Abstract: Techniques are described for automating the creating, provisioning, and deployment of resources and infrastructure for building a data center that is configured to provide a set of services. Techniques are described for scheduling and executing multiple releases for a service. For a service for which a first release has been previously scheduled and executed, a second release may be scheduled for the service in response to an optional capability dependency for the service being published in a data center. The second release for the flock is then executed. As a result of the execution of the second release, additional enhanced capabilities may be added to the service.

Abstract: Techniques for utilizing multiple network interfaces for a cloud shell are provided. The techniques include receiving, by a computer system, a command to execute an operation by the computer system, the command being received from a router via a primary virtual network interface card (vNIC), the primary vNIC being configured to permit incoming traffic. The computer system may execute the operation, generating an output of the operation. The techniques also include transmitting, by the computer system, a message comprising the output of the operation to a shell subnet via a secondary vNIC, the secondary vNIC being configured to permit outgoing traffic from the computer system to the shell subnet.

Abstract: A system may include a computer processor and a repository configured to store a first code fragment including language features represented in a first programming language, and a second code fragment including language features represented in a second programming language. The system may further include a universal code fragment classifier, executing on the computer processor and configured to generate a first universal abstract syntax tree for the first code fragment and a second universal abstract syntax tree for the second code fragment, generate, using a graph embedding model, first vectors for the first universal abstract syntax tree and second vectors for the second universal abstract syntax tree, and classify, by executing an abstract syntax tree classifier on the first vectors and the second vectors, the first code fragment as a first code category and the second code fragment as a second code category.

Abstract: Techniques for preventing concurrent execution of an infrastructure orchestration service are described. Worker nodes can receive instructions, or tasks, for deploying infrastructure resources and can provide heartbeat notifications to scheduler nodes, also considered a lease. A signing proxy can track the heartbeat notifications sent from the worker nodes to the scheduler node. The signing proxy can receive requests corresponding to a performance of the tasks assigned to the worker nodes. The signing proxy can determine whether the lease between each worker node and the scheduler is valid. If the lease is valid, the signing proxy may make a call to services on behalf of the worker node, and if the lease is not valid, the signing proxy may not make a call to services on behalf of the worker node. Instead, the signing proxy may cut off all outgoing network traffic, blocking access of the worker node to services.

Abstract: The present embodiments relate to using feature engineering to generate time-varying features via metadata. A first exemplary embodiment provides a method for performing feature engineering to generate time-varying features. The method can include receiving a first value and a second value of the time-series data. The method can further include receiving metadata that describes a relationship between the first value and the second value. The method can further include detecting the relationship between the first value and the second value based on the metadata. The method can further include generating, a time-varying feature from a combination of the first value and the second value based on the relationship detected from the metadata. The method can further include generating, by implementing the machine learning forecasting model, a forecasted value for the time-series data based on the time-varying feature.

Abstract: Techniques for controlling packet flows through the generation of packet flow rules are described. In an example, a network virtualization device receives network data. The network virtualization device determines a set of networks of a virtual network based on the network data. The network virtualization device receives flow data of the customer. The network virtualization device generates a packet flow rule based on the flow data and the set of networks. The packet flow rule defines a network boundary of one or more networks such that a first packet having a destination within the network boundary can flow and such that a second packet having a destination outside of the network boundary is to be dropped. The network virtualization device stores the packet flow rule in association with the compute instance.

Abstract: The present embodiments relate to providing near real-time communications from a public network to a private network. A first computing device in a public network can obtain data packets to be provided to the private network from an application executing on the first computing device. A trust module executed by the first computing device can authenticate the user, application, and the data packets to be provided to the private network and add metadata relating to the sending user, recipient user, etc. The data packets can be forwarded to the private network via a cross-domain system (CDS). The metadata and the digital signature on the data packets can be verified by a trust module executing on a second computing device in the private network. The second computing device can receive the data packets and store the data packets for subsequent actions to be performed in the private network.

Abstract: A method for generating a query filter list includes obtaining set of training queries, each training query comprising a predicate and one or more accessed columns returned from evaluating the predicate, and transforming the set of training queries into a structure. The structure relates, for an accessed column and a training query, the predicate and a correlation value to the accessed column. The method further includes normalizing the structure into a normalized structure. The normalized structure grouping entries in the structure according to accessed column. The method further includes generating a generalized query from the normalized structure, and adding the generalized query to the query filter list.

Abstract: The present embodiments relate to an event attribution for estimating a downstream impact for a computing device of a cloud computing system. The computing device can transmit a data schema to a first client application executing on a first web server, the data schema describing a plurality of event data instance characteristics. The computing device can receive a first event data instance and a second event data instance from the first client application. The computing device can format the first event data instance and the second event data instance to conform to a uniform format as described by the data schema. The computing device can link the first event data instance and the second event data instance based at least in part on an event data instance characteristic. The computing device can calculate an attribution score between the first event data instance and the second event data instance.

Abstract: Disclosed systems relate to automatically instrumenting a web application for tracing. In an example, a method includes providing a web page application to a web browser on a client device. The web page application includes a tracer application. The method further includes detecting a start of the web page application and instantiating tracer application. The tracer application is configured to log tracing data for the web page application. The method further includes detecting an event initiated by interaction with the web page application. The method further includes automatically logging a start of a span based on the detection, the logging associating the span with the tracer application. The method further includes executing operations corresponding to the event. The method further includes automatically logging an end of the span based upon a completion of the operations corresponding to the event.

Abstract: The present disclosure relates to systems and methods for a machine learning platform that generates a library of components to generate machine learning models and machine learning applications. The machine learning infrastructure system allows a user (i.e., a data scientist) to generate machine learning applications without having detailed knowledge of the cloud-based network infrastructure or knowledge of how to generate code for building the model. The machine learning platform can analyze the identified data and the user provided desired prediction and performance characteristics to select one or more library components and associated API to generate a machine learning application. The machine learning can monitor and evaluate the outputs of the machine learning model to allow for feedbacks and adjustments to the model. The machine learning application can be trained, tested, and compiled for export as stand-alone executable code.

Abstract: Systems and methods described herein relate to runtime completion of web component metadata. Execution of a loader script of a web component may call a registration application programming interface (API) and provide component-specific metadata of the web component to the registration API. Execution of the registration API may provide a rendering engine with completed metadata of the web component, combining the component-specific metadata of the web component with a web component signature (e.g., a standard metadata signature that indicates a plurality of properties of the web component) to produce the completed metadata of the web component. The execution of the registration API may also store an entry in a component registry of the rendering engine that associates a name of the web component with the completed metadata of the web component.

Abstract: Techniques are described for extracting tables and associated content from image-based documents and generating a machine-readable representation of a table. A system is described that executes an end-to-end pipeline for extracting one or more tables from an image-based documents and generating a machine-readable and editable table representation based upon the extracted contents. The processing may include using OCR techniques to extract text portions from an image-based document, identifying a region (table region) in the image-based document containing a table, identifying a subset of text portions that are located inside the table region, determining a number of rows and columns in the table to be generated, aligning the text portions and assigning row and column indices to the text portions, and generating a machine-readable table representation based upon the text portions.

Abstract: Techniques for managing requests to modify a data set at future times are disclosed. The system receives a request to modify the data set at a future time, such as in a future time window. The system generates a representation of the data set at the future time. The system determines the future state of the data set based on the current state of the data set and requested future modifications to the data set. The system determines whether a conflict exists between the request to modify the data set at the future time and another scheduled request to modify the data set at the future time. Based on determining whether a conflict exists, the system performs one or more of scheduling the request to modify the data set at the future time and performing a remediation action to address the conflict.

Abstract: A computing device may receive a plurality of scanning requests with at least one scanning request in the plurality identifying a target address of a target network. The computing device may for at least a subset of the plurality of scanning requests: generate a scanner instance and a virtual network interface card (VNIC) in response to the scanning request. The scanner instance and the VNIC communicating with a routing namespace that can communicate with two or more scanner instances simultaneously. Until the target address has been scanned: one or more packets can be sent from the scanner instance to the target address via the routing namespace and VNIC. The one or more packets can be wrapped in one or more packet wrappers identifying the target address and the target network. In response to the target address being scanned, the scanner instance and VNIC can be decommissioned.

Abstract: The present disclosure relates generally to techniques for analyzing and improving a bot system, and more particularly to an analytic system integrated with a bot system for monitoring, analyzing, visualizing, diagnosing, and improving the performance of the bot system. For example, an analytic system is integrated with a bot system for monitoring, analyzing, visualizing, and improving the performance of the bot system. The analytic system monitors events occurred in conversations between end users and the bot system, aggregates and analyzes the collected events, and provides information regarding the conversations graphically on a graphic user interface as insights reports at different generalization levels. The insights reports offer developer-oriented analytics to pinpoint issues with skills so a user can address them before they cause problems.

Abstract: Techniques for controlling packet flows are described. In an example, a packet is sent on a virtual network. The packet’s header includes scoping data that indicates a network boundary within which the packet is permitted and/or prohibited to flow. A network virtualization device of a substrate network receives the packet. The network virtualization device determines the scoping data from the header and, based on network configuration information, determines the forward flow of the packet. If the forward flow falls within a permitted network boundary indicated by the scoping data, the network virtualization device sends the packet forward. Otherwise, the packet is dropped.

Abstract: Techniques are described for identifying resources within a region of a cloud computing environment that may be leveraged during a region build. A Multi-Flock Orchestrator (MFO) may be configured to obtain configuration files corresponding to services to be bootstrapped within the region during a region build process. MFO may determine an order by which the services are to be bootstrapped and transmits a first request in accordance with the order. Planning data may be received (e.g., indicating an intent to create a new resource). MFO may obtain (e.g., via a Resource Identification Service) an identifier corresponding to a previously created resource. MFO can modify the planning data with the identifier and transmits a second request comprising the modified planning data. Transmitting the second request can cause resource corresponding to the flock configuration file to be bootstrapped within the region using the resource corresponding to the identifier.

Abstract: Techniques are disclosed for migrating services from a virtual bootstrap environment. A distributed computing system can generate a virtual cloud network in a data center of a host region. A virtual bootstrap environment may be implemented in the virtual cloud network. The virtual bootstrap environment can include a plurality of services. The distributed computing system can also deploy an instance of one of the plurality of services to a target region data center. When the instance has been deployed, an indication that the deployment was successful can be received by the distributed computing system. In response, the distributed computing system may identify additional resources associated with the deployed instance of the service and update another service in the virtual bootstrap environment with that resource.

Abstract: Techniques are described for performing an automated region build using a version set that identifies versions of configuration files and/or artifacts with which the region build is to be performed. A Multi-Flock Orchestrator (MFO) may be configured to maintain multiple version sets identifying a respective set of configuration files associated with various services to be bootstrapped. The MFO may execute a validation process using one version set. A second version set may be identified from the first based on identifying configuration files that successfully passed the validation process. The automated region build can be performed using the second version set.

Abstract: Techniques are described for performing an automated region build. An orchestration service (e.g., a Multi-Flock Orchestrator (MFO)) may be configured to bootstrap any suitable number of services within a region corresponding to one or more data centers. Each service can be associated with a respective set of resources (e.g., infrastructure components to be provisioned, software artifacts to be deployed, etc.). The WO can obtain configuration files corresponding to the services to be bootstrapped and perform a static analysis the configuration files to identify one or more dependencies between the services. Circular dependencies can be identified and resolved before region build. A graph may be generated that maintains the dependencies identified and indicates a corresponding order with which bootstrapping tasks are to be performed. The WO may traverse the graph to incrementally instruct, according to the identified dependencies, a provisioning and deployment manager to bootstrap services in the region.

Abstract: The present embodiments relate to data center outage detection and alert generation. An outage detection service as described herein can process near real-time data from various sources in a datacenter and process the data using a model to determine one or more projected sources of a detected outage. The model as described herein can include one or more machine learning models incorporating a series of rules to process near-real time data and offline data and determine one or more projected sources of an outage. An alert message can be generated to provide the projected sources of the outage and other data relevant to the outage.

Abstract: A framework for establishing new regions and/or new realms. For example, techniques for establishing new regions and/or new realms by generating seed data by a seed maker and provisioning the seed data to resources for the new regions and/or new realms.

Abstract: Techniques are described for monitoring the health of services in a computing environment such as a data center. More particularly, the present disclosure describes techniques for monitoring the health and availability of capabilities in a computing environment such as a data center by enabling alarms to be associated with the capabilities. A capability refers to a set of resources in a data center. By providing the ability to associate an alarm with a capability, the health or availability of the associated capability can be monitored or ascertained by tracking the state of the alarm associated with the capability. For example, if the alarm associated with a particular capability is triggered, it may indicate that the particular capability and the one or more resources corresponding to the particular capability are not in a healthy state. Accordingly, by monitoring alarms associated with capabilities, the health of the associated capabilities can be ascertained.

Abstract: Techniques for extracting data from conversations across different types of communication channels are disclosed. A system applies a set of rules to extract data from conversations based, at least in part, on a type of communication channel used for conducting the conversation. The system applies a machine learning model to recognize semantic content in conversations. The system divides conversations into conversation segments and classifies the conversation segments based on the semantic content. The system selects conversation segments to be extracted based on the semantic content and the type of communication channel over which a conversation is conducted. The system maps conversation segments from different conversations conducted on different types of communication channels to a same set of transactions.

Abstract: Techniques are described for identifying resources within a region of a cloud-computing environment. A Resource Identification Service (RIS) may be configured to obtain a flock configuration file comprising resource discovery data associated with a service. The resource discovery data may indicate a set of parameters with which a previously existing resource of the cloud-computing environment is to be identified. RIS may execute operations to identify the previously existing resource based at least in part on matching attributes associated with previously existing resource to the set of parameters of the resource discovery data. The RIS may identify, from the flock configuration file, a set of import operations to perform to obtain an identifier corresponding to the previously existing resource. The identifier may be provided to cause the previously existing resource to be utilized in a region build.

Abstract: Techniques are disclosed for establishing a distributed virtual private network within a virtual bootstrap environment. A distributed computing system can generate a virtual cloud network in a data center of a host region. The virtual cloud network can include a plurality of host instances, including an instance hosting a virtual private network router. A second instance can provide a secondary network address to the virtual private network router. A third instance can send a request addressed to the secondary network address. The virtual cloud network may route the request to the virtual private network router according to a default route of a routing table. The request may then be forwarded by the virtual private network router to the secondary address using a networking tunnel established between the first instance and the second instance.

Abstract: The present embodiments relate to determining a critical path that identifies an order for bootstrapping a subset of resources within a data center under build. A cloud infrastructure orchestration service (CIOS) can identify from configuration files associated with resources to be bootstrapped within the data set, a set of capabilities. The CIOS can identify a first set of capabilities on which publishing each respective capability depends. User input can be received identifying a selected flock. The CIOS can identify the unpublished capabilities on which capabilities corresponding to the selected flock depend. Those unpublished capabilities can be ranked and provided via a visualization to the user. The unpublished capabilities can be ranked according to identifying, for a respective unpublished capability, a set of capabilities that are capable of being published responsive to publishing the respective unpublished capability.

Abstract: Techniques are disclosed for establishing a virtual bootstrap environment. A distributed computing environment may generate a virtual cloud network within a host region corresponding to one or more data centers. The distributed computing system may then implement a virtual bootstrap environment within the virtual cloud network. A first service may be deployed to the virtual bootstrap environment. A network connection may be established between the host region and a target region. The first service in the virtual bootstrap environment can then deploy resources to the target region over the network connection.

Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.

Abstract: A distributed event processing system is disclosed that receives a batch of events via a continuous data stream and performs the serialization of data in the batch of events. In certain embodiments, the system identifies a first data type of a first attribute for each event in a batch of events and determines a first type of data compression to be performed on data values represented by the first attribute. The system determines a first type of data compression to be performed on data values represented by the first attribute based on the first data type of the first attribute. The system then generates a first set of serialized data values for the first attribute. The system processes the first set of serialized data values against a set of one or more continuous queries to generate a first set of output events.

Abstract: A test environment is provided for testing of a flock configuration. A configuration file of a service is parsed to identify one or more capabilities for executing a release of the configuration file of the service. The one or more capabilities correspond to operations performed with respect to one or more resource types. A capability-aware-proxy server included in the test environment is configured based on the one or more capabilities identified from the configuration file of the service. The release of the configuration file of the service is executed in the test environment in accordance with the configured capability aware-proxy server. The capability aware-proxy server generates a response message corresponding to an execution result of the release of the configuration file of the service.

Abstract: Techniques are described for exporting observability data related to execution of a service from a first cloud environment to a second cloud environment. The service is executed in the first cloud environment for a customer of a second cloud environment. Observability data associated with execution of the service is collected in the first cloud environment for the customer of the second cloud environment. The observability data comprises one or more metrics associated with the execution of the service. The observability data collected from the first cloud environment is communicated to the second cloud environment to enable a user associated with the customer of the second cloud environment to access the observability data via the second cloud environment.

Abstract: Techniques are described for performing an automated region build with real time region data. Region data including region identifiers and execution target identifiers for the region may be maintained. When a modification of the region data is detected (or new region data is detected), configuration files corresponding to bootstrapping resources (e.g., at the execution targets) within the region may be obtained. Operations are executed to cause the configuration files to be updated. This may include recompiling or otherwise injecting region data into the configuration files. A region build may be executed to bootstrap resources within the region using the updated configuration files.

Abstract: The present embodiments relate to identifying and tracking capabilities within a data center managed by a cloud infrastructure orchestration service (CIOS). The CIOS can generate visualization(s) for the capabilities of the CIOS. A first portion of a visualization can identify capabilities that depend on previously published capabilities A second portion of the visualization can provide capabilities with one or more unpublished capabilities. In some embodiments, the capabilities depicted as part of the visualization can be arranged by a ranking derived based at least in part on a number of other capabilities publishing of a given capability blocks and/or a number of capabilities on which publishing a given capability depends. The visualization can be used to allocate resources to efficiently publish capabilities and build new regions (e.g., new data centers) with the CIOS.

Abstract: Techniques are described for assessing container images for vulnerabilities without actually scanning the container images. A vulnerability assessment system (VAS) is described that is configured to perform vulnerabilities assessment for container images. The VAS is configured to perform the vulnerability assessment without scanning the container images. In certain embodiments, the VAS calculates a vulnerability score for the container image where the vulnerability score is indicative of a probability that the container image contains a vulnerability.

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: Embodiments implement non-intrusive load monitoring using a novel learning scheme. A trained machine learning model configured to disaggregate device energy usage from household energy usage can be stored, where the machine learning model is trained to predict energy usage for a target device from household energy usage. Household energy usage over a period of time can be received, where the household energy usage includes energy consumed by the target device and energy consumed by a plurality of other devices. Using the trained machine learning model, energy usage for the target device over the period of time can be predicted based on the received household energy usage.

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. The first cloud infrastructure receives a request from a user associated with an account in the second cloud infrastructure. The request corresponding to using a service provided by the first cloud infrastructure. A tenancy is created for the user in the first cloud infrastructure to enable the user to utilize the service, and a link-resource object is created that includes information linking the tenancy of the user in the first cloud infrastructure to the account of the user in the second cloud infrastructure, the link-resource object enabling the user to utilize the service provided by the first cloud infrastructure.

Abstract: Techniques are described for establishing a private network path from a first cloud environment to a second cloud environment. A tenancy associated with the first cloud environment is provided in the second cloud environment. The tenancy includes a set of one or more resources that enable communication between the first cloud environment and the second cloud environment. A request originating in the second cloud environment and associated with a service provided by the first cloud environment is caused to be received by a first resource from the set of one or more resources. Using at least one resource from the set of one or more resources, the request is transmitted from the second cloud environment to first cloud environment.

Abstract: Techniques are described for communications in an L2 virtual network. In an example, the L2 virtual network includes a plurality of L2 compute instances hosted on a set of host machines and a plurality of L2 virtual network interfaces and L2 virtual switches hosted on a set of network virtualization devices. An L2 virtual network interface emulates an L2 port of the L2 virtual network. IGMP configuration is distributed to the L2 virtual switches. A control plane of the L2 virtual network coordinates IGMP configuration across the L2 virtual switches.

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 one or more link-enabling virtual networks being deployed in the first cloud environment and the second cloud 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. The first cloud infrastructure receives a request from a user associated with an account in the second cloud infrastructure. The request corresponding to using a service provided by the first cloud infrastructure. A tenancy is created for the user in the first cloud infrastructure to enable the user to utilize the service, and a link-resource object is created that includes information linking the tenancy of the user in the first cloud infrastructure to the account of the user in the second cloud infrastructure, the link-resource object enabling the user to utilize the service provided by the first cloud infrastructure.

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. The first cloud infrastructure receives a request from a user associated with an account in the second cloud infrastructure. The request corresponding to using a service provided by the first cloud infrastructure. A tenancy is created for the user in the first cloud infrastructure to enable the user to utilize the service, and a link-resource object is created that includes information linking the tenancy of the user in the first cloud infrastructure to the account of the user in the second cloud infrastructure, the link-resource object enabling the user to utilize the service provided by the first cloud infrastructure.

Abstract: Techniques are described for providing, in a first cloud infrastructure (FCI), an adaptor associated with a service provided by the FCI. The adaptor enables the service to be requested by one or more users associated with one or more accounts in a second cloud infrastructure (SCI), where the SCI is different than the FCI. The adaptor receives a first request from a first user associated with a first account in the SCI to create a resource in the FCI. The adaptor executes a workflow to provision the resource using the service, where the workflow includes processing comprising retrieving a resource-principal that is associated with the resource and transmitting a second request to the service provided by the FCI. The second request includes the resource-principal and corresponds to creation of the resource.

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 one or more link-enabling virtual networks being deployed in the first cloud environment and the second cloud environment.

Abstract: A multi-cloud infrastructure included in a first cloud environment provided by a first cloud services provider generates a set of one or more graphical user interfaces for each of a plurality of external cloud environments that are provided by a plurality of external cloud services providers. The set of one or more graphical user interfaces for an external cloud environment of the plurality of external cloud environments is generated based upon a native graphical user interface provided by the external cloud environment. Responsive to a request received by the first cloud environment and from a first external cloud environment of the plurality of external cloud environments, providing as a response to the request, a first graphical user interface from the set of one or more graphical user interfaces generated for the first external cloud environment.

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 one or more link-enabling virtual networks being deployed in the first cloud environment and the second cloud environment.

Abstract: Techniques for managing the distribution of configuration information that supports the flow of packets in a cloud environment are described. In an example, a virtual network interface card (VNIC) hosted on a network virtualization device NVD receives a first packet from a compute instance associated with the VNIC. The VNIC determines that flow information to send the first packet on a virtual network is unavailable from a memory of the NVD. The VNIC sends, via the NVD, the first packet to a network interface service, where the network interface service maintains configuration information to send packets on the substrate network and is configured to send the first packet on the substrate network based on the configuration information. The NVD receives the flow information from the network interface service, where the flow information is a subset of the configuration information. The NVD stores the flow information in the memory.

Abstract: Implementations generally relate to importing data and presenting the data in a user interface (UI). In some implementations, a method includes capturing an image of an object using a camera, where the object includes text. The method further includes recognizing the text and recognizing data in a table. The method further includes generating a data structure that includes the text or the data in the table. The method further includes generating a graphical image that represents at least a portion of the text or the data in the table. The method further includes displaying the graphical image in a UI in a display screen of a client device.