both base classes and custom classes with high levels of accuracy.

Abstract: The present embodiments relate to identifying and mitigating memory bit flips in a cloud infrastructure service. The cloud infrastructure service can provide a monitoring system to monitor low level memory space to detect bit flips by the DRAM instances in the cloud infrastructure service. The bit flips detected in various DRAM computing instances can be processed to verify that the bit flips are sustained (e.g., and possibly relating to a Rowhammer attack) rather than transitory bit flips occurring in DRAM computing devices. Responsive to validating a set of bit flips at one or more computing instances, workloads associated with the affected computing instances can be migrated to other computing instances in the cloud infrastructure service.

Abstract: Disclosed herein are techniques for using a generative adversarial network (GAN) to train a semantic parser of a dialog system. A method described herein involves accessing seed data that includes seed tuples. Each seed tuple includes a respective seed utterance and a respective seed logical form corresponding to the respective seed utterance. The method further includes training a semantic parser and a discriminator in a GAN. The semantic parser learns to map utterances to logical forms based on output from the discriminator, and the discriminator learns to recognize authentic logical forms based on output from the semantic parser. The semantic parser may then be integrated into a dialog system.

Abstract: A computing system may access a source device configured to store device traffic in a source device queue. The computing system may launch, by one or more worker nodes of a control plane of the computing device, a destination device. The computing system may transmit a source device state to the destination device. The control plane worker nodes may configure the destination device from the source device state. The computing system may instruct the source device to pause storing the device traffic to the source device guest memory. The computing system may store dirty page information in the computing system memory. The computing system may transmit the dirty page information to the destination guest memory. The computing system may instruct the destination device to resume storing the device traffic to the destination guest memory.

Abstract: According to certain implementations, a certificate management service of a cloud service provider requests a certificate for a domain from a certificate authority utilizing an HTTP-based challenge. The certificate authority responds with a challenge string and a subdirectory within the domain. The challenge string and subdirectory within the domain are sent from the certificate management service to a proxy server of the cloud service provider that manages a flow of data to a host that hosts the domain. When the certificate authority sends a request to the sub directory within the domain, the request is intercepted at the proxy server. Instead of forwarding the request to the host that hosts the domain, the proxy server responds to the certificate authority with the challenge string. This verifies ownership of the domain, which is required to obtain the certificate for the domain.

Abstract: Techniques for perspective-preserving seamless application switching are disclosed. A system may display a first interface using a first application. The first interface includes interface elements representing a plurality of objects. The system may detect a zoom-in command, received by the first application, requesting a particular zoom level for a first interface element, corresponding to a first object in the first plurality of objects. The system may determine that the requested zoom level exceeds a threshold. Responsive to determining that the requested zoom level exceeds the threshold, the system may display, using a second application, a second interface corresponding to the first object. The second interface may include one or more of: (a) characteristics associated with the first object that were not displayed by the first application, or (b) user input elements for executing operations associated with the first object that were not displayed by the first application.

Abstract: The present disclosure is related to techniques for converting a natural language utterance to a logical form query and deriving a natural language interpretation of the logical form query. The techniques include accessing a Meaning Resource Language (MRL) query and converting the MRL query into a MRL structure including logical form statements. The converting includes extracting operations and associated attributes from the MRL query and generating the logical form statements from the operations and associated attributes. The techniques further include translating each of the logical form statements into a natural language expression based on a grammar data structure that includes a set of rules for translating logical form statements into corresponding natural language expressions, combining the natural language expressions into a single natural language expression, and providing the single natural language expression as an interpretation of the natural language utterance.

Abstract: Techniques are described for a hierarchical caching mechanism enabling efficient cross-region replications. In some embodiments, replication-related information (e.g., key-value pairs) is stored in a particular layout in a binary tree (B-tree) of a file system for replication processing. A hierarchy of caches storing a first type of information (e.g., crypto keys associated with iNodes) may be arranged to match the particular layout in the B-tree to enable efficient parallel processing of a second type of information (e.g., files, file data, or symbolic links), where the replication-related information in the B-tree is partitioned into multiple key ranges for parallel processing. In some embodiments, the caches in different hierarchies may be shared by different parallel-processing key ranges and replication jobs in a file system.

Abstract: A computer-implemented method includes: accessing a plurality of datasets, where each dataset of the plurality of datasets includes training examples; selecting datasets that include the training examples in a source language and a target language; and sampling, based on a sampling weight that is determined for each of the selected datasets, the training examples from the selected datasets to generate the training batches; training an ML model for performing at least a first task using the training examples of the training batches, by interleavingly inputting the training batches to the ML model; and outputting the trained ML model configured to perform the at least the first task on input utterances provided in at least one among the source language and the target language. The sampling weight is determined for each of the selected datasets based on one or more attributes common to the training examples of the selected dataset.

Abstract: Approaches of reassigning a home region from a first data center to a second data center as requested by a customer are described herein. The home region is able to implement write operations to a domain, whereas other data centers cannot implement write operations to the domain. The customer can request the home region being reassigned to another data center such that the customer can utilize the other data center to implement write operations to the domain.

Abstract: A computer-implemented method includes obtaining, from text corpus including article-summary pairs in a plurality of languages, a plurality of article-summary pairs in a target language among the plurality of languages, to form an article-summary pairs dataset in which each article corresponds to a summary; inputting articles from the article-summary pairs to a machine learning model; generating, by the machine learning model, embeddings for sentences of the articles; extracting, by the machine learning model, keywords from the articles with a probability that varies based on lengths of the sentences, respectively; outputting, by the machine learning model, the keywords; applying a maximal marginal relevance algorithm to the extracted keywords, to select relevant keywords; and generating a keyword-text pairs dataset that includes the relevant keywords and text from the articles, the text corresponding to the relevant keywords in each of keyword-text pairs of the keyword-text pairs dataset.

Abstract: Techniques for configuring an enriched data metrics pipeline (DMP) include: obtaining node configuration data associated with an unenriched DMP for nodes of a heterogeneous computing platform, including (a) a first kind of node including an application programming interface (API) for obtaining unenriched data associated with the first kind of node and (b) a second kind of node including an API for obtaining unenriched data associated with the second kind of node; the unenriched DMP being configured to provide node-level unenriched data to a service according to a first schedule; the service being configured to generate node-level data metrics based on the unenriched data; based on the node configuration data, configuring an enriched DMP to provide node-level enriched data to the service according to a second schedule that is less frequent than the first schedule; the service being configured to generate fleet-level data metrics based on the node-level enriched data.

Abstract: Techniques are described for implementing a container environment where each pod within the container environment is provided with a unique IP address and a virtual communication device such as an IPvlan device. Communications from source pods are directly routed to destination pods within the container environment by one or more virtualized network interface cards (VNICs) utilizing the unique IP addresses of the destination pods, without the need for bridging and encapsulation. This reduces a size of data being transmitted and also eliminates a compute cost necessary to perform encapsulation of data during transmission.

Abstract: Techniques for managing task assignments to workers in a work environment are disclosed. A system identifies one or more workers with qualifications that match recommended qualifications to perform a task in a work environment. The system applies a trained machine learning model to task performance data associated with the worker, such as a past history of tasks performed and statistics associated with the performance of the task. The machine learning model generates a prediction of downstream effects associated with assigning the task to the user. The downstream effects include delays and performance improvements on subsequent tasks performed by the worker, as well as effects on tasks performed by other workers, at work centers in the work environment.

Abstract: In one or more embodiments, a metadata-driven user interface is implemented for presenting a set of available services, provided by a plurality of vendors, to a particular service consumer. The system queries metadata associated with of a set of candidate vendors to identify services provided by the candidate vendors that are available to a service consumer. The system generates and customizes the meta-driven interface for the service consumer based on the services available. The system receives user input selecting at least one of the services provided by a vendor. The system then queries configuration information associated with the particular service. The configuration information includes, for example, a workflow associated with the service, and identification of the service consumer's information to be used in execution of the workflow associated with the service. The system obtains the service consumer's information and uses the service consumer's information to cause execution of the workflow.

Abstract: Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and/or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.

Abstract: Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and/or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.

Abstract: Techniques are described herein for analyzing and tuning database workloads to optimize application performance. In some embodiments, a workload analyzer identifies a captured workload that includes a set of database queries executed within a particular timeframe. The workload analyzer compares the workload within one or more other workloads executed within a previous timeframe to determine differences between the different workloads. For example, the workload analyzer may identify changes in the distributions of queries, including how many queries are unchanged, missing, and/or new. The workload analyzer may further detect changes in the performance of individual queries. The workload analyzer may determine the overall performance impact of such changes on the total workload. Based on the analysis, the workload analyzer may generate reports, alerts, tuning advice, and/or recommendations to boost performance.

Abstract: Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and/or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.

Abstract: A method includes preparing a base model using an input model pretrained on at least three languages different from each other and a base vocabulary including words corresponding to two languages among the at least three languages, where the preparing the base model includes constraining the input model to the words included in the base vocabulary; training the base model using a first enhanced training dataset generated from public data, to generate a text summarization model; training the base model using a second enhanced training dataset generated from the first enhanced training dataset, to generate a text generation model; and training the base model using a third enhanced training dataset that is generated using the second enhanced training dataset and the text summarization model, to generate a next sentence generation model.

Abstract: Techniques for managing anomalies in a software system include monitoring the software system for anomalies via a plurality of signals and determining that signal results associated with the signals indicate a presence of an anomaly in the software system. The techniques also include identifying a hierarchy of sensors associated with the anomaly, where the hierarchy includes a parent sensor and a set of child sensors that are direct or indirect descendants of the parent sensor. The techniques additionally include executing the parent and child sensors to analyze the software system for one or more causes of the anomaly, and determining the cause(s) of the anomaly based on sensor results generated by the parent and child sensors. Finally, the techniques include causing remediation of the cause(s) of the anomaly based on one or more child sensors associated with the cause(s) and one or more resolutions mapped to the child sensor(s).

Abstract: The present disclosure relates to a system and techniques for resolving dangling references resulting from a dependency relationship between computing resource objects uncovered during a harvesting process. In embodiments, a harvester application adds computing resource objects associated with a client to a resource collection as those computing resource objects are identified. Dependencies are identified as each computing resource object is added to the resource collection, which are resolved only if the computing resource objects associated with those dependencies have already been added to the resource collection. If the computing resource objects associated with the dependencies have not already been added to the resource collection, then the dependency is added to an observer pool. Observer modules are configured to check each computing resource object as it is processed during the harvest process in order to match those computing resource objects to unresolved dependencies.

Abstract: Techniques for lazy compaction are disclosed, including: selecting, by a garbage collector, multiple regions of a memory for inclusion in a relocation set; populating, by the garbage collector, a lazy free list (LFL) with the multiple regions selected for inclusion in the relocation set; subsequent to populating the LFL: determining, by an allocator, that an ordinary free list managed by the garbage collector is depleted; responsive to determining that the ordinary free list is depleted: selecting a region in the LFL; executing one or more load barriers associated respectively with one or more objects marked as live in the region, each respective load barrier being configured to relocate the associated object from the region if the associated object is still live; subsequent to executing the one or more load barriers: allocating the region.

Abstract: Method includes populating fake value for each of entities, to generate string of fake entity values that correspond to entities; inserting sentinel token between adjacent fake values included in the string to generate first input data; generating, by natural language generation model, natural language sentences based on first input data, natural language sentences including one or more fake values from the string; analyzing natural language sentences to determine whether any fake value from the string is missing; based on the fake value missing, summarizing, using text summarization model, natural language sentences to generate text summary; concatenating the text summary with the fake value, to generate second input data; and generating, by a next sentence generation model, additional natural language sentence using the second input data, the additional natural language sentence including the fake value.

Abstract: Described are improved systems, computer program products, and methods for a new local rolling online patching solution to a database server with minimized disruption to other instances during patching. For a one-node database server, it achieves single rolling online patching by starting a new instance of the same database from the newly patched home before shutting down the collocated instance running out of the old home.

Abstract: The present embodiments relate to data processing model recommendation and review of a portion of data using a recommended model. A model catalog executing on a cloud infrastructure (CI) system can parse data from an obtained dataset identifying aspects of the dataset. The parsed data from the dataset can be compared with a plurality of potential models stored in a domain ontology store of the model catalog to identify one or more recommended models. Review output data can be generated using the dataset and any of the recommended models. The review output data resulting from the recommended model can be provided to the client for the client to either accept or reject the model.

Abstract: Described are improved systems, computer program products, and methods for obtaining space usage information within a clustered database system. Some approaches provide an improved algorithm and structure that gives the ability to compute the latest and accurate space usage with only in-memory operations.

Abstract: Techniques are disclosed herein for integrating document question answering in an artificial intelligence-based platform, such as a chatbot system. The techniques include receiving a query from a user, rewriting the query to include one or more specific descriptors, computing an embedding vector for the rewritten query, retrieving one or more textual passages from a document store utilizing the embedding vector for the rewritten query, determining one or more answers to the rewritten query within the one or more textual passages, and returning the one or more answers.

Abstract: Techniques for maintaining list-type text formatting when converting content from a source content format to a destination content format are disclosed. A system generates text content by applying text formatting tags to segments of characters obtained from a source electronic document. The system parses a static-display type source electronic document to obtain character data of the characters in the source document. The system analyzes the parsed data to identify text arranged in a list-type text format in the source document. The system generates text content in a destination content format different from the source format by applying tags to segments of the text content designating the segments items in a list.

Abstract: Techniques for managing digital messages to and from a proxy message address are disclosed. A system receives a message directed to a particular destination address. The system replaces any source address included in the message with a proxy address. When the system receives a reply to the message, the reply is directed to the proxy address. The system analyzes message data to identify a target address for the reply message. The system identifies contextual data associated with the reply message. The system transmits the reply message, and the contextual data, to the target address.

Abstract: Techniques are described for creating a network-link between a first virtual network in a first cloud environment and a second virtual network in a second cloud environment. The first virtual network in the first cloud environment is created to enable a user associated with a customer tenancy in the second cloud environment to access one or more services provided in the first cloud environment. The network-link is created based on network resources and one or more link-enabling virtual networks being deployed in the first cloud environment and the second cloud environment.

Abstract: An expense report generation system receives transaction authorization data from a card issuer and compares the data with expense report generation criteria to determine whether to generate an expense report, prior to settlement of the transaction, based on the authorization data. The expense report generation system evaluates additional data obtained from other data sources including contextual information of the employee, transaction authorization, location, and other employees to generate the expense report. The expense report generation system subsequently updates the generated expense report based on updated transaction authorization data and/or transaction settlement data. The expense report generation system trains and uses a machine learning model for efficiency and accuracy in generating expense reports from transaction authorization data while reducing an employee's burden in manually inputting expense information and the approval process burden.

Abstract: Techniques for implementing a qualification-based task management system in a work environment are disclosed. When a user logs in to a work center terminal, a system identifies a set of pending tasks that need to be completed. The system filters the tasks available to the user based on the user's qualifications and the equipment present at the work center. When the system identifies a task for which there is not a set of users with matching qualifications, the system applies a machine learning model to the task parameters to identify candidate users or recommended qualifications for performing the task.

Abstract: In one or more embodiments, a software service allows software providers to implement machine learning (ML) features into products offered by the software providers. Each ML feature may be referred to as an encapsulated ML application, which may be defined and maintained in a central repository, while also being provisioned for each user of the software provider on an as-needed basis. Advantageously, embodiments allow for a central definition for an ML application that encapsulates data science and processing capabilities and routines of the software provider. This central ML application delivers a ML deployment pipeline template that may be replicated multiple times as separate, tailored runtime pipeline instances on a per-user basis. Each runtime pipeline instance accounts for differences in the specific data of each user, resulting in user-specific ML models and predictions based on the same central ML application.

Abstract: The present disclosure relates to systems and methods for providing cloud-based services securely to on-premises networks or other infrastructure. More particularly, the present disclosure relates to systems and methods for enriching first-party data (e.g., data collected directly by an on-premises server) stored within on-premises networks by enabling the on-premises networks to retrieve and process third-party data stored on cloud-based networks. As a technical benefit, cloud-based services can be performed on the first-party data within the on-premises networks.

Abstract: Techniques for generating recommendations for re-ordering scheduled tasks to improve completion times of one or more tasks are disclosed. A system displays a representation of a schedule for performing tasks among work centers in a work environment. The system identifies performance metrics associated with a current configuration of tasks in the work environment. The system further analyzes performance metrics for alternative task schedules in the work environment. The system displays interface elements to allow a user to re-order tasks among the work centers in the work environment. The system also displays predicted performance metrics associated with the alternative task schedules. When a user selects a particular interface element to implement an alternative task schedule, the system generates instructions to work centers to reorder tasks in the work environment.

Abstract: Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and/or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.