Edge-Cloud Platform

The Edge-Cloud Platform is a set of services that allow for distributed and secure management of edge sites ("cloudlets"), featuring deployment of workloads, one-touch provisioning of new cloudlets, monitoring, metrics, alerts, events, and more.

Services

• The Controller provides the API endpoint for, and manages creating, updating, deleting, and showing application definitions, cloudlets, clusters, application instances, policies, etc. It manages object dependencies and validation, stores objects in Etcd, and distributes objects to other services that need to be notified of data changes.

• The Cloudlet Resource Manager (CRM) manages infrastructure on a cloudlet site, calling the underlying infrastruture APIs to instantiate virtual machines, docker containers, kubernetes clusters, or kubernetes applications, depending on what the actual infrastructure type supports.

• The Distrbuted Matching Engine (DME) provides the API endpoint for mobile device clients to find existing application instances, provide operator-specific services like location APIs, and pushes notifications to mobile devices via a persistent connection.

• The ClusterSvc service automatically deploys additional applications to clusters to enable monitoring, metrics, and storage.

• The EdgeTurn service is much like a TURN server, providing secure console and shell access to virtual machines and containers deployed on cloudlets.

Checking Out Code and Building

Please see Getting Started.

Running unit tests

make unit-test

Running e2e (end-to-end) tests

Make sure you have installed required third party services as noted in the getting started guide. This runs the above services, and any required third party services locally, and stimuates the platform via the public APIs to do end-to-end testing.

make test

or, to stop on error:

make test-debug

Running local KIND test

This is similar to the e2e test above, except instead of fake cloudlet platforms, it uses a KIND (Kubernetes IN Docker) cluster to simulate a cloudlet with a single Kubernetes cluster locally. There are two commands, one to start the local processes, and one to stop.

# start processes
make test-kind-start
# stop processes
make test-kind-stop