Testing Environment

Selecting the Right Testing Environment

Support Engineers need testing environments to learn how to support GitLab and also to replicate customer issues.

This page explains the main choices available to you. Some guidelines:

1. You should choose a way to spin up a specific version of GitLab quickly so that you can replicate customer issues. The current recommended way to do this is to use GitLab Sandbox Cloud. Each specific module that you’ll be using has its own README.md in the deployment projects, so make sure to give that a read as well.
2. Testing locally is also recommended - configuring Docker Engine / VM based system (details below) to your taste will let you quickly spin up a specific GitLab version.
3. You will need licenses for all self-managed tiers so you can match the features available with your customer’s features - see the next section.
4. For most testing, a single box Omnibus installation will be fine.
5. If you need a more complex environment, the following tools can help:
   • GitLab Environment Toolkit
   • GitLab Support Setups via local (Virtualbox, VMWare, libvirt) VMs
6. For K8s Helm installations, we recommend using GKE.
7. If you need to replicate specific cloud provider environments (e.g. for a scaled architecture), see the sections on GCP, AWS and Azure below.
8. Consider joining the #spt_testing Slack Channel to share your own tips and tricks for testing environments.

Have fun!

Testing Environment License

If you require a license for testing:

• For a self-managed instance, use the Support Super Form.
• For GitLab.com, individual test namespaces with licenses pre-applied have been provisioned as part of your onboarding.

Please keep in mind you can’t generate licenses for customers, only for your own testing purposes.

AWS Marketplace Resources

Note that when using some AWS Marketplace resources, free trials (including GitLab Ultimate) may automatically renew. You should always prefer using test licenses, but ensure that you cancel any AWS Marketplace subscriptions if you trial anything for testing purposes.

Cloud Testing Environments

You can create (ephemeral) testing environments. We recommend using the support-resources project for doing so.

You’re free to create any testing environments that you need in order to perform your role, however be advised that:

• Cloud resources are not free: please delete or shutdown any instances you aren’t using.
• Multi-node reference architectures are very expensive to run, so be particularly mindful of not leaving them active longer than you need to.
• You shouldn’t expose your instances to the public Internet or run without TLS. Instances vulnerable to known RCEs or other exploits detected through automated scans will be shut down without warning. Please review Securing Cloud Testing Environments before you create your first instance.

GCP

GCP resources can belong to different GCP projects. There is a number of GCP projects available to you to create your resources in.

GitLab Sandbox Cloud for GCP (preferred)

If you need flexibility for creating test environments, the GitLab Sandbox Cloud allows for creating a personally-owned GCP projects. You can create test resources using the GCP console, or gcloud command line tool. If you need to replicate any of the Reference Architectures, it’s recommended that you use the GitLab Environment Toolkit.

Note: Please remember to shut down resources that you are no longer using. We are now using automation scripts to shutdown resources over the weekend. To exclude your resources from being shutdown you’ll need to add the instance-ttl-bot-ignore label to those resources.

Managing your GCP resources automatically

You can use Terraform Environments to automatically manage GCP resources in your personally-owned GCP projects. If you are after a simple Omnibus machine with a runner, select support-resources-template-v2-######## template. Feel free to also explore other available Project templates to deploy GitLab Environment Toolkit or create a GKE cluster that already has GitLab installed through Helm chart.

Note that these environments are ephemeral.

Check out a this demo video for details walk-through.

Other GCP Projects

You can use the support-resources project to manually create resources in a GCP testing environment alongside the resources created by our automation tools. As with the GitLab Sandbox Cloud for GCP - you can manage these manually created resources using the GCP console, or gcloud command line tool.

Warning: You may also have access to the gitlab-internal and gitlab-support GCP projects. It’s strongly recommended that you make use of the support-resources project or the GitLab Sandbox Cloud, instead of creating new resources in these projects.

We also have a support-openshift project created for the purpose of creating OpenShift clusters for testing the GitLab Operator and GitLab Runner Operator. Reach out to your Support Team colleagues in the #support-testing Slack Channel for more details on using this project for shared OpenShift testing.

Note: Please remember to shut down or delete any resources that you are no longer using.

GCP support-resources automation (deprecated)

You can also use the support-resources project to automatically spin up resources. They will appear in the support-resources GCP project, which all Support Engineers should have access to as part of their baseline entitlements. If you don’t have access to this project, please reach out in the #support_operations slack channel for assistance.

support-resources is considered deprecated and we’re actively tracking migration to Sandbox Cloud in STM-4037. Resources can still be created here, but if you’re looking to create something enduring Sandbox Cloud should be preferred.

Some advantages of using the support-resources automation project over Sandbox Cloud are:

1. Frugal times - this is a key feature that allows for resources to be turned off (and on) based on a customizable schedule (GCP only charges for uptime). If you’re using GET to spin up a 10k reference architecture (for example), the cost can be upwards of $250 USD/day. Frugal times lets you halve that by automatically turning it off when you’re not online.
2. Easy provisioning of streamlined complex topologies - with only a few clicks or a couple of commands, one can provision complex GitLab set-ups (GitLab installed on GKE, GitLab+Runner+Elasticsearch stack, etc) on any available version.
3. Easily troubleshooting customer tickets by replicating their set-up in minutes and easily reproducing their issues. The GitLab instance can be provisioned as already seeded with Groups, Projects, Issues, MRs, etc. Because they are easy to set-up and, hence disposable, the instances can be shared with customers so they can themselves reproduce or showcase an issue or experiment and collaborate.
4. Easy ramp-up and experimentation for various training modules - running before walking has never been easier. For example for someone taking the HA&Scale-out module, a good first step could be to create a 3K reference arch to poke around and see how everything is set-up, before actually creating their own HA set-up, or maybe just use the 3K as a reference.
5. Security - Support-resources allows the ports reviewed by our security team and if those were to change, we have a centralized way of imposing and rolling out that change across instances.
6. Terraform development - while continuously developing the project a few support engineers have become very familiar with terraform, ansible and general automation guidelines (could include here gcloud, bash and chef). This is becoming more and more important as we are seeing the adoption of GET.

There’s also a few disadvantages to using the project:

1. Less granularity - while you can identify all the resources a user is running, having one’s personal GCP project brings a lot more granularity to the data about each individual user.
2. Isolation - while the Support-Resources automation project is good at preventing resources conflicts, those can still happen as everybody has access to the pool of resources (so accidents can and have happened). In a personal GCP project one can, among other things, restrict access to their resources.
3. Familiarity with GCP - when using the Support-Resources project a lot of the intricacies of using GCP are performed beneath the covers. Having your own GCP projects will expose you to the complexity of setting things up manually or automating that yourself.
4. Sandbox Cloud is the emerging company standard. For more history and details on the sets of problems it solves, see the Sandbox Cloud Context and Problem Statement

GCP GKE Kubernetes Cluster

Please use your GitLab Sandbox Cloud GCP project to create a GCP Kubernetes (GKE) cluster. You can create a GKE cluster manually from the console or you can use the Support GKE cluster template (for an empty GKE cluster) or Support GitLab GKE cluster template (for a GKE cluster with a GitLab helm deployment) from your GitLab Sandbox account. Click here for more information on spinning up resources with terraform in the GitLab Sandbox.

Note: If you are using GKE to test GitLab Runners, note that GitLab Runners require the use of RBAC roles in GCP. The support-resources GCP project does not allow the user enough permission to create the required roles, but you can do it with your personal GitLab Sandbox Cloud GCP project

AWS Testing Environment

Please use Sandbox Cloud to create credentials for AWS.

EKS testing Environment with Helm

brew install certbot helm kubectl

2022-07-18 16:47:40 [ℹ]  node "ip-192-168-63-211.us-east-2.compute.internal" is ready
2022-07-18 16:47:41 [ℹ]  kubectl command should work with "/Users/cats/.kube/config", try 'kubectl get nodes'
2022-07-18 16:47:41 [✔]  EKS cluster "gitlab-cluster" in "us-east-2" region is ready

sudo certbot --server https://acme-v02.api.letsencrypt.org/directory --manual --preferred-challenges dns-01 certonly -d "*.<DOMAIN NAME>"

sudo kubectl create secret tls tls-star-<SECRET NAME> --cert=/etc/letsencrypt/live/<DOMAIN NAME>/fullchain.pem --key=/etc/letsencrypt/live/<DOMAIN NAME>/privkey.pem

sudo certbot --server https://acme-v02.api.letsencrypt.org/directory --manual --preferred-challenges dns-01 certonly -d "*.pages.<DOMAIN NAME>"

sudo kubectl create secret tls tls-star-pages-<SECRET NAME> --cert=/etc/letsencrypt/live/pages.<DOMAIN NAME>/fullchain.pem --key=/etc/letsencrypt/live/pages.<DOMAIN NAME>/privkey.pem

helm repo add gitlab https://charts.gitlab.io/

helm repo update

helm install gitlab gitlab/gitlab -f <values.yml>

kubectl get ingress/gitlab-webservice-default -ojsonpath='{.status.loadBalancer.ingress[0].hostname}'

kubectl get secret gitlab-gitlab-initial-root-password -ojsonpath='{.data.password}' | base64 --decode ; echo

Azure Testing Environment

For Group SAML/SCIM (GitLab.com) testing, shared account credentials can be located within the 1password entry Azure Active Directory Sandbox (SAML Testing). This level of access should be sufficient for the majority of test cases.

If you need access to the shared infrastructure team’s Azure account for testing AKS and similar features, please create an access request and tag your manager.

For features not available in either instance, please create your own trial for Azure.

Okta Testing Environment

If you need an Okta sandbox environment to test SAML and SCIM, please go to https://developer.okta.com/signup/ and enter your credentials for a free developer instance where you can perform all your tests. This is a full featured environment so you should be able to add and remove applications, and perform all tests as if you were in a regular production instance.

Google Workspace Testing Environment

The IT team has a Google Workspace test environment which the Support team can use. The credentials for 1 admin and 1 user account can be found in 1password as:

• Google Workspace Admin Test Account
• Google Workspace User Test Account

If you need to create more user test accounts, please delete them afterwards. There is a seat limit in the test environment.

When creating apps, please include your name or the ticket number in the app name. Note that all apps should be considered temporary and may be deleted 2 weeks after creation.

LDAP Testing Environments

For testing LDAP integrations with a self-managed GitLab instance, you may consider any of these options:

1. GDK.
2. Docker container.
3. Jumpcloud (Free for up to 10 users).

DNS for test instances

See the handbook for IT policies about Domain Names and DNS Records.

If you wish to test resources using a real domain name (instead of an IP address, e.g. for testing TLS certificates), you can purchase a domain name of your choice (without GitLab trademarks) that is paid for by GitLab through your Sandbox Cloud AWS account or GCP project. Instructions and guidelines can be found here.

Securing Cloud Testing Environments

Test instances are, by default, publicly accessible on the Internet. Often, we need to test specific versions or configurations that may be vulnerable to remote compromise. It is your responsibility to secure your test instances to prevent them from being compromised and used to further attack our cloud environment.

The GitLab Red Team regularly scans GitLab’s cloud environments for publicly accessible instances with known vulnerabilities. Instances vulnerable to known RCEs or other exploits detected through automated scans will be shut down without warning.

IP Filtering

A highly effective way to secure your cloud instances is to apply the concept of IP filtering for each test instance you create whether its a GitLab instance or otherwise. For the majority of cases, this means source IP filtering from one or more CIDR block ranges ensuring that only certain IPs and integrations can interact with the GitLab instance, therefore reducing the attack surface of the GitLab organization as a whole.

If you don’t know your current IP address to use for source IP filtering, you can utilize services like whatsmyipaddress.com or ipinfo.io to retrieve it. Though configuring IP filtering is currently a manual process for each cloud service, discussions are underway at the time of writing regarding how best to automate this practice to reduce complexity and manual processes needed in some cases. The steps to implement IP filtering will differ per cloud environment. Below you can find a detailed guide maintained by the support engineering team.

• Support Engineering Step-by-Step Guide to Implementing IP Filtering

In addition, you can find official, platform-specific documentation of features involved in implementing IP filtering:

• Google Cloud
• Amazon Web Services (AWS)
• Azure

TLS

To be in line with GitLab’s encryption policy, TLS should also be implemented on public-facing testing resources.

For GitLab instances specifically, it’s recommended that LetsEncrypt is manually enabled for Omnibus installs. First, you’ll need a domain assigned to your external IP regardless of your cloud platform. Enabling LetsEncrypt for Omnibus installs is well documented at the link above.

Self-Signed Certificates

Implementing TLS on any test instance that includes a login page can be done with a self-signed certificate if desired. Self-signed certificates are free, suitable for testing environments, and encrypt ingress and egress traffic with the same ciphers as paid certificates. The down-side is that self-signed certificates are not trusted by any browser or operating system and will therefore warn users of the risks when accessing a site that utilizes a self-signed (untrusted) certificate. If external parties will be accessing your instance that should rely on your TLS implementation, it’s best to include a signed certificate from a legitimate certificate authority.

Self-signed certificates can be generated with a tool like mkcert. Once mkcert has been installed, you can this command to generate a certificate file and a key file for gitlab.example.com:

mkcert gitlab.example.om

The command’s output will tell you the filenames that are generated:

The certificate is at "./gitlab.example.com.pem" and the key at "./gitlab.example.com-key.pem" ✅

For instructions on using self-signed certificates on your test instances, please review the GitLab docs on Configure HTTPS manually and the documentation available from these cloud service providers:

• Google Cloud
• AWS
• Azure

Patching against known vulnerabilities

Running a Support test instance with a known vulnerability can be a security issue. When running a test instance, you should patch against known vulnerabilities if possible.

For example, GitLab versions from 11.9 to 13.10.2 are vulnerable to CVE-2021-22205.

If you’re running GitLab version 12.6 to 13.10.2, patch against this vulnerability by running the following commands for each instance:

sudo su
cd ~
curl -JLO https://gitlab.com/gitlab-org/build/CNG/-/raw/master/gitlab-ruby/patches/allow-only-tiff-jpeg-exif-strip.patch
cd /opt/gitlab/embedded/lib/exiftool-perl
patch -p2 < ~/allow-only-tiff-jpeg-exif-strip.patch

For GitLab versions 11.9.0 to 12.5.x, you can “patch” the vulnerability by replacing the exiftool binary with the following commands:

sudo rm -f /opt/gitlab/embedded/bin/exiftool
sudo printf '#!/bin/bash \n\ncat -' > /opt/gitlab/embedded/bin/exiftool
sudo chmod a+x /opt/gitlab/embedded/bin/exiftool

Local Testing Environments

Docker

If you’d like to use Docker Desktop for Mac a subscription is required for business use. Please review the Docker Desktop handbook page to find more information on how to obtain a license as well as a list of recommended alternatives.

In the mean time, consider using a Cloud or local VM with Linux Engine for testing Docker environments.

Note that on Macs with M1 / Apple Silicon, running GitLab in Docker is not working properly for now. Check out UTM below as an alternative for a local setup on your M1 Mac.

Docker Machine

Since Docker Toolbox has been deprecated, Docker Machine has to be downloaded and installed manually. Use the following commands to install or upgrade Docker Machine separately:

$ curl -L https://github.com/docker/machine/releases/download/v0.16.2/docker-machine-`uname -s`-`uname -m` >/usr/local/bin/docker-machine && \
  chmod +x /usr/local/bin/docker-machine

VMWare

This guide involves configuring and setting up VMWare and Docker locally and assumes you’re using macOS.

Install VMWare (paid)

1. Navigate to VMWare store, and then purchase VMWare Fusion 10 (for macOS) (or current version).
2. Download VMWare Fusion 10 (for macOS) using the provided link.
3. Install VMWare Fusion 10.
4. Launch VMWare Fusion.
5. When prompted, enter the license details.

UTM (Apple M1 Compatible)

UTM is an open source QEMU-based virtualisation software for MacOS. It currently provides support for Apple silicon hardware, so may be useful for engineers on Apple M1 devices to deploy local virtual machines.

Install UTM

1. Navigate to the UTM home page and select ‘Download’.
2. Once installed, follow the instructions for an ARM-based installation of Ubuntu
3. Start the VM within the UTM interface.

VirtualBox (Incompatible with Apple M1)

This guide involves configuring and setting up VirtualBox and Docker locally and assumes you’re using macOS. VirtualBox does not currently support Apple M1 CPUs.

Install VirtualBox

Oracle VM VirtualBox is a free and open-source hosted hypervisor for x86 virtualization.

1. Navigate to VirtualBox.
2. Download the latest version of the software for your operating system.
3. Install VirtualBox.

Note The following list of commands can be saved as bash script for quickly spinning up new instances

Vagrant

Install Vagrant

From Introduction to Vagrant

Vagrant is a tool for building and managing virtual machine environments in a single workflow

Vagrant encapsulates the local VM apps VMWare and Virtual along with libvirt.

To install Vagrant, go to tutorials/vagrant/getting-started-install

Once installed, support/toolbox has two projects which you can explore for local GitLab and tools setup.

• GitLab Support Toolkit

Support toolkit to help manage GitLab inventory and additional services via docker containers.

• GitLab Support Setups

Provide a common provisioning and directory structure for various support setups including GitLab with connected GitLab Runners.

Multipass

Install multipass

Multipass is a tool to generate cloud-style Ubuntu VMs quickly on Linux, macOS, and Windows. This method is similar to Vagrant.

It can be installed using brew or the package installer.

NOTE: Some Mac users may experience a long standing bug where the MacOS firewall prevents Multipass from functioning consistently. Use macOS 13.3.1 or above to avoid this issue.

Once installed, use multipass help to get an idea of what it can do. The general format is multipass <command> <name>.

Examples

Omnibus

1. Make sure you download and install multipass.

2. Create a script called install-omnibus.sh inside of ~/mp_mount (or your preferred mount directory) with the following content:

   #!/bin/bash
   
   echo "Starting script..."
   sudo apt-get update
   sudo apt-get install -y curl openssh-server ca-certificates
   curl https://packages.gitlab.com/install/repositories/gitlab/gitlab-ee/script.deb.sh | sudo bash
   export GITLAB_ROOT_PASSWORD="your_root_password"
   export EXTERNAL_URL="$(hostname -I | awk '{print $1}')"
   echo $EXTERNAL_URL
   echo "Please enter the GitLab version (ex. 15.1.1):"
   read GL_VERSION
   apt install -y "gitlab-ee=$GL_VERSION-ee.0"
   

   Please note: You need to replace the above password entry “your_root_password” with an alphanumeric password which is not a series of words and phrases otherwise you will encounter the error message “Password must not contain commonly used combinations of words and letters”.

3. Run the following one-liner. If you’d like to increase/decrease memory or disk, replace with the appropriate values. You can use multipass help launch for more details on this command.

   multipass launch --cpus 4 --memory 8G --disk 10G --name gitlab-omnibus && multipass mount ~/mp_mount/ gitlab-omnibus:/mp_mount && multipass exec gitlab-omnibus -- sh -c 'sudo sh /mp_mount/install-omnibus.sh'
   

4. You’re finished! Use multipass shell gitlab-omnibus to access your instance. Additionally:

   • multipass list or multipass ls to see all instances
   • multipass stop gitlab-omnibus to stop the instance
   • multipass delete gitlab-omnibus to delete the instance
   • Change the default open shell menu item by using duti

GitLab Runner

1. Create an executable script called install-runner.sh inside of ~/mp_mount (or your preferred mount directory) with the following content:

   #!/bin/bash
   
   echo "Starting script..."
   sudo apt-get update
   sudo mkdir -p /etc/apt/keyrings
   curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
   echo \
     "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
     $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
   sudo apt-get update
   sudo apt-get install -y docker-ce docker-ce-cli containerd.io docker-compose-plugin
   curl -L "https://packages.gitlab.com/install/repositories/runner/gitlab-runner/script.deb.sh" | sudo bash
   apt-get install -y gitlab-runner
   

2. Create a new instance:

   multipass launch --cpus 2 --memory 4G --disk 5G --name gitlab-runner && multipass mount ~/mp_mount/ gitlab-runner:/mp_mount && multipass exec gitlab-runner -- sh -c 'sudo sh /mp_mount/install-runner.sh'
   

3. Use multipass shell gitlab-runner to access your instance.

Elasticsearch Instance

1. Create a script called install-es.sh inside of ~/mp_mount (or your preferred mount directory) with the following content:

   #!/bin/bash
   
   wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo gpg --dearmor -o /usr/share/keyrings/elasticsearch-keyring.gpg
   sudo apt-get install apt-transport-https
   echo "deb [signed-by=/usr/share/keyrings/elasticsearch-keyring.gpg] https://artifacts.elastic.co/packages/7.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-7.x.list
   sudo apt-get update && sudo apt-get install elasticsearch
   sudo /bin/systemctl daemon-reload
   sudo /bin/systemctl enable elasticsearch.service
   sudo systemctl start elasticsearch.service
   cat << EOF > /etc/elasticsearch/elasticsearch.yml
   path.data: /var/lib/elasticsearch
   path.logs: /var/log/elasticsearch
   network.host: $(hostname -I | awk '{print $1}')
   http.port: 9200
   discovery.seed_hosts: ["$(hostname -I | awk '{print $1}')", "elasticsearch"]
   EOF
   sudo systemctl restart elasticsearch.service
   

2. Create a new instance:

   multipass launch --cpus 2 --memory 8G --disk 5G --name gitlab-es && multipass mount ~/mp_mount/ gitlab-es:/mp_mount && multipass exec gitlab-es -- sh -c 'sudo sh /mp_mount/install-es.sh'
   

3. Use multipass shell gitlab-es to access your instance. You can use multipass ls to get the IP address and connect to it in your browser at port :9200 to verify it is working. Alternatively, run curl ip_address:9200 from your GitLab Omnibus instance to confirm you can reach your Elasticsearch instance.

Creating GitLab test instance

Creating settings variables

export SSH_PORT=2222
export HTTP_PORT=8888
export VERSION=11.9.9-ee.0
export ENV_NAME=gitlab-test-env
export CONTAINER_NAME=gitlab-test-11.9

Create new docker host

This command will create a new VirtualBox virtual machine called gitlab-test-env that will act as a docker host.

• CPUs: Same as host (-1)
• RAM: 4GB
• Name: gitlab-test-env
• Driver: virtualbox

docker-machine create \
--virtualbox-cpu-count -1 \
--virtualbox-memory 4096 \
--virtualbox-disk-size 30000 \
--driver virtualbox $ENV_NAME

• Resource: https://web.archive.org/web/20210619101324/https://docs.docker.com/machine/drivers/virtualbox/

Creating GitLab test instance with docker machine

Connect your shell to the new machine

In this example we’ll create a GitLab EE 11.9.9 instance.

First connect the docker client to the docker host you created previously.

eval "$(docker-machine env gitlab-test-env)"

You can add this to your ~/.bash_profile file to ensure the docker client uses the gitlab-test-env docker host. You can use echo to do so:

echo 'eval "$(docker-machine env gitlab-test-env)"' >> ~/.bash_profile

Get the available tags for GitLab

Optionally replace the ee in the URL with ce

wget -q https://registry.hub.docker.com/v1/repositories/gitlab/gitlab-ee/tags -O - | sed -e 's/[][]//g' -e 's/"//g' -e 's/ //g' | tr '}' '\n' | awk -F: '{print $3}'

Create new GitLab container

• HTTP port: 8888
• SSH port: 2222
  • Set gitlab_shell_ssh_port using --env GITLAB_OMNIBUS_CONFIG
• Hostname: IP of docker host
• Container name: gitlab-test-11.9
• GitLab version: EE 11.9.9-ee.0

Create container

export IP=$(docker-machine ip $ENV_NAME)

docker run --detach \
--env GITLAB_OMNIBUS_CONFIG="external_url 'https://$IP:$HTTP_PORT'; gitlab_rails['gitlab_shell_ssh_port'] = $SSH_PORT;" \
--hostname $IP \
-p $HTTP_PORT:$HTTP_PORT -p $SSH_PORT:22 \
--name $CONTAINER_NAME \
gitlab/gitlab-ee:$VERSION

Connect to the GitLab container

Retrieve the docker host IP

echo $IP
# example output: 192.168.151.134

• Browse to: https://192.168.151.134:8888/

Note: The container might take a few seconds to spin up and become accessible via the browser.

Execute interactive shell/edit configuration

docker exec -it $CONTAINER_NAME /bin/bash

# example commands
root@192:/# vi /etc/gitlab/gitlab.rb
root@192:/# gitlab-ctl reconfigure

How to update gitlab.rb values with sed

For example, to set the gitlab_shell_ssh port on a container named gitlab-ee to port 2222

docker exec -it gitlab-ee \
sed -i "s/.*gitlab_shell_ssh_port.*/gitlab_rails['gitlab_shell_ssh_port'] = 2222/g" /etc/gitlab/gitlab.rb

docker exec -it gitlab-ee gitlab-ctl reconfigure

Resources

• https://docs.gitlab.com/ee/install/docker.html
• https://web.archive.org/web/20210619101324/https://docs.docker.com/machine/get-started/
• https://web.archive.org/web/20210619101324/https://docs.docker.com/machine/reference/ip/

Windows

It may come to pass that you require a Windows environment to test a Windows Runner or even the Kubernetes Executor in a Mixed Cluster.

The options are the same as above:

• Cloud environments: GCP and AWS have Windows Server images you can spin up to connect to via RDP.
• A local environment: Microsoft provides pre-packeged Windows VMs for your hypervisor of choice.

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