debian-mirror-gitlab/doc/topics/autodevops/requirements.md

---
stage: Configure
group: Configure
info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments
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# Requirements for Auto DevOps **(FREE)**

Before enabling [Auto DevOps](index.md), we recommend you to prepare it for
deployment. If you don't, you can use it to build and test your apps, and
then configure the deployment later.

To prepare the deployment:

1. Define the [deployment strategy](#auto-devops-deployment-strategy).
1. Prepare the [base domain](#auto-devops-base-domain).
1. Define where you want to deploy it to:

   1. [Kubernetes](#auto-devops-requirements-for-kubernetes).
   1. [Amazon Elastic Container Service (ECS)](#auto-devops-requirements-for-amazon-ecs).
   1. [Amazon EC2](#auto-devops-requirements-for-amazon-ec2).
   1. [Bare metal](#auto-devops-requirements-for-bare-metal).

When done:

1. [Enable Auto DevOps](index.md#enable-or-disable-auto-devops).
1. See the [quick start](quick_start_guide.md) process.

## Auto DevOps deployment strategy

> - [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/38542) in GitLab 11.0.

When using Auto DevOps to deploy your applications, choose the
[continuous deployment strategy](../../ci/introduction/index.md)
that works best for your needs:

| Deployment strategy | Setup | Methodology |
|--|--|--|
| **Continuous deployment to production** | Enables [Auto Deploy](stages.md#auto-deploy) with the default branch continuously deployed to production. | Continuous deployment to production.|
| **Continuous deployment to production using timed incremental rollout** | Sets the [`INCREMENTAL_ROLLOUT_MODE`](customize.md#timed-incremental-rollout-to-production) variable to `timed`. | Continuously deploy to production with a 5 minutes delay between rollouts. |
| **Automatic deployment to staging, manual deployment to production** | Sets [`STAGING_ENABLED`](customize.md#deploy-policy-for-staging-and-production-environments) to `1` and [`INCREMENTAL_ROLLOUT_MODE`](customize.md#incremental-rollout-to-production) to `manual`. | The default branch is continuously deployed to staging and continuously delivered to production. |

You can choose the deployment method when enabling Auto DevOps or later:

1. In GitLab, on the top bar, select **Menu > Projects** and find your project.
1. On the left sidebar, select **Settings > CI/CD**.
1. Expand **Auto DevOps**.
1. Choose the deployment strategy.
1. Select **Save changes**.

NOTE:
Use the [blue-green deployment](../../ci/environments/incremental_rollouts.md#blue-green-deployment) technique
to minimize downtime and risk.

## Auto DevOps base domain

The Auto DevOps base domain is required to use
[Auto Review Apps](stages.md#auto-review-apps), [Auto Deploy](stages.md#auto-deploy), and
[Auto Monitoring](stages.md#auto-monitoring).

To define the base domain, either:

- In the project, group, or instance level: go to your cluster settings and add it there.
- In the project or group level: add it as an environment variable: `KUBE_INGRESS_BASE_DOMAIN`.
- In the instance level: go to **Menu > Admin > Settings > CI/CD > Continuous Integration and Delivery** and add it there.

The base domain variable `KUBE_INGRESS_BASE_DOMAIN` follows the same order of precedence
as other environment [variables](../../ci/variables/index.md#cicd-variable-precedence).

If you don't specify the base domain in your projects and groups, Auto DevOps uses the instance-wide **Auto DevOps domain**.

Auto DevOps requires a wildcard DNS A record matching the base domain(s). For
a base domain of `example.com`, you'd need a DNS entry like:

```plaintext
*.example.com   3600     A     1.2.3.4
```

In this case, the deployed applications are served from `example.com`, and `1.2.3.4`
is the IP address of your load balancer, generally NGINX ([see requirements](requirements.md)).
Setting up the DNS record is beyond the scope of this document; check with your
DNS provider for information.

Alternatively, you can use free public services like [nip.io](https://nip.io)
which provide automatic wildcard DNS without any configuration. For [nip.io](https://nip.io),
set the Auto DevOps base domain to `1.2.3.4.nip.io`.

After completing setup, all requests hit the load balancer, which routes requests
to the Kubernetes pods running your application.

## Auto DevOps requirements for Kubernetes

To make full use of Auto DevOps with Kubernetes, you need:

- **Kubernetes** (for [Auto Review Apps](stages.md#auto-review-apps),
  [Auto Deploy](stages.md#auto-deploy), and [Auto Monitoring](stages.md#auto-monitoring))

  To enable deployments, you need:

  1. A [Kubernetes 1.12+ cluster](../../user/project/clusters/index.md) for your
     project. The easiest way is to create a
     [new cluster using the GitLab UI](../../user/project/clusters/add_remove_clusters.md#create-new-cluster).
     For Kubernetes 1.16+ clusters, you must perform additional configuration for
     [Auto Deploy for Kubernetes 1.16+](stages.md#kubernetes-116).
  1. For external HTTP traffic, an Ingress controller is required. For regular
     deployments, any Ingress controller should work, but as of GitLab 14.0,
     [canary deployments](../../user/project/canary_deployments.md) require
     NGINX Ingress. You can deploy the NGINX Ingress controller to your
     Kubernetes cluster either through the GitLab [Cluster management project template](../../user/clusters/management_project_template.md)
     or manually by using the [`ingress-nginx`](https://github.com/kubernetes/ingress-nginx/tree/master/charts/ingress-nginx)
     Helm chart.

     NOTE:
     For metrics to appear when using the [Prometheus cluster integration](../../user/clusters/integrations.md#prometheus-cluster-integration), you must [enable Prometheus metrics](https://github.com/kubernetes/ingress-nginx/tree/master/charts/ingress-nginx#prometheus-metrics).

     When deploying [using custom charts](customize.md#custom-helm-chart), you must also
     [annotate](https://kubernetes.io/docs/concepts/overview/working-with-objects/annotations/)
     the Ingress manifest to be scraped by Prometheus using
     `prometheus.io/scrape: "true"` and `prometheus.io/port: "10254"`.

     NOTE:
     If your cluster is installed on bare metal, see
     [Auto DevOps Requirements for bare metal](#auto-devops-requirements-for-bare-metal).

- **Base domain** (for [Auto Review Apps](stages.md#auto-review-apps),
  [Auto Deploy](stages.md#auto-deploy), and [Auto Monitoring](stages.md#auto-monitoring))

  You must [specify the Auto DevOps base domain](#auto-devops-base-domain),
  which all of your Auto DevOps applications use. This domain must be configured
  with wildcard DNS.

- **GitLab Runner** (for all stages)

  Your runner must be configured to run Docker, usually with either the
  [Docker](https://docs.gitlab.com/runner/executors/docker.html)
  or [Kubernetes](https://docs.gitlab.com/runner/executors/kubernetes.html) executors, with
  [privileged mode enabled](https://docs.gitlab.com/runner/executors/docker.html#use-docker-in-docker-with-privileged-mode).
  The runners don't need to be installed in the Kubernetes cluster, but the
  Kubernetes executor is easy to use and automatically autoscales.
  You can configure Docker-based runners to autoscale as well, using
  [Docker Machine](https://docs.gitlab.com/runner/executors/docker_machine.html).

  Runners should be registered as [shared runners](../../ci/runners/runners_scope.md#shared-runners)
  for the entire GitLab instance, or [specific runners](../../ci/runners/runners_scope.md#specific-runners)
  that are assigned to specific projects.

- **Prometheus** (for [Auto Monitoring](stages.md#auto-monitoring))

  To enable Auto Monitoring, you need Prometheus installed either inside or
  outside your cluster, and configured to scrape your Kubernetes cluster.
  If you've configured the GitLab integration with Kubernetes, you can
  instruct GitLab to query an in-cluster Prometheus by enabling
  the [Prometheus cluster integration](../../user/clusters/integrations.md#prometheus-cluster-integration).

  The [Prometheus integration](../../user/project/integrations/prometheus.md)
  integration must be activated for the project, or activated at the group or instance level.
  Learn more about [Project integration management](../../user/admin_area/settings/project_integration_management.md).

  To get response metrics (in addition to system metrics), you must
  [configure Prometheus to monitor NGINX](../../user/project/integrations/prometheus_library/nginx_ingress.md#configuring-nginx-ingress-monitoring).

- **cert-manager** (optional, for TLS/HTTPS)

  To enable HTTPS endpoints for your application, you can [install cert-manager](https://cert-manager.io/docs/installation/kubernetes/),
  a native Kubernetes certificate management controller that helps with issuing
  certificates. Installing cert-manager on your cluster issues a
  [Let's Encrypt](https://letsencrypt.org/) certificate and ensures the
  certificates are valid and up-to-date.

If you don't have Kubernetes or Prometheus configured, then
[Auto Review Apps](stages.md#auto-review-apps),
[Auto Deploy](stages.md#auto-deploy), and [Auto Monitoring](stages.md#auto-monitoring)
are skipped.

After all requirements are met, you can [enable Auto DevOps](index.md#enable-or-disable-auto-devops).

## Auto DevOps requirements for Amazon ECS

> [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/208132) in GitLab 13.0.

You can choose to target [AWS ECS](../../ci/cloud_deployment/index.md) as a deployment platform instead of using Kubernetes.

To get started on Auto DevOps to AWS ECS, you must add a specific CI/CD variable.
To do so, follow these steps:

1. In GitLab, on the top bar, select **Menu > Projects** and find your project.
1. On the left sidebar, select **Settings > CI/CD**.
1. Expand **Auto DevOps**.
1. Specify which AWS platform to target during the Auto DevOps deployment
   by adding the `AUTO_DEVOPS_PLATFORM_TARGET` variable with one of the following values:
   - `FARGATE` if the service you're targeting must be of launch type FARGATE.
   - `ECS` if you're not enforcing any launch type check when deploying to ECS.

When you trigger a pipeline, if you have Auto DevOps enabled and if you have correctly
[entered AWS credentials as variables](../../ci/cloud_deployment/index.md#deploy-your-application-to-the-aws-elastic-container-service-ecs),
your application is deployed to AWS ECS.

If you have both a valid `AUTO_DEVOPS_PLATFORM_TARGET` variable and a Kubernetes cluster tied to your project,
only the deployment to Kubernetes runs.

WARNING:
Setting the `AUTO_DEVOPS_PLATFORM_TARGET` variable to `ECS` triggers jobs
defined in the [`Jobs/Deploy/ECS.gitlab-ci.yml` template](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Jobs/Deploy/ECS.gitlab-ci.yml).
However, it's not recommended to [include](../../ci/yaml/index.md#includetemplate)
it on its own. This template is designed to be used with Auto DevOps only. It may change
unexpectedly causing your pipeline to fail if included on its own. Also, the job
names within this template may also change. Do not override these jobs' names in your
own pipeline, as the override stops working when the name changes.

## Auto DevOps requirements for Amazon EC2

[Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/216008) in GitLab 13.6.

You can target [AWS EC2](../../ci/cloud_deployment/index.md)
as a deployment platform instead of Kubernetes. To use Auto DevOps with AWS EC2, you must add a
specific CI/CD variable.

For more details, see [Custom build job for Auto DevOps](../../ci/cloud_deployment/index.md#custom-build-job-for-auto-devops)
for deployments to AWS EC2.

## Auto DevOps requirements for bare metal

According to the [Kubernetes Ingress-NGINX docs](https://kubernetes.github.io/ingress-nginx/deploy/baremetal/):

> In traditional cloud environments, where network load balancers are available on-demand,
a single Kubernetes manifest suffices to provide a single point of contact to the NGINX Ingress
controller to external clients and, indirectly, to any application running inside the cluster.
Bare-metal environments lack this commodity, requiring a slightly different setup to offer the
same kind of access to external consumers.

The docs linked above explain the issue and present possible solutions, for example:

- Through [MetalLB](https://github.com/metallb/metallb).
- Through [PorterLB](https://github.com/kubesphere/porterlb).