Some embodiments provide a method of providing distributed storage services to a host computer from a network interface card (NIC) of the host computer. At the NIC, the method accesses a set of one or more external storages operating outside of the host computer through a shared port of the NIC that is not only used to access the set of external storages but also for forwarding packets not related to an external storage. In some embodiments, the method accesses the external storage set by using a network fabric storage driver that employs a network fabric storage protocol to access the external storage set. The method presents the external storage as a local storage of the host computer to a set of programs executing on the host computer. In some embodiments, the method presents the local storage by using a storage emulation layer on the NIC to create a local storage construct that presents the set of external storages as a local storage of the host computer.

Systems and methods for a virtual layer-2 network are described herein. The method can include providing a virtual Layer 3 network in a virtualized cloud environment. The virtual Layer 3 network can be hosted by an underlying physical network. The method can include providing a virtual Layer 2 network in the virtualized cloud environment. The virtual Layer 2 network can be hosted by the underlying physical network.

Some embodiments of the invention provide a method for deploying network elements for a set of machines in a set of one or more datacenters. The datacenter set is part of one availability zone in some embodiments. The method receives intent-based API (Application Programming Interface) requests, and parses these API requests to identify a set of network elements to connect and/or perform services for the set of machines. In some embodiments, the API is a hierarchical document that can specify multiple different compute and/or network elements at different levels of compute and/or network element hierarchy. The method performs automated processes to define a virtual private cloud (VPC) to connect the set of machines to a logical network that segregates the set of machines from other machines in the datacenter set. In some embodiments, the set of machines include virtual machines and containers, the VPC is defined with a supervisor cluster namespace, and the API requests are provided as YAML files.

Methods, systems, and computer-readable media for optimizing application configurations in a provider network are disclosed. An application description is determined that comprises one or more resource utilization characteristics of an application. Automated analysis is performed of a plurality of potential configurations for the application based at least in part on the application description. The automated analysis comprises scoring at least a portion of the potential configurations based at least in part on a scoring function. A recommended configuration for the application is determined based at least in part on the automated analysis. The recommended configuration comprises a type and number of computing resources in a multi-tenant provider network.

This disclosure relates generally to selection of cloud service providers in a multi-cloud. The selection of cloud service providers (CSPs) in a multi-cloud environment is challenging as it depends on multiple criteria such as security, usability, latency, and service cost. In an embodiment, for each CSP and multi-CSP combination, two decision problems are solved; namely, a VM selection problem and a cloud region selection problem, taking latency requirement and DR laws constraints into consideration. By solving the VM selection and CC selection problems, the service cost and the user to cloud region mapping are estimated. Using said estimates and other qualitative criteria, a multi-cloud multi-criteria decision problem is solved using MCDM techniques to rank the CSP combinations for each application. Based on the ranks and a constraint on a service cost of the entity one of a CSP and a CSP combination is selected for each application.

A processing system may obtain a request to deploy a service comprising a first virtual network function (VNF) to a multi-cloud environment comprising cloud infrastructures, the request including metadata associated with the service, decompose the service into a plurality of modules comprising: a plurality of VNFs and/or a plurality of components of the first VNF, select at least a first deployment model for the service from among a plurality of deployment models, based upon the metadata, each deployment model comprising rules for assigning the plurality of modules to cloud infrastructures, and deploy a first module to a first cloud infrastructure and a second module to a second cloud infrastructure.

Systems, methods, and non-transitory computer-readable media can receive gameplay information associated with a first user playing a game on a computing device. Game-related content is generated based on the gameplay information. The game-related content is published to an ephemeral content feed on a social networking system.

A system may receive a first definition for a virtualized instance of a network function. The first definition may include a first set of declarations in a first format that is different than respective formats supported by different virtualized environments. The system may select a first virtualized environment to run the virtualized instance based on requirements specified within the first definition, and may generate a second definition with a second set of declarations that map the first set of declarations from the first format to a second format supported by the first virtualized environment. The system may deploy the virtualized instance to the first virtualized environment using the second set of declarations from the second definition. Deploying the virtualized instance may include configuring its operation based on some of the second set of declarations matching a configuration format supported by the first virtualized environment.

Systems and methods for initiating communication between users of a user group based on machine learning techniques. The disclosed systems and methods provide a novel framework for automating communication scheduling and communication initiation based on user communication objectives and machine learning techniques. The disclosed framework operates by leveraging available user provided communication parameters, user provided objectives, and various real-time data associated with the users, and using the aforementioned data as inputs for machine learning models, in order to schedule communication between the users, automatically initiate communication between the users, or transmit communication notifications to the users.

The invention relates to a technique of co-operation between a plurality of client entities communicating among themselves by way of at least one instantaneous-communication channel established between the client entities and said plurality. A first client entity of said plurality dispatches an executable application to at least one second client entity of said plurality by way of said at least one instantaneous-communication channel. This application is then executed by the first client entity in co-operation with an execution of said application on the second client entity.