/rancher-private-registry-workshop

Rancher and Private Registry Hands-on Workshop

MIT LicenseMIT

Rancher and Private Registry Hands-on Workshop

This repository content provide the lab exercise guide for a hands-on workshop to help audience to understand and explore the open source technologies like Rancher and OPA in managing and securing containers on cloud based repositories like Azure Container Registry and/or private repositories such as Harbor.

Pre-requisites

  1. This Lab will require only chrome browser with fast and reliable internet connection.

  2. Make sure you have access to following urls behind your corporate firewall/personal computers.

    Github (https://github.com/)

    Sslip (https://sslip.io, *.sslip.io)

  3. Watch presentation/demo on Cloud native trusted container registry for Kubernetes [TUT-1212]. You may asked to register if you're visting first time.

    https://reg.rainfocus.com/flow/suse/susecon22/SessionCatalog/page/SessionCatalog/session/16490787591920019KcD

  4. If you want to spin this lab with your own personal/corporate Microsoft Azure Cloud account, please follow below link:

    https://github.com/dsohk/workshops/tree/main/scenarios/azure/rancher-harbor-acr

  5. Optional - Access to SUSE Partner Portal (https://myaccount.suse.com/)

Open Source Technologies Used

Software Version Remarks
Rancher 2.6.6 Enterprise-grade Kubernetes Management Platform
RKE2 v1.23.6+rke2r1 Rancher Kubernetes Engine 2 - with Kubernetes version 1.23.6
OPA 100.1.0+up3.7.1 Open Policy Agent Gatekeeper: Policy and Governance for Kubernetes
Harbor v2.2.2-56d7937f Project Harbor is an an open source trusted cloud native registry project that stores, signs, and scans content.
Trivy v0.16.0 Aqua Trivy: Vulnerability and Misconfiguration Scanning

Before We Begin

Before we start the lab, please make sure you have been provided with the following lab access credentials from the instructor. Each participant should have their own unique environment and credentials.

Item Value
Rancher Server URL https://rancher.xx.xx.xx.xx.sslip.io
Rancher Server Username admin
Rancher Server Bootstrap Password system assigned strong password
Harbor URL https://harbor.yy.yy.yy.yy.sslip.io
Harbor Username admin
Harbor Password system assigned strong password
Azure Registry Server Name attendeexx.azurecr.io (for example, attendee99.azurecr.io)
Azure Registry User Name attendeexx (for example, attendee99)
Azure Registry Password (system assigned strong password)

Step 1 - Access Rancher and Harbor Portals

a) With a Google Chrome browser, access Rancher Server URL (https://rancher.xx.xx.xx.xx.sslip.io). If you are greeted by an invalid SSL certificate error message, please follow the Note*.

b) Enter the admin credentials to login i.e. Username: admin and Password: system assigned strong password.

c) When it's successful, you will be landing on the Rancher Home page.

d) Do the same for Harbor URL (https://harbor.yy.yy.yy.yy.sslip.io). You will then be led to Harbor login page. If you are greeted by an invalid SSL certificate error message, please follow the Note*.

e) Enter the admin credentials to login i.e. Username: admin and Password: system assigned strong password.

*Note:

If you are greeted by an invalid SSL certificate error message, you can click on the Advanced button

Rancher:

Screenshot-2022-07-24-at-12.40.10-PM

Harbor:

Screenshot-2022-07-24-at-1.19.59-PM

Click the Proceed to https://rancher.xx.xx.xx.xx.sslip.io and/or https://harbor.yy.yy.yy.yy.sslip.io hyperlink to continue.

Screenshot-2022-07-24-at-1.20.37-PM

Now the login page will be displayed and proceed to authenticate yourself by entering username and password.

Screenshot-2022-07-24-at-1.22.45-PM

If link isn't shown, click on the empty space on browser and type the word thisisunsafe without any spaces to bypass the warning message.

Screenshot-2022-07-24-at-12.40.53-PM

Now the login page will be displayed and proceed to authenticate yourself by entering username and password.

Screenshot-2022-07-24-at-12.42.17-PM

End of Step 1

Lab Exercises

This lab consists of 3 exercises and 1 bonus exersise which can be completed offline within the stuipulated timeline.

Bonus Lab Exercise (Independent - Self learning)

References