scaffolding and initial doc update

Author: day0hero

content/patterns/hypershift/_index.adoc

@@ -0,0 +1,103 @@
+---
+title: HyperShift
+date: 2023-11-15
+validated: true
+summary: This pattern is for deploying the Hosted Control Plane (HyperShift) service.
+products:
+- Red Hat OpenShift Container Platform
+- Multi-cluster-Engine
+- AWS Controller for Kubernetes (S3)
+industries:
+- infrastructure
+aliases: /hypershift/
+pattern_logo: medical-diagnosis.png
+links:
+  install: getting-started
+  arch: https://www.redhat.com/architect/portfolio/architecturedetail?ppid=6
+  help: https://groups.google.com/g/validatedpatterns
+  bugs: https://github.com/validatedpatterns/medical-diagnosis/issues
+ci: hypershift
+---
+
+:toc:
+:imagesdir: /images
+:_content-type: ASSEMBLY
+include::modules/comm-attributes.adoc[]
+
+//Module to be included
+//:_content-type: CONCEPT
+//:imagesdir: ../../images
+[id="about-med-diag-pattern"]
+= About the {med-pattern}
+
+Background::
+
+This pattern is designed and intended to assist with simplifying the deployment of a HyperShift Hosting cluster. When this pattern is deployed, users will be be able to create hostedclusters of their own.
+
+Workflow::
+
+* Install multicluster-engine operator
+* Create an instance of the multicluster-engine which enables the tech preview feature `hypershift`
+* Install the AWS Controller for Kubernetes (ACK) operator for S3
+* Create an S3 bucket to be used by HyperShift for OIDC
+* Create a buildconfig and imagestream that provide the HyperShift cli (`hypershift`) as an imagestream to be used in further automation if desired.
+
+This pipeline is showcased link:https://www.youtube.com/watch?v=zja83FVsm14[in this video].
+
+image::medical-edge/dashboard.png[link="/images/medical-edge/dashboard.png"]
+
+//[NOTE]
+//====
+//This pattern is still under development. If you have any questions or concerns contact mailto:jrickard@redhat.com[Jonny Rickard].
+//====
+
+[id="about-solution-med"]
+== About the solution elements
+
+The solution aids the understanding of the following:
+
+* How to use a GitOps approach to keep in control of configuration and operations.
+* How to deploy AI/ML technologies for medical diagnosis using GitOps.
+
+The {med-pattern} uses the following products and technologies:
+
+* {rh-ocp} for container orchestration
+* {rh-gitops}, a GitOps continuous delivery (CD) solution
+* {rh-amq-first}, an event streaming platform based on the Apache Kafka
+* {rh-serverless-first} for event-driven applications
+* {rh-ocp-data-first} for cloud native storage capabilities
+* {grafana-op} to manage and share Grafana dashboards, data sources, and so on
+* S3 storage
+
+[id="about-architecture-med"]
+== About the architecture
+
+[IMPORTANT]
+====
+Presently, the {med-pattern} does not have an edge component. Edge deployment capabilities are planned as part of the pattern architecture for a future release.
+====
+
+image::medical-edge/edge-medical-diagnosis-marketing-slide.png[link="/images/medical-edge/edge-medical-diagnosis-marketing-slide.png"]
+
+Components are running on OpenShift either at the data center, at the medical facility, or public cloud running OpenShift.
+
+[id="about-physical-schema-med"]
+=== About the physical schema
+
+The following diagram shows the components that are deployed with the various networks that connect them.
+
+image::medical-edge/physical-network.png[link="/images/medical-edge/physical-network.png"]
+
+The following diagram shows the components that are deployed with the the data flows and API calls between them.
+
+image::medical-edge/physical-dataflow.png[link="/images/medical-edge/physical-dataflow.png"]
+
+== Recorded demo
+
+link:/videos/xray-deployment.svg[image:/videos/xray-deployment.svg[Demo\]]
+
+[id="next-steps_med-diag-index"]
+== Next steps
+
+* Getting started link:getting-started[Deploy the Pattern]
+//We have relevant links on the patterns page