Revamped Reference section with proper landing page
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@@ -247,5 +247,5 @@ You can expose a Service in multiple ways that don't directly involve the Ingres
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* Use [Service.Type=LoadBalancer](https://github.com/kubernetes/kubernetes/blob/release-1.0/docs/user-guide/services.md#type-loadbalancer)
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* Use [Service.Type=NodePort](https://github.com/kubernetes/kubernetes/blob/release-1.0/docs/user-guide/services.md#type-nodeport)
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* Use a [Port Proxy] (https://github.com/kubernetes/contrib/tree/master/for-demos/proxy-to-service)
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* Use a [Port Proxy](https://github.com/kubernetes/contrib/tree/master/for-demos/proxy-to-service)
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* Deploy the [Service loadbalancer](https://github.com/kubernetes/contrib/tree/master/service-loadbalancer). This allows you to share a single IP among multiple Services and achieve more advanced loadbalancing through Service Annotations.
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@@ -40,7 +40,7 @@ The replication controller simply ensures that the desired number of pods matche
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The replication controller is forever constrained to this narrow responsibility. It itself will not perform readiness nor liveness probes. Rather than performing auto-scaling, it is intended to be controlled by an external auto-scaler (as discussed in [#492](http://issue.k8s.io/492)), which would change its `replicas` field. We will not add scheduling policies (e.g., [spreading](http://issue.k8s.io/367#issuecomment-48428019)) to the replication controller. Nor should it verify that the pods controlled match the currently specified template, as that would obstruct auto-sizing and other automated processes. Similarly, completion deadlines, ordering dependencies, configuration expansion, and other features belong elsewhere. We even plan to factor out the mechanism for bulk pod creation ([#170](http://issue.k8s.io/170)).
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The replication controller is intended to be a composable building-block primitive. We expect higher-level APIs and/or tools to be built on top of it and other complementary primitives for user convenience in the future. The "macro" operations currently supported by kubectl (run, stop, scale, rolling-update) are proof-of-concept examples of this. For instance, we could imagine something like [Spinnaker] (http://spinnaker.io/) managing replication controllers, auto-scalers, services, scheduling policies, canaries, etc.
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The replication controller is intended to be a composable building-block primitive. We expect higher-level APIs and/or tools to be built on top of it and other complementary primitives for user convenience in the future. The "macro" operations currently supported by kubectl (run, stop, scale, rolling-update) are proof-of-concept examples of this. For instance, we could imagine something like [Spinnaker](http://spinnaker.io/) managing replication controllers, auto-scalers, services, scheduling policies, canaries, etc.
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## Common usage patterns
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