Abstract: Techniques for presenting a graphical user interface (GUI) for configuring a cloud service workstation are disclosed. The system presents a GUI that presents a plurality of possible workstation configurations and the costs associated with each respective workstation configuration, prior to creation of a workstation. The GUI updates the cost associated with a workstation configuration responsive to receiving a selection to modify the workstation configuration from a user. The user may request a different configuration based on a single user input, without specifying which resources to modify. The GUI may recommend a workstation configuration based on one or more user inputs such as a budget, an application service domain, a duration, or a processing power requirement.

Abstract: Systems and techniques for budget-based management of a cloud infrastructure are disclosed. A system monitors a cloud infrastructure for one or more trigger-action conditions associated with the cloud infrastructure. When a trigger-action condition is detected, the system determines a cloud infrastructure modification action that corresponds to the detected trigger condition. The system may apply the cloud infrastructure modification action to the cloud infrastructure. A cloud infrastructure modification action may modify one or more the workstation resources such that a rate of budget consumption is changed, for example, by pausing a resource, deleting a resource, resuming a paused resource, or changing from one resource to a different resource.

Abstract: Novel techniques are disclosed for virtualizing a cloud infrastructure in a region provided by a cloud service provider (CSP) to allow a reseller of the CSP to provide reseller-offered cloud services using a securely isolated portion of the CSP-provided infrastructure in the region and have a direct business relationship with the reseller'customers. In certain embodiments, the CSP-provided infrastructure in a region is organized into one or more data centers. In certain embodiments, the securely isolation portion of the CSP-provided infrastructure comprises at least one compute resource or a memory resource.

Abstract: Techniques are disclosed herein for objective function optimization in target based hyperparameter tuning. In one aspect, a computer-implemented method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that comprises a domain score for each domain that is calculated based on a number of instances within an evaluation dataset that are correctly or incorrectly predicted by the machine learning algorithm during a given trial. For each trial of a hyperparameter tuning process: training the machine learning algorithm to generate a machine learning model, running the machine learning model in different domains using the set of hyperparameter values, evaluating the machine learning model for each domain, and once the machine learning model has reached convergence, outputting at least one machine learning model.

Abstract: Novel techniques for creating service endpoints associated with different virtual private label clouds (vPLCs) for accessing a cloud service are disclosed. In certain embodiments, an endpoint management service (EMS) uses a novel architecture that enables the concurrent use of multiple vPLC-specific service endpoints with one endpoint per cloud service per vPLC to access the same cloud service running on multiple vPLC-specific resources. In some embodiments, each vPLC-specific service endpoint may be associated with a fully qualified domain name (FQDN) and an IP address.

Abstract: Novel techniques are disclosed for enabling customizable consoles of different virtual private label clouds (vPLCs). In some embodiments, one console server may execute multiple consoles for multiple vPLCs and CSP. In other embodiments, one console server may be dedicated to a vPLC-specific console. In certain embodiments, console customization including a customized set of console user interfaces (UIs) may be performed for each vPLC-specific console.

Abstract: Systems and methods for route mismatch identification are disclosed herein. A method of route mismatch identification can create in cache an expected routing table based on expected routing information received by a routing agent of a host from a database accessible by each of the plurality of hosts. The method can include creating in cache an actual routing table based on actual routing information received by the routing agent of the host from an advertising agent of the host, comparing the actual routing table and the expected routing table, and taking an action based on the comparison of the actual routing table and the expected routing table.

Abstract: The disclosed systems, methods and computer readable media relate to managing Non-Volatile Memory Express (NVMe) over Transmission Control Protocol (TCP) (NVMeOTCP) connections between a smart network interface card (smartNIC) and a block storage data plane (BSDP) of a cloud computing environment. A software agent (“agent”) executing at the smartNIC may manage a number of network paths (active and, in some cases, passive network paths). The agent may monitor the network traffic (e.g., input/output operations (IOPS)) through the paths (e.g., using established NVMeOTCP connections corresponding to the paths). If a condition is met relating to a performance threshold associated with the monitored paths, the agent may increase or decrease the number established NVMeOTCP connections to match real time network conditions.

Abstract: Data can be received that includes information corresponding to a set of users. Privacy protection protocols that apply to the data can be identified. A subset of the data can be identified as being personally identifiable information (PII) data, where the subset includes a set of PII attributes. The PII attributes can be split into categories based on a format of a data field in the PII attributes. The processed PII data can be combined with non-PII data to create processed client data. It can be determined to add noise to part of the processed PII data. An amount of noise can be determined based on the privacy protection protocols. The amount of noise can be added to part of the processed PII data to produce protected data. A machine-learning model can be trained using the protected data.

Abstract: Novel techniques for resource usage monitoring, billing, and enforcement for virtual private label clouds (vPLCs) are disclosed. In some embodiments, resource usage for a vPLC associated with a reseller is monitored at both reseller level and customer-of-reseller level using resource IDs, and stored as usage information in two levels and associated with a tenancy ID for the reseller (at the reseller level) and tenancy IDs for customers of the reseller (at the customer-of-reseller level). In some embodiments, a two-level billing process generates invoices using two-level pricing information and the generated invoices to either resellers or customers of resellers directly. In some embodiments, usage enforcement can be performed per vPLC or per customer tenancy of a reseller's customer.

Abstract: Aspects of the present disclosure include implementing fabric availability and synchronization (FAS) agents within a fabric network. In one example, a first FAS agent executing on a first network device may receive, from a second network device, a command to modify a configuration of a second network device. The first FAS may upgrade the configuration of the first network device based on the command from a current configuration to a new configuration. The first FAS agent increment a state identifier associated with the configuration of the first network device to a new state identifier associated with the new configuration. The first FAS agent may then transmit a control packet that includes the new state identifier. A second FAS agent executing on the second network device may receive the control packet and execute the command to update the configuration of the second network device to the new configuration.

Abstract: Techniques for predicting marketing outcomes using contrastive learning are disclosed, including: obtaining historical marketing messages; obtaining historical open rates associated respectively with the historical marketing messages; based on the historical marketing messages, generating latent space representations associated respectively with the historical marketing messages; based on the latent space representations and respective contents of the historical marketing messages, training a first machine learning model to map contents of marketing messages to corresponding latent space representations of the marketing messages; based at least on the latent space representations and the historical open rates, training a second machine learning model to map latent space representations of marketing messages to predicted open rates of the marketing messages.

Abstract: Novel techniques are disclosed that enable the creation of a two-tier marketplace comprising a CSP marketplace and one or more marketplaces for virtual private label clouds (vPLCs). Each marketplace can be created and operated independently. In some embodiments, a publisher may publish a solution offering directly on a vPLC marketplace without involving the CSP marketplace. In other embodiments, a solution offering published on a marketplace may be automatically republished on another marketplace. Yet, in another embodiment, a customer subscribing to a vPLC marketplace can see a composite view of a directly published solution listing and a republished solution listing.

Abstract: Techniques are disclosed for tuning external invocations utilizing weight-based parameter resampling. In one example, a computer system determines a plurality of samples, each sample being associated with a parameter value of a plurality of potential parameter values of a particular parameter. The computer system assigns weights to each of the parameter values, and then selects a first sample for processing via a first external invocation based on a weight of the parameter value of the first sample. The computer system then determines feedback data associated with a level of performance of the first external invocation. The computer system adjusts the weights of the parameter values of the particular parameter based on the feedback data. The computer system then selects a second sample of the plurality of samples to be processed via execution of a second external invocation based on the adjustment of weights of the parameter values.

Abstract: A secure private network connectivity system (SNCS) within a cloud service provider infrastructure (CSPI) is described that provides secure private network connectivity between external resources residing in a customer's on-premise environment and the customer's resources residing in the cloud. The SNCS provides secure private bi-directional network connectivity between external resources residing in a customer's external site representation and resources and services residing in the customer's VCN in the cloud without a user (e.g., an administrator) of the enterprise having to explicitly configure the external resources, advertise routes or set up site-to-site network connectivity.

Abstract: Techniques are disclosed for deploying a computing resource (e.g., a service) in response to user input. A computer-implemented method can include operations of receiving (e.g., by a gateway computer of a cloud-computing environment) a request comprising an identifier for a computing component of the cloud-computing environment. The computing device receiving the request may determine whether the identifier exists in a routing table that is accessible to the computing device. If so, the request may be forwarded to the computing component. If not, the device may transmit an error code (e.g., to the user device that initiated the request) indicating the computing component is unavailable and a bootstrap request to a deployment orchestrator that is configured to deploy the requested computing component. Once deployed, the computing component may be added to a routing table such that subsequent requests can be properly routed to and processed by the computing component.

Abstract: Novel techniques are disclosed for providing vPLC-specific metadata service including customized vPLC-specific metadata. In certain embodiments, each vPLC may generate a customized metadata using its corresponding vPLC-specific customization instructions. In some embodiments, a vPLC-specific metadata service may be performed using pre-generated customized vPLC-specific metadata, on-the-fly customized metadata, pre-generated CSP-format metadata, or combinations thereof.

Abstract: Techniques for facilitating connectivity to vPLCs created in a CSP-provided infrastructure in a region. Within the CSP-provided infrastructure in a region, when the destination of a packet is determined to be an endpoint associated with a particular vPLC, the packet is tagged with information related to the particular vPLC. The vPLC-related information for the particular vPLC can include, for example, a vPLC identifier identifying the particular vPLC, an identifier identifying a customer associated with the endpoint, a virtual cloud network identifier identifying a virtual cloud network (VCN) belonging to the particular vPLC and where the endpoint is part of the VCN, and other vPLC-related information. The packet is then routed or communicated within the CSP-provided infrastructure in a region along with the tagged vPLC-related information. The vPLC-related information is used as part of the connectivity and for routing of packets within the CSP-provided infrastructure in a region.

Abstract: Techniques are described herein for applying access controls to logical secure elements (LSEs) running on the same secure element hardware platform. Embodiments include a firmware component that determines whether a message targeting an LSE is authorized to trigger an operation. For example, the firmware component may verify a signature of the received message using a public key, shared secret, or other access control key. Additionally or alternatively, access control policies may be defined to constrain the load of the LSEs on the SE platform hardware and/or to prioritize LSE access. For example, the access control policies may define usage thresholds, such as maximum threshold memory and/or processor utilization rates. As another example, the access controls may restrict the active time for an LSE to a threshold duration. If access constraints are violated or the message cannot be verified, then the firmware component may delay or deny the operation.

Abstract: Techniques for generating supplemental information based on runbook operation results are disclosed. A system generates and displays supplemental information for a runbook execution interface based on one of a system component associated with an executable operation of a runbook, and a set of runbook operation results corresponding to the executable operation. The system receives a user input to execute an operation defined by a runbook presented to remediate an event. The system generates supplemental information for the runbook execution interface based on the results of the operation executed by the user. The system identifies characteristics associated with the runbook operation results and identifies sources for additional information. Source may include performance data from the same component over a different period of time, performance data of a similar component, and performance data of topologically-connected components.