Develop a framework for running end-to-end and scenario acceptance test suites

The ginkgo based integration tests do a decent job of testing the internal mechanics of the operator. But they do NOT provide 100% coverage of the overall system as a "working unit."

Formalize a plan for running automated, full-stack coverage of Fabric networks constructed with the operator. Operator provides several routes for realizing a Fabric network, and each should be tested independently as a recurring validation of system behavior.

The "acceptance" tests _can_ be run continuously, but the expectation is that they _MUST_ be run at release intervals.

Whatever "platform" is used, it should complete the end-to-end-to-end scenario validation in a 100% predictable and automated fashion. Like: everything, even to the point of dynamically provisioning an ephemeral EKS, IKS, KIND, OCP, etc. cluster as a base kubernetes, if that is possible.

We have had early, very positive results integrating cloud-native workflow engines, such as Argo and Tekton, into the context of an automated provisioning workflows. One route to achieve an acceptance test bed would involve:

General idea:

1. Provision a Kube (or reference one if available)
2. kubectl apply an Nginx ingress controller
3. kubectl apply argo / tkn

Submit a `Workflow` (or tkn `Pipeline`) to run natively in the cluster as a sequence of orchestrated containers:
1. "Install Fabric" to a namespace (See #27) via k8s apply URL
2. apply peers, orderers, CAs, etc. via CRD (or Ansible -> console SDKs)
4. Issue peer, osnadmin, etc. CLI routines (or Ansible -> console SDKs) to create channels
5. Compile chaincode images, prepare packages, and install/commit
6. Execute E2E test / consuming application scenarios.

Finally: tear down the k8s cluster at the completion of the suite.

Workflows and Pipelines should be relatively modular, if possible, such that they can be assembled in the future as building blocks for additional test and automation scenarios.

Start by reviewing issue #27 and the proposed Workflow or Tekton Pipeline sequence. Trace the required stages from cluster provisioning and Fabric installation through CRD setup, CLI routines, chaincode deployment, end-to-end scenarios, and teardown. Done means a predictable, automated, modular acceptance-test framework that can run at release intervals.

Written by the indexing model from the issue text.