Avesha, Inc.

Sudhir Halbhavi

Raj Nair

Prabhudev Navali

Chin-Cheng Wu

Prasad Dorbala

Sai Koti Reddy Danda

Eric Peterson

A distributed computing system has one or more clusters each including compute nodes connected by a cluster network and executing microservices in respective containers organized into pods. The system includes application slice components (routers, slice gateways) distributed among the clusters to define and operate application slices each providing application slice services for respective sets of pods distributed among the clusters. Each slice gateway provides an interface between local pods of the application slice and remote pods of the application slice on a respective different cluster. Each slice is associated with namespaces, network policies and resource quotas for the applications onboarded on the slice. The slice routers and slice gateways for a given application slice form a respective slice-specific overlay network providing cross-cluster network services including service discovery and traffic forwarding with isolation from other application slices that co-reside on the clusters.

Distributed computing system employing application slice overlay networks

A networked system for real-time computer-aided augmentation of a live input video stream includes an endpoint system configured and operative to handle the live input video stream and a live augmented video stream and to provide service access to a video augmentation service for the computer-aided augmentation of the live input video stream. The system further includes a backend system providing service orchestration to orchestrate use and operation of the video augmentation service, and an edge inference system coupled to the endpoint system and to the backend system, the edge inference system being configured and co-operative with the endpoint system to provide the video augmentation service on the live input video stream and thereby generate the live augmented video stream, based on the service orchestration by the backend system.

Networked system for real-time computer-aided augmentation of live input video stream

A technique is directed toward controlling placement of workloads of an application within an application environment. The technique involves, while a first placement of workloads of the application is in a first deployment of resources within the application environment, generating a set of resource deployment changes that accommodates a predicted change in demand on the application. The technique further involves adjusting the first deployment of resources within the application environment to form a second deployment of resources within the application environment, the second deployment of resources being different from the first deployment of resources. The technique further involves providing a second placement of workloads of the application in the second deployment of resources to accommodate the predicted change in demand on the application, the second placement of workloads being different from the first placement of workloads.

Controlling placement of workloads of an application within an application environment

A technique performs load balancing self-adjustment within an application environment. The technique involves, while nodes of the application environment load balance traffic among clusters that provide services for an application in accordance with a first load balancing configuration, sensing application environment metrics. The technique further involves performing a self-adjustment operation that generates a second load balancing configuration based on the application environment metrics, the second load balancing configuration being different from the first load balancing configuration. The technique further involves deploying the second load balancing configuration among the nodes to enable the nodes to load balance the traffic among the clusters that provide the services for the application in accordance with second load balancing configuration in place of the first load balancing configuration.

Performing load balancing self adjustment within an application environment

Techniques manage cluster resources within an application environment. The techniques involve identifying a group of cluster resources from a plurality of cluster resources of the application environment, the plurality of cluster resources being constructed and arranged to provide a plurality of services. The techniques further involve forming an application slice having the group of cluster resources. The techniques further involve deploying the application slice to provide services. Certain techniques provide a platform that allows operators to build application slices (or application overlays) that are a way of grouping application pods (or containers) based on one or more organizing principles such as velocity of deployment, security, governance, etc.

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Bengaluru, India

Sudhir Halbhavi