472 lines
22 KiB
Markdown
472 lines
22 KiB
Markdown
# Auto DevOps
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> - [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/37115) in GitLab 10.0.
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> - Generally available on GitLab 11.0.
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Auto DevOps are default CI/CD templates that auto-discover the source code you have. They
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enable GitLab to automatically detect, build, test, deploy, and monitor your applications.
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Leveraging [CI/CD best practices](../../ci/pipelines/pipeline_efficiency.md) and tools,
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Auto DevOps aims to simplify the setup and execution of a mature and modern software
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development lifecycle.
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## Overview
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You can spend a lot of effort to set up the workflow and processes required to
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build, deploy, and monitor your project. It gets worse when your company has
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hundreds, if not thousands, of projects to maintain. With new projects
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constantly starting up, the entire software development process becomes
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impossibly complex to manage.
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Auto DevOps provides you a seamless software development process by
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automatically detecting all dependencies and language technologies required to
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test, build, package, deploy, and monitor every project with minimal
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configuration. Automation enables consistency across your projects, seamless
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management of processes, and faster creation of new projects: push your code,
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and GitLab does the rest, improving your productivity and efficiency.
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For an introduction to Auto DevOps, watch [AutoDevOps in GitLab 11.0](https://youtu.be/0Tc0YYBxqi4).
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For requirements, see [Requirements for Auto DevOps](requirements.md) for more information.
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## Enabled by default
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> [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/41729) in GitLab 11.3.
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Auto DevOps is enabled by default for all projects and attempts to run on all pipelines
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in each project. An instance administrator can enable or disable this default in the
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[Auto DevOps settings](../../user/admin_area/settings/continuous_integration.md#auto-devops).
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Auto DevOps automatically disables in individual projects on their first pipeline failure,
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if it has not been explicitly enabled for the project.
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Since [GitLab 12.7](https://gitlab.com/gitlab-org/gitlab/-/issues/26655), Auto DevOps
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runs on pipelines automatically only if a [`Dockerfile` or matching buildpack](stages.md#auto-build)
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exists.
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If a [CI/CD configuration file](../../ci/yaml/README.md) is present in the project,
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it will continue to be used, whether or not Auto DevOps is enabled.
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## Quick start
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If you're using GitLab.com, see the [quick start guide](quick_start_guide.md)
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for setting up Auto DevOps with GitLab.com and a Kubernetes cluster on Google Kubernetes
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Engine (GKE).
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If you use a self-managed instance of GitLab, you must configure the
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[Google OAuth2 OmniAuth Provider](../../integration/google.md) before
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configuring a cluster on GKE. After configuring the provider, you can follow
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the steps in the [quick start guide](quick_start_guide.md) to get started.
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In [GitLab 13.0](https://gitlab.com/gitlab-org/gitlab/-/issues/208132) and later, it is
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possible to leverage Auto DevOps to deploy to [AWS ECS](requirements.md#auto-devops-requirements-for-amazon-ecs).
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## Comparison to application platforms and PaaS
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Auto DevOps provides features often included in an application
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platform or a Platform as a Service (PaaS). It takes inspiration from the
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innovative work done by [Heroku](https://www.heroku.com/) and goes beyond it
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in multiple ways:
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- Auto DevOps works with any Kubernetes cluster; you're not limited to running
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on GitLab's infrastructure. (Note that many features also work without Kubernetes).
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- There is no additional cost (no markup on the infrastructure costs), and you
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can use a Kubernetes cluster you host or Containers as a Service on any
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public cloud (for example, [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine/)).
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- Auto DevOps has more features including security testing, performance testing,
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and code quality testing.
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- Auto DevOps offers an incremental graduation path. If you need advanced customizations,
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you can start modifying the templates without starting over on a
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completely different platform. Review the [customizing](customize.md) documentation for more information.
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## Features
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Comprised of a set of [stages](stages.md), Auto DevOps brings these best practices to your
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project in a simple and automatic way:
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1. [Auto Build](stages.md#auto-build)
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1. [Auto Test](stages.md#auto-test)
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1. [Auto Code Quality](stages.md#auto-code-quality)
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1. [Auto SAST (Static Application Security Testing)](stages.md#auto-sast)
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1. [Auto Secret Detection](stages.md#auto-secret-detection)
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1. [Auto Dependency Scanning](stages.md#auto-dependency-scanning) **(ULTIMATE)**
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1. [Auto License Compliance](stages.md#auto-license-compliance) **(ULTIMATE)**
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1. [Auto Container Scanning](stages.md#auto-container-scanning) **(ULTIMATE)**
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1. [Auto Review Apps](stages.md#auto-review-apps)
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1. [Auto DAST (Dynamic Application Security Testing)](stages.md#auto-dast) **(ULTIMATE)**
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1. [Auto Deploy](stages.md#auto-deploy)
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1. [Auto Browser Performance Testing](stages.md#auto-browser-performance-testing) **(PREMIUM)**
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1. [Auto Monitoring](stages.md#auto-monitoring)
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1. [Auto Code Intelligence](stages.md#auto-code-intelligence)
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As Auto DevOps relies on many different components, you should have a basic
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knowledge of the following:
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- [Kubernetes](https://kubernetes.io/docs/home/)
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- [Helm](https://helm.sh/docs/)
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- [Docker](https://docs.docker.com)
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- [GitLab Runner](https://docs.gitlab.com/runner/)
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- [Prometheus](https://prometheus.io/docs/introduction/overview/)
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Auto DevOps provides great defaults for all the stages and makes use of
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[CI templates](https://gitlab.com/gitlab-org/gitlab/-/tree/master/lib/gitlab/ci/templates). You can, however,
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[customize](customize.md) almost everything to your needs, and
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[manage Auto DevOps with GitLab APIs](customize.md#extend-auto-devops-with-the-api).
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For an overview on the creation of Auto DevOps, read more
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[in this blog post](https://about.gitlab.com/blog/2017/06/29/whats-next-for-gitlab-ci/).
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NOTE: **Note:**
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Kubernetes clusters can [be used without](../../user/project/clusters/index.md)
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Auto DevOps.
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## Kubernetes requirements
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See [Auto DevOps requirements for Kubernetes](requirements.md#auto-devops-requirements-for-kubernetes).
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## Auto DevOps base domain
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The Auto DevOps base domain is required to use
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[Auto Review Apps](stages.md#auto-review-apps), [Auto Deploy](stages.md#auto-deploy), and
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[Auto Monitoring](stages.md#auto-monitoring). You can define the base domain in
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any of the following places:
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- either under the cluster's settings, whether for an instance,
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[projects](../../user/project/clusters/index.md#base-domain) or
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[groups](../../user/group/clusters/index.md#base-domain)
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- or at the project level as a variable: `KUBE_INGRESS_BASE_DOMAIN`
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- or at the group level as a variable: `KUBE_INGRESS_BASE_DOMAIN`
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- or as an instance-wide fallback in **Admin Area > Settings** under the
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**Continuous Integration and Delivery** section
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The base domain variable `KUBE_INGRESS_BASE_DOMAIN` follows the same order of precedence
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as other environment [variables](../../ci/variables/README.md#priority-of-environment-variables).
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If the CI/CD variable is not set and the cluster setting is left blank, the instance-wide **Auto DevOps domain**
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setting will be used if set.
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TIP: **Tip:**
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If you use the [GitLab managed app for Ingress](../../user/clusters/applications.md#ingress),
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the URL endpoint should be automatically configured for you. All you must do
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is use its value for the `KUBE_INGRESS_BASE_DOMAIN` variable.
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NOTE: **Note:**
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`AUTO_DEVOPS_DOMAIN` was [deprecated in GitLab 11.8](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/52363)
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and replaced with `KUBE_INGRESS_BASE_DOMAIN`, and removed in
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[GitLab 12.0](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/56959).
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Auto DevOps requires a wildcard DNS A record matching the base domain(s). For
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a base domain of `example.com`, you'd need a DNS entry like:
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```plaintext
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*.example.com 3600 A 1.2.3.4
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```
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In this case, the deployed applications are served from `example.com`, and `1.2.3.4`
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is the IP address of your load balancer; generally NGINX ([see requirements](requirements.md)).
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Setting up the DNS record is beyond the scope of this document; check with your
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DNS provider for information.
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Alternatively, you can use free public services like [nip.io](https://nip.io)
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which provide automatic wildcard DNS without any configuration. For [nip.io](https://nip.io),
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set the Auto DevOps base domain to `1.2.3.4.nip.io`.
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After completing setup, all requests hit the load balancer, which routes requests
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to the Kubernetes pods running your application.
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### AWS ECS
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See [Auto DevOps requirements for Amazon ECS](requirements.md#auto-devops-requirements-for-amazon-ecs).
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## Enabling/Disabling Auto DevOps
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When first using Auto DevOps, review the [requirements](requirements.md) to ensure
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all the necessary components to make full use of Auto DevOps are available. First-time
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users should follow the [quick start guide](quick_start_guide.md).
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GitLab.com users can enable or disable Auto DevOps only at the project level.
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Self-managed users can enable or disable Auto DevOps at the project, group, or
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instance level.
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### At the project level
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If enabling, check that your project does not have a `.gitlab-ci.yml`, or if one exists, remove it.
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1. Go to your project's **Settings > CI/CD > Auto DevOps**.
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1. Select the **Default to Auto DevOps pipeline** checkbox to enable it.
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1. (Optional, but recommended) When enabling, you can add in the
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[base domain](#auto-devops-base-domain) Auto DevOps uses to
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[deploy your application](stages.md#auto-deploy),
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and choose the [deployment strategy](#deployment-strategy).
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1. Click **Save changes** for the changes to take effect.
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After enabling the feature, an Auto DevOps pipeline is triggered on the `master` branch.
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### At the group level
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> [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/52447) in GitLab 11.10.
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Only administrators and group owners can enable or disable Auto DevOps at the group level.
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When enabling or disabling Auto DevOps at group level, group configuration is
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implicitly used for the subgroups and projects inside that group, unless Auto DevOps
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is specifically enabled or disabled on the subgroup or project.
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To enable or disable Auto DevOps at the group level:
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1. Go to your group's **Settings > CI/CD > Auto DevOps** page.
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1. Select the **Default to Auto DevOps pipeline** checkbox to enable it.
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1. Click **Save changes** for the changes to take effect.
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### At the instance level (Administrators only)
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Even when disabled at the instance level, group owners and project maintainers can still enable
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Auto DevOps at the group and project level, respectively.
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1. Go to **Admin Area > Settings > Continuous Integration and Deployment**.
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1. Select **Default to Auto DevOps pipeline for all projects** to enable it.
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1. (Optional) You can set up the Auto DevOps [base domain](#auto-devops-base-domain),
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for Auto Deploy and Auto Review Apps to use.
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1. Click **Save changes** for the changes to take effect.
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### Deployment strategy
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> [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/38542) in GitLab 11.0.
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You can change the deployment strategy used by Auto DevOps by going to your
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project's **Settings > CI/CD > Auto DevOps**. The following options
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are available:
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- **Continuous deployment to production**: Enables [Auto Deploy](stages.md#auto-deploy)
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with `master` branch directly deployed to production.
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- **Continuous deployment to production using timed incremental rollout**: Sets the
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[`INCREMENTAL_ROLLOUT_MODE`](customize.md#timed-incremental-rollout-to-production) variable
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to `timed`. Production deployments execute with a 5 minute delay between
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each increment in rollout.
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- **Automatic deployment to staging, manual deployment to production**: Sets the
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[`STAGING_ENABLED`](customize.md#deploy-policy-for-staging-and-production-environments) and
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[`INCREMENTAL_ROLLOUT_MODE`](customize.md#incremental-rollout-to-production) variables
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to `1` and `manual`. This means:
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- `master` branch is directly deployed to staging.
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- Manual actions are provided for incremental rollout to production.
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TIP: **Tip:**
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Use the [blue-green deployment](../../ci/environments/incremental_rollouts.md#blue-green-deployment) technique
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to minimize downtime and risk.
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## Using multiple Kubernetes clusters
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When using Auto DevOps, you can deploy different environments to
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different Kubernetes clusters, due to the 1:1 connection
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[existing between them](../../user/project/clusters/index.md#multiple-kubernetes-clusters).
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The [Deploy Job template](https://gitlab.com/gitlab-org/gitlab/blob/master/lib/gitlab/ci/templates/Jobs/Deploy.gitlab-ci.yml)
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used by Auto DevOps currently defines 3 environment names:
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- `review/` (every environment starting with `review/`)
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- `staging`
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- `production`
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Those environments are tied to jobs using [Auto Deploy](stages.md#auto-deploy), so
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except for the environment scope, they must have a different deployment domain.
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You must define a separate `KUBE_INGRESS_BASE_DOMAIN` variable for each of the above
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[based on the environment](../../ci/variables/README.md#limit-the-environment-scopes-of-environment-variables).
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The following table is an example of how to configure the three different clusters:
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| Cluster name | Cluster environment scope | `KUBE_INGRESS_BASE_DOMAIN` variable value | Variable environment scope | Notes |
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|--------------|---------------------------|-------------------------------------------|----------------------------|---|
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| review | `review/*` | `review.example.com` | `review/*` | The review cluster which runs all [Review Apps](../../ci/review_apps/index.md). `*` is a wildcard, used by every environment name starting with `review/`. |
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| staging | `staging` | `staging.example.com` | `staging` | (Optional) The staging cluster which runs the deployments of the staging environments. You must [enable it first](customize.md#deploy-policy-for-staging-and-production-environments). |
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| production | `production` | `example.com` | `production` | The production cluster which runs the production environment deployments. You can use [incremental rollouts](customize.md#incremental-rollout-to-production). |
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To add a different cluster for each environment:
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1. Navigate to your project's **Operations > Kubernetes**.
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1. Create the Kubernetes clusters with their respective environment scope, as
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described from the table above.
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1. After creating the clusters, navigate to each cluster and install
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Ingress. Wait for the Ingress IP address to be assigned.
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1. Make sure you've [configured your DNS](#auto-devops-base-domain) with the
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specified Auto DevOps domains.
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1. Navigate to each cluster's page, through **Operations > Kubernetes**,
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and add the domain based on its Ingress IP address.
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After completing configuration, you can test your setup by creating a merge request
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and verifying your application is deployed as a Review App in the Kubernetes
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cluster with the `review/*` environment scope. Similarly, you can check the
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other environments.
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## Limitations
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The following restrictions apply.
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### Private registry support
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No documented way of using private container registry with Auto DevOps exists.
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We strongly advise using GitLab Container Registry with Auto DevOps to
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simplify configuration and prevent any unforeseen issues.
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### Install applications behind a proxy
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GitLab's Helm integration does not support installing applications when
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behind a proxy. Users who want to do so must inject their proxy settings
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into the installation pods at runtime, such as by using a
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[`PodPreset`](https://kubernetes.io/docs/concepts/workloads/pods/podpreset/):
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```yaml
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apiVersion: settings.k8s.io/v1alpha1
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kind: PodPreset
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metadata:
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name: gitlab-managed-apps-default-proxy
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namespace: gitlab-managed-apps
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spec:
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env:
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- name: http_proxy
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value: "PUT_YOUR_HTTP_PROXY_HERE"
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- name: https_proxy
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value: "PUT_YOUR_HTTPS_PROXY_HERE"
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```
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## Troubleshooting
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### Unable to select a buildpack
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Auto Build and Auto Test may fail to detect your language or framework with the
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following error:
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```plaintext
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Step 5/11 : RUN /bin/herokuish buildpack build
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---> Running in eb468cd46085
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-----> Unable to select a buildpack
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The command '/bin/sh -c /bin/herokuish buildpack build' returned a non-zero code: 1
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```
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The following are possible reasons:
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- Your application may be missing the key files the buildpack is looking for.
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Ruby applications require a `Gemfile` to be properly detected,
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even though it's possible to write a Ruby app without a `Gemfile`.
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- No buildpack may exist for your application. Try specifying a
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[custom buildpack](customize.md#custom-buildpacks).
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### Pipeline that extends Auto DevOps with only / except fails
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If your pipeline fails with the following message:
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```plaintext
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Found errors in your .gitlab-ci.yml:
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jobs:test config key may not be used with `rules`: only
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```
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This error appears when the included job’s rules configuration has been overridden with the `only` or `except` syntax.
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To fix this issue, you must either:
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- Transition your `only/except` syntax to rules.
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- (Temporarily) Pin your templates to the [GitLab 12.10 based templates](https://gitlab.com/gitlab-org/auto-devops-v12-10).
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### Failure to create a Kubernetes namespace
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Auto Deploy will fail if GitLab can't create a Kubernetes namespace and
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service account for your project. For help debugging this issue, see
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[Troubleshooting failed deployment jobs](../../user/project/clusters/index.md#troubleshooting).
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### Detected an existing PostgreSQL database
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After upgrading to GitLab 13.0, you may encounter this message when deploying
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with Auto DevOps:
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```plaintext
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Detected an existing PostgreSQL database installed on the
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deprecated channel 1, but the current channel is set to 2. The default
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channel changed to 2 in of GitLab 13.0.
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[...]
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```
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Auto DevOps, by default, installs an in-cluster PostgreSQL database alongside
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your application. The default installation method changed in GitLab 13.0, and
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upgrading existing databases requires user involvement. The two installation
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methods are:
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- **channel 1 (deprecated):** Pulls in the database as a dependency of the associated
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Helm chart. Only supports Kubernetes versions up to version 1.15.
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- **channel 2 (current):** Installs the database as an independent Helm chart. Required
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for using the in-cluster database feature with Kubernetes versions 1.16 and greater.
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If you receive this error, you can do one of the following actions:
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- You can *safely* ignore the warning and continue using the channel 1 PostgreSQL
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database by setting `AUTO_DEVOPS_POSTGRES_CHANNEL` to `1` and redeploying.
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- You can delete the channel 1 PostgreSQL database and install a fresh channel 2
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database by setting `AUTO_DEVOPS_POSTGRES_DELETE_V1` to a non-empty value and
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redeploying.
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DANGER: **Danger:**
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Deleting the channel 1 PostgreSQL database permanently deletes the existing
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channel 1 database and all its data. See
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[Upgrading PostgreSQL](upgrading_postgresql.md)
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for more information on backing up and upgrading your database.
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- If you are not using the in-cluster database, you can set
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`POSTGRES_ENABLED` to `false` and re-deploy. This option is especially relevant to
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users of *custom charts without the in-chart PostgreSQL dependency*.
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Database auto-detection is based on the `postgresql.enabled` Helm value for
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your release. This value is set based on the `POSTGRES_ENABLED` CI variable
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and persisted by Helm, regardless of whether or not your chart uses the
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variable.
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DANGER: **Danger:**
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Setting `POSTGRES_ENABLED` to `false` permanently deletes any existing
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channel 1 database for your environment.
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### Error: unable to recognize "": no matches for kind "Deployment" in version "extensions/v1beta1"
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After upgrading your Kubernetes cluster to [v1.16+](stages.md#kubernetes-116),
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you may encounter this message when deploying with Auto DevOps:
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```plaintext
|
||
UPGRADE FAILED
|
||
Error: failed decoding reader into objects: unable to recognize "": no matches for kind "Deployment" in version "extensions/v1beta1"
|
||
```
|
||
|
||
This can occur if your current deployments on the environment namespace were deployed with a
|
||
deprecated/removed API that doesn't exist in Kubernetes v1.16+. For example,
|
||
if [your in-cluster PostgreSQL was installed in a legacy way](#detected-an-existing-postgresql-database),
|
||
the resource was created via the `extensions/v1beta1` API. However, the deployment resource
|
||
was moved to the `app/v1` API in v1.16.
|
||
|
||
To recover such outdated resources, you must convert the current deployments by mapping legacy APIs
|
||
to newer APIs. There is a helper tool called [`mapkubeapis`](https://github.com/hickeyma/helm-mapkubeapis)
|
||
that works for this problem. Follow these steps to use the tool in Auto DevOps:
|
||
|
||
1. Modify your `.gitlab-ci.yml` with:
|
||
|
||
```yaml
|
||
include:
|
||
- template: Auto-DevOps.gitlab-ci.yml
|
||
- remote: https://gitlab.com/shinya.maeda/ci-templates/-/raw/master/map-deprecated-api.gitlab-ci.yml
|
||
|
||
variables:
|
||
HELM_VERSION_FOR_MAPKUBEAPIS: "v2" # If you're using auto-depoy-image v2 or above, please specify "v3".
|
||
```
|
||
|
||
1. Run the job `<environment-name>:map-deprecated-api`. Ensure that this job succeeds before moving
|
||
to the next step. You should see something like the following output:
|
||
|
||
```shell
|
||
2020/10/06 07:20:49 Found deprecated or removed Kubernetes API:
|
||
"apiVersion: extensions/v1beta1
|
||
kind: Deployment"
|
||
Supported API equivalent:
|
||
"apiVersion: apps/v1
|
||
kind: Deployment"
|
||
```
|
||
|
||
1. Revert your `.gitlab-ci.yml` to the previous version. You no longer need to include the
|
||
supplemental template `map-deprecated-api`.
|
||
|
||
1. Continue the deployments as usual.
|
||
|
||
## Development guides
|
||
|
||
[Development guide for Auto DevOps](../../development/auto_devops.md)
|