Table Of Contents

Getting started

The dataverse project describes itself as:

Dataverse is an open source web application to share, preserve, cite, explore,

and analyze research data. It facilitates making data available to others, and

allows you to replicate others’ work more easily. Researchers, journals, data

authors, publishers, data distributors, and affiliated institutions all receive

academic credit and web visibility.

Introduction: what’s this all about?

This project aims at offering a new way to deploy, run and maintain a Dataverse installation for any purpose on any kind of Kubernetes-based cloud infrastructure.

You can use this on your laptop, in your on-prem datacentre or public cloud. With the power of Kubernetes, many scenarios are possible.

Tip

tl;dr…

Quick’n’dirty demo persona on naked cluster [1]:

kubectl apply -k github.com/IQSS/dataverse-kubernetes/personas/demo/common

Wait. Regularly check logs and pods. Login with dataverseAdmin:admin1.

[1]	Your mileage may vary due to storage classes. You really should look at the demos below.

Prerequisites: First things first.

Before you start deploying, make sure to look at the following checklist:

1. Think first

If you never touched a commandline, never thought about why using cloud infrastructure might be a good idea: maybe you should stick with the old, but paved and solid ways of installing complex applications like Dataverse.

Keen to learn new technology? Be part of the future? Want to streamline CI/CD and your application? Continue.

2. Install tools

You will at least need:

• kubectl, at least version 1.14
• git (or another VCS)

Depending on your use-case and targeted environment that might be just it. If something else is necessary, it’ll be documented in its respective documentation part.

3. Grasp some knowledge

If you never used Kubernetes, but want to deploy to production, you definitely should be reading some docs first. Some starting points:

• https://kubernetes.io/docs/tutorials/kubernetes-basics/
• https://ramitsurana.github.io/awesome-kubernetes
• https://kubernetes-on-aws.readthedocs.io/en/latest/admin-guide/kubernetes-in-production.html

4. Grab a cluster

You’ll need a running and fully configured Kubernetes cluster.

• Local options:
  • k3s
  • minikube
  • microk8s
  • kind
• Deploy your own (production) cluster. Many tools to choose from. Examples:
  • kops
  • kubespray
• Use a hosted solution. Some example services at
  • Google: GKE
  • Microsoft: Azure AKS
  • Amazon: AWS EKS
  • RedHat: OpenShift

5. Choose persistent identifiers

When you want to register datasets and/or files in your deployment to DataCite, EZID or similar, you will need active accounts. Be sure to have access credentials around. As an alternative, you might want to use the FAKE provider.

See also

For more information on Dataverses supported providers:

• Installation Guide: Persistent Identifiers and Publishing Datasets
• Installation Guide: Configuration Option :DoiProvider

Use Cases: What installation persona are you?

1. Demo time!

Demos provide showcases what Dataverse can do for you. Currently pre-packaged:

• Local
  • Using minikube, see Using minikube persona
  • Using k3s, see Using k3s.io persona
• Cloud-based
  • Using kops on Amazon EC2 VMs, see demo/aws-kops

2. Developing is my thing

There is an entire section in this guide dealing with how to use this project for developing Dataverse, run development snapshots for tech demos, etc.

Please go to development docs here.

3. Gimme the production stuff

Todo

This needs yet to be refactored.

You should make yourself familiar with a series of documentation articles, linked below:

• [Container images](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/images.md)
• [Persistance storage](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/storage.md)
• [Detailed insight into inner workings](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/how-it-works.md)
• [Using Kubernetes descriptors from this project](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/reuse.md)
• [Configuration of Dataverse](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/config.md)
• [Secrets usage](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/secrets.md)
• [(Custom) Metadata Blocks](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/metadata.md)
• [Maintenance Jobs and Little Helpers](https://github.com/IQSS/dataverse-kubernetes/blob/master/docs/little-helpers.md)

Please be aware that this project currently only offers images and support for basic usage. Integrations are not yet part of this, but may be added as needed. See also relevant docs within Dataverse guides and upstream projects.

4. Integrate yourself!

One of the true superpowers of Dataverse is its ability to integrate with external tools. Previewers, data analysis, data capturing and many more await you.

Hint

Currently, none of these are supported or maintained by this project, although this is a mid-term goal. If you feel a need, raise an issue. You are most welcome to contribute.

Table Of Contents

• Getting started
  • Introduction: what’s this all about?
  • Prerequisites: First things first.
  • Use Cases: What installation persona are you?
    • 1. Demo time!
    • 2. Developing is my thing
    • 3. Gimme the production stuff
    • 4. Integrate yourself!

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