Oracle International Corporation

Microsoft Technology Licensing, LLC

Boris Markus Scholl

Claudio Caldato

Mark Eugene Russinovich

Haishi Bai

Yaron Schneider

Sung Hon Wu

Brahmnes Fung

Alan Turnquist

Nizar Nassar Ali Qamar

A method of distributing microservice containers for a service across a plurality of computing environments may include receiving a service that is built from a plurality of containerized microservices to be deployed in a container platform. The container platform may include a plurality of computing environments. The method may also include receiving a deployment criteria for deploying the service in the container platform; accessing characteristics of the plurality of computing environments; and deploying the plurality of containerized micro services across the plurality of computing environments based on the deployment criteria and the characteristics of the plurality of computing environments.

Optimizing redeployment of functions and services across multiple container platforms and installations

The present disclosure relates to systems, methods, and computer-readable media for deploying cloud-native services across a plurality of cloud-computing platforms. For example, systems disclosed herein identify resource identifiers associated with cloud-computing services (e.g., types of services) to be deployed on one or more resources capable of executing or otherwise providing cloud-native services. The systems disclosed herein further generate resource bindings including deployment specifications that include data for deploying cloud-native services on corresponding platform resources (e.g., cloud resources, edge resources). Using the resource bindings, the systems disclosed herein can deploy cloud-native services across multiple platforms via control planes configured to manage operation of resources on the different platforms.

Deploying cloud-native services across control planes

A method of providing Application Programming Interface (API) functions for registered service endpoints in container environments may include receiving, at an API registry, a request from a second service to use a first service in a container environment, where the API registry may list one or more API functions that call the first service. The method may also include generating, by the API registry, a client library for the second service that includes the one or more API functions to execute calls from the second service to the first service in the container environment.

API registry in a container platform for automatically generating client code libraries

A method of customizing deployment and operation of services in container environments may include receiving, at an API registry, a property for a service that is or will be encapsulated in a container that is or will be deployed in a container environment. The method may also include determining whether the property for the service affects the deployment of the service to the container environment, and in response to a determination that the property affects the deployment of the service, deploying the service based at least in part on the property. The method may additionally include determining whether the property for the service affects the generation of a client library that calls the service in the container environment, and in response to a determination that the property affects the generation of the client library, generating the client library based at least in part on the property.

API registry in a container platform providing property-based API functionality

The present disclosure relates to systems, methods, and computer-readable media for generating a platform-neutral application model that provides a complete and accurate representation of functionality and topology for a cloud-native application. For example, systems disclosed herein analyze application data to identify platform neutral application features including resources, mesh connections, and quality of service (QoS) constraints associated with implementing a cloud-native application via a cloud computing system. The systems disclosed herein further construct a platform-neutral application model including identifiers of the application features. The platform-neutral application model facilitates convenient translation of applications between different platforms and further streamlines development and deployment of cloud-native applications across any number of platforms.

Generating and implementing a platform-neutral cloud-native application model

A method of providing Application Programming Interface (API) functions for registered service endpoints in container environments includes receiving, at an API registry, a request from a second service to use a first service in a container environment; providing an API function to the second service, where the API function is included as part of the second service to execute calls from the second service to the first service in the container environment; receiving a request from the API function for an endpoint of the first service; and providing the endpoint of the first service such that the API function in the second service can execute a call to the endpoint of the first service in the container environment.

A method may include receiving a request for a service at a container environment. The container environment may include a service mesh and a plurality of services encapsulated in a plurality of containers. The service may be encapsulated in first one or more containers. The method may also include determining that the request should be routed to a debug instance of the service; and instantiating the debug instance of the service. The debug instance may be encapsulated in second one or more containers and may include code implementing the service and one or more debugging utilities. The method may additionally include routing, by the service mesh, the request to the debug instance.

Real-time debugging instances in a deployed container platform

A method may include deploying a plurality of container pods to a plurality of container nodes in a container environment. Each of the plurality of container pods may include one or more services. Each of the plurality of container nodes may include one or more container pods. The plurality of container pods may be deployed to the plurality of container nodes based on initial characterizations of usage factors for each of the plurality of container pods. The method may also include monitoring actual usage factors for each of the plurality of container pods after deployment to the plurality of container nodes; identifying one or more container pods in the plurality of container pods that deviate from their initial characterizations of usage factors; and redistributing the one or more container pods throughout the plurality of container nodes based on the actual usage factors.

Dynamic node rebalancing between container platforms

A method of providing Application Programming Interface (API) functions for registered service endpoints in container environments may include receiving, at an API registry, an API definition that may include an endpoint of a first service that is encapsulated in a container that is deployed in a container environment and one or more API functions. The method may also include creating, by the API registry, a binding between the one or more API functions and the endpoint of the service; receiving, by the API registry, a request from a second service to use the first service; and providing, by the API registry, the one or more API functions to the second service.

Debugging capabilities for software running in a cloud-computing environment are disclosed. Embodiments enable developers to debug any process running on a virtual machine hosted in a remote data center, virtual network, or cloud services environment over the Internet through a secured connection without manually installing and configuring a remote debugging monitor. A debugger module is dynamically installed and configured on a remote machine over the Internet through an extension model. In another embodiment, a debugger module is dynamically installed and configured on a remote machine over the Internet through a remote scripting approach. A secure connection is automatically established between debugger application components and debugging components on the remote machine.

Growing community of inventors

Kirkland, WA, United States of America

Boris Markus Scholl