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some fixes in documentation #765

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merged 1 commit into from
Jan 16, 2019
Merged

some fixes in documentation #765

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2 changes: 1 addition & 1 deletion doc/index.rst
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Expand Up @@ -11,7 +11,7 @@ Getting started

The primary goal of BinderHub is creating custom computing environments that
can be used by many remote users. BinderHub enables an end user to easily
specify a desired computing environment from a GitHub repo. BinderHub then
specify a desired computing environment from a Git repo. BinderHub then
serves the custom computing environment at a URL which users can access
remotely.

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4 changes: 2 additions & 2 deletions doc/overview.rst
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Expand Up @@ -17,9 +17,9 @@ and registry of Docker images. It utilizes the following tools:
- **Kubernetes** to manage resources on the cloud
- **Helm** to configure and control Kubernetes
- **Docker** to use containers that standardize computing environments
- A **BinderHub UI** that users can access to specify GitHub repos they want
- A **BinderHub UI** that users can access to specify Git repos they want
built
- **BinderHub** to generate Docker images using the URL of a GitHub repository
- **BinderHub** to generate Docker images using the URL of a Git repository
- A **Docker registry** (such as gcr.io) that hosts container images
- **JupyterHub** to deploy temporary containers for users

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2 changes: 1 addition & 1 deletion doc/turn-off.rst
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Expand Up @@ -10,7 +10,7 @@ Contracting the size of your cluster
------------------------------------

If you would like to shrink the size of your cluster, refer to the
`Expanding and contracting the size of your cluster <https://zero-to-jupyterhub.readthedocs.io/en/latest/extending-jupyterhub.html#expanding-and-contracting-the-size-of-your-cluster>`_
`Expanding and contracting the size of your cluster <https://zero-to-jupyterhub.readthedocs.io/en/latest/user-resources.html#expanding-and-contracting-the-size-of-your-cluster>`_
section of the `Zero to JupyterHub`_ documentation. Resizing the cluster to
zero nodes could be used if you wish to temporarily reduce the cluster (and
save costs) without deleting the cluster.
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