https://github.com/http-apis/hydra-cloud-scale

hydus and hydra-agent as a cloud system
https://github.com/http-apis/hydra-cloud-scale

Last synced: 12 days ago
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hydus and hydra-agent as a cloud system

• Host: GitHub
• URL: https://github.com/http-apis/hydra-cloud-scale
• Owner: HTTP-APIs
• License: mit
• Created: 2019-11-19T14:33:00.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-09-30T16:03:35.000Z (about 4 years ago)
• Last Synced: 2024-10-29T12:34:05.442Z (about 2 months ago)
• Homepage:
• Size: 3.91 KB
• Stars: 0
• Watchers: 5
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# hydra-cloud-scale

## Blueprint

As APIs developers may want to deploy a Hydra-based servers/agents system on the cloud, it is provided here a tool to easily structure the content of Hydra specification documentation (`ApiDoc`) as a distributed cluster using a Docker stack.

Briefly, it should be possible to create a cluster from any compliant `ApiDoc` and deploy a docker container for each `HydraClass` in the document, so to create a "microservices-like" environment on which to plug a compliant agent (like `hydra-python-agent`). The agent would act as the tool to query the relationships among classes at scale. One agent, many hydrus servers that represent the data model; to query this distributed model, every agent connected stores the graph and runs query on its graph store.

Practically:

* the `ApiDoc` is destructured into its `HydraClass`es and for each of them a hydrus instance is spawned

* every authorised agent (`hydra-python-agent`) can connect to the cluster, build its own data graph and run queries and receive data updates.

## Local test implementation

Proposed implementation is to use Apache OpenWhisk. OpenWhisk is a portable serverless framework that works on top of popular technologies like Docker (i.e. Docker-On-Docker) and Kubernetes.

### Prerequisites

* install Docker and latest stable version of GoLang

* install [kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-kubectl-binary-with-curl-on-linux)

* install `kind` (GoLang library, only used for local development) following [these instructions](https://kind.sigs.k8s.io/docs/user/quick-start/#installation)

* install [OpenWhisk wsk CLI](https://github.com/apache/openwhisk-cli#compile-the-binary-using-your-local-go-environment)

* install [OpenWhisk wskdeploy](https://openwhisk.apache.org/documentation.html#wskdeploy)

### Create a local environment

* Follow [this instructions](https://github.com/apache/openwhisk-deploy-kube/blob/master/docs/k8s-kind.md#deploying-openwhisk-on-kind) to create a local cluster

* Deploy [local cluster with Helm](https://github.com/apache/openwhisk-deploy-kube#deploy-with-helm). Need to clone `openwhisk-deploy-kube` repository locally

* try: `wsk -i property get`