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# Auto DevOps
> [Introduced][ce-37115] in GitLab 10.0. Auto DevOps is currently in Beta and
**not recommended for production use**. Access to the Container Registry is only
available while the pipeline is running. Restarting a pod, scaling a service, or
other actions which require on-going access **will fail** even for public
projects. On-going secure access is planned for a subsequent release.
Auto DevOps brings best practices to your project in an easy and default way. A
typical web project starts with Continuous Integration (CI), then adds automated
deployment to production, and maybe some time in the future adds some kind of
monitoring. With Auto DevOps, every project has a complete workflow, with
no configuration, including:
- [Auto Build](#auto-build)
- [Auto Test](#auto-test)
- [Auto Code Quality](#auto-code-quality)
- [Auto Review Apps](#auto-review-apps)
- [Auto Deploy](#auto-deploy)
- [Auto Monitoring](#-auto-monitoring)
DANGER: Auto DevOps is currently in **Beta** and _not recommended for production use_.
> [Introduced][ce-37115] in GitLab 10.0.
Auto DevOps automatically detects, builds, tests, deploys, and monitors your
applications.
## Overview
You will need [Kubernetes](https://kubernetes.io/) and
[Prometheus](https://prometheus.io/) to make full use of Auto DevOps, but
even projects using only [GitLab Runners](https://docs.gitlab.com/runner/) will
be able to make use of Auto Build, Auto Test, and Auto Code Quality.
Auto DevOps makes use of an open source tool called
[Herokuish](https://github.com/gliderlabs/herokuish) which uses [Heroku
buildpacks](https://devcenter.heroku.com/articles/buildpacks) to automatically
detect, build, and test applications. Auto DevOps supports all of the languages
and frameworks that are [supported by
Herokuish](https://github.com/gliderlabs/herokuish#buildpacks) such as Ruby,
Rails, Node, PHP, Python, and Java, and [custom buildpacks can be
specified](#using-custom-buildpacks). *GitLab is in no way affiliated with Heroku
or Glider Labs.*
Projects can [customize](#customizing) the process by specifying [custom
buildpacks](#custom-buildpack), [custom `Dockerfile`s](#custom-dockerfile),
[custom Helm charts](#custom-helm-chart), or even copying the complete CI/CD
configuration into your project to enable staging and canary deployments, and
more.
With Auto DevOps, the software development process becomes easier to set up
as every project can have a complete workflow from build to deploy and monitoring,
with minimal to zero configuration.
## Quick start
Comprised of a set of stages, Auto DevOps brings these best practices to your
project in an easy and automatic way:
If you are using GitLab.com, see our [quick start guide](quick_start_guide.md)
for using Auto DevOps with GitLab.com and an external Kubernetes cluster on
Google Cloud.
1. [Auto Build](#auto-build)
1. [Auto Test](#auto-test)
1. [Auto Code Quality](#auto-code-quality)
1. [Auto Review Apps](#auto-review-apps)
1. [Auto Deploy](#auto-deploy)
1. [Auto Monitoring](#auto-monitoring)
For self-hosted installations, the easiest way to make use of Auto DevOps is to
install GitLab inside a Kubernetes cluster using the [GitLab-Omnibus Helm
Chart](../../install/kubernetes/gitlab_omnibus.md) which automatically installs
and configures everything you need.
As Auto DevOps relies on many different components, it's good to have a basic
knowledge of the following:
## Prerequisites
- [Kubernetes](https://kubernetes.io/docs/home/)
- [Helm](https://docs.helm.sh/)
- [Docker](https://docs.docker.com)
- [GitLab Runner](https://docs.gitlab.com/runner/)
- [Prometheus](https://prometheus.io/docs/introduction/overview/)
Auto DevOps provides great defaults for all the stages; you can, however,
[customize](#customizing) almost everything to your needs.
You will need one or more GitLab Runners, a Kubernetes cluster, and Prometheus
installed in the cluster to make full use of Auto DevOps. If you do not have
Kubernetes or Prometheus installed then Auto Review Apps, Auto Deploy, and Auto
Monitoring will be silently skipped.
## Prerequisites
If you are using GitLab outside of Kubernetes, for example with GitLab.com, then
you should take these prerequisites into account:
TIP: **Tip:**
For self-hosted installations, the easiest way to make use of Auto DevOps is to
install GitLab inside a Kubernetes cluster using the [GitLab Omnibus Helm Chart]
which automatically installs and configures everything you need!
1. **Base domain** - You will need a base domain configured with wildcard DNS to
be used by all of your Auto DevOps applications.
To make full use of Auto DevOps, you will need:
1. **GitLab Runner** - Your Runner needs to be configured to be able to run Docker.
Generally this means using the
1. **GitLab Runner** (needed for all stages) - Your Runner needs to be
configured to be able to run Docker. Generally this means using the
[Docker](https://docs.gitlab.com/runner/executors/docker.html) or [Kubernetes
executor](https://docs.gitlab.com/runner/executors/kubernetes.html), with
[privileged mode enabled](https://docs.gitlab.com/runner/executors/docker.html#use-docker-in-docker-with-privileged-mode).
......@@ -78,35 +56,98 @@ you should take these prerequisites into account:
should be registered as [shared Runners](../../ci/runners/README.md#registering-a-shared-runner)
for the entire GitLab instance, or [specific Runners](../../ci/runners/README.md#registering-a-specific-runner)
that are assigned to specific projects.
1. **Kubernetes** - To enable deploys, you will need Kubernetes 1.5+, with NGINX
ingress and wildcard SSL termination, for example using the
[`nginx-ingress`](https://github.com/kubernetes/charts/tree/master/stable/nginx-ingress)
and [`kube-lego`](https://github.com/kubernetes/charts/tree/master/stable/kube-lego)
Helm charts respectively. The [Kubernetes service][kubernetes-service]
1. **Base domain** (needed for Auto Review Apps and Auto Deploy) - You will need
a domain configured with wildcard DNS which is gonna be used by all of your
Auto DevOps applications. [Read the specifics](#auto-devops-base-domain).
1. **Kubernetes** (needed for Auto Review Apps, Auto Deploy, and Auto Monitoring) -
To enable deployments, you will need Kubernetes 1.5+. The [Kubernetes service][kubernetes-service]
integration will need to be enabled for the project, or enabled as a
[default service template](../../user/project/integrations/services_templates.md)
for the entire GitLab installation.
1. **Prometheus** - To enable Auto Monitoring, you will need Prometheus installed
somewhere (inside or outside your cluster) and configured to scrape your
Kubernetes cluster. To get response metrics (in addition to system metrics),
you need to [configure Prometheus to monitor NGINX](../../user/project/integrations/prometheus_library/nginx_ingress.md#configuring-prometheus-to-monitor-for-nginx-ingress-metrics).
1. **A load balancer** - You can use NGINX ingress by deploying it to your
Kubernetes cluster using the
[`nginx-ingress`](https://github.com/kubernetes/charts/tree/master/stable/nginx-ingress)
Helm chart.
1. **Wildcard TLS termination** - You can deploy the
[`kube-lego`](https://github.com/kubernetes/charts/tree/master/stable/kube-lego)
Helm chart to your Kubernetes cluster to automatically issue certificates
for your domains using Let's Encrypt.
1. **Prometheus** (needed for Auto Monitoring) - To enable Auto Monitoring, you
will need Prometheus installed somewhere (inside or outside your cluster) and
configured to scrape your Kubernetes cluster. To get response metrics
(in addition to system metrics), you need to
[configure Prometheus to monitor NGINX](../../user/project/integrations/prometheus_library/nginx_ingress.md#configuring-prometheus-to-monitor-for-nginx-ingress-metrics).
The [Prometheus service](../../user/project/integrations/prometheus.md)
integration needs to be enabled for the project, or enabled as a
[default service template](../../user/project/integrations/services_templates.md)
for the entire GitLab installation.
## Enabling Auto DevOps
NOTE: **Note:**
If you do not have Kubernetes or Prometheus installed, then Auto Review Apps,
Auto Deploy, and Auto Monitoring will be silently skipped.
### Auto DevOps base domain
The Auto DevOps base domain is required if you want to make use of [Auto
Review Apps](#auto-review-apps) and [Auto Deploy](#auto-deploy). It is defined
under the project's CI/CD settings while [enabling Auto DevOps](#enabling-auto-devops).
It can also be set at the project or group level as a variable, `AUTO_DEVOPS_DOMAIN`.
A wildcard DNS A record matching the base domain is required, for example,
given a base domain of `example.com`, you'd need a DNS entry like:
```
*.example.com 3600 A 1.2.3.4
```
where `example.com` is the domain name under which the deployed apps will be served,
and `1.2.3.4` is the IP address of your load balancer; generally NGINX
([see prerequisites](#prerequisites)). How to set up the DNS record is beyond
the scope of this document; you should check with your DNS provider.
In your GitLab.com project, go to **Settings > CI/CD** and find the Auto DevOps
section. Select "Enable Auto DevOps", add in your base domain, and save.
Once set up, all requests will hit the load balancer, which in turn will route
them to the Kubernetes pods that run your application(s).
![auto devops settings](img/auto_devops_settings.png)
NOTE: **Note:**
If GitLab is installed using the [GitLab Omnibus Helm Chart], there are two
options: provide a static IP, or have one assigned. For more information see the
relevant docs on the [network prerequisites](../../install/kubernetes/gitlab_omnibus.md#networking-prerequisites).
## Quick start
If you are using GitLab.com, see our [quick start guide](quick_start_guide.md)
for using Auto DevOps with GitLab.com and an external Kubernetes cluster on
Google Cloud.
## Enabling Auto DevOps
NOTE: **Note:**
If you haven't done already, read the [prerequisites](#prerequisites) to make
full use of Auto DevOps. If this is your fist time, we recommend you follow the
[quick start guide](#quick-start).
1. Go to your project's **Settings > CI/CD > General pipelines settings** and
find the Auto DevOps section
1. Select "Enable Auto DevOps"
1. Optionally, but recommended, add in the [base domain](#auto-devops-base-domain)
that will be used by Kubernetes to deploy your application
1. Hit **Save changes** for the changes to take effect
Now that it's enabled, there are a few more steps depending on whether your project
has a `.gitlab-ci.yml` or not:
- **For projects with no `.gitlab-ci.yml` present:**
A pipeline needs to be triggered either by pushing a new commit to the
repository or manually visiting `https://example.gitlab.com/<username>/<project>/pipelines/new`
and creating a new pipeline for your default branch, generally `master`.
- **For projects with a `.gitlab-ci.yml` present:**
All you need to do is remove your existing `.gitlab-ci.yml`, and you can even
do that in a branch to test Auto DevOps before committing to `master`.
## Stages of Auto DevOps
The following sections describe the stages of Auto DevOps.
The following sections describe the stages of Auto DevOps. Read them carefully
to understand how each one works.
### Auto Build
......@@ -118,18 +159,24 @@ Auto Build creates a build of the application in one of two ways:
to automatically detect and build the application into a Docker image.
Either way, the resulting Docker image is automatically pushed to the
[Container Registry][container-registry], tagged with the commit SHA.
[Container Registry][container-registry] and tagged with the commit SHA.
CAUTION: **Important:**
If you are also using Auto Review Apps and Auto Deploy and choose to provide
your own `Dockerfile`, make sure you expose your application to port
`5000` as this is the port assumed by the default Helm chart.
### Auto Test
Auto Test automatically tests your application using
Auto Test automatically runs the appropriate tests for your application using
[Herokuish](https://github.com/gliderlabs/herokuish) and [Heroku
buildpacks](https://devcenter.heroku.com/articles/buildpacks). Auto Test will
analyze your project to detect the language and framework, and run appropriate
tests. Several languages and frameworks are detected automatically, but if your
language is not detected, you may succeed with a [custom
buildpack](#custom-buildpack).
buildpacks](https://devcenter.heroku.com/articles/buildpacks) by analyzing
your project to detect the language and framework. Several languages and
frameworks are detected automatically, but if your language is not detected,
you may succeed with a [custom buildpack](#custom-buildpacks). Check the
[currently supported languages](#currently-supported-languages).
NOTE: **Note:**
Auto Test uses tests you already have in your application. If there are no
tests, it's up to you to add them.
......@@ -137,99 +184,110 @@ tests, it's up to you to add them.
Auto Code Quality uses the open source
[`codeclimate` image](https://hub.docker.com/r/codeclimate/codeclimate/) to run
static analysis and other code checks on the current code, creating a report
that is uploaded as an artifact. In GitLab EE, differences between the source
and target branches are shown in the merge request widget. *GitLab is in no way
affiliated with Code Climate.*
static analysis and other code checks on the current code. The report is
created, and is uploaded as an artifact which you can later download and check
out. In GitLab Enterprise Edition Starter, differences between the source and
target branches are
[shown in the merge request widget](../../user/project/merge_requests/code_quality_diff.md).
### Auto Review Apps
Auto Review Apps create a [Review App][review-app] for each branch. Review Apps
are temporary application environments based on the branch's code so developers,
designers, QA, product managers, and other reviewers can actually see and
interact with code changes as part of the review process.
The review app will have a unique URL based on the project name, the branch
NOTE: **Note:**
This is an optional step, since many projects do not have a Kubernetes cluster
available. If the [prerequisites](#prerequisites) are not met, the job will
silently be skipped.
CAUTION: **Caution:**
Your apps should *not* be manipulated outside of Helm (using Kubernetes directly.)
This can cause confusion with Helm not detecting the change, and subsequent
deploys with Auto DevOps can undo your changes. Also, if you change something
and want to undo it by deploying again, Helm may not detect that anything changed
in the first place, and thus not realize that it needs to re-apply the old config.
[Review Apps][review-app] are temporary application environments based on the
branch's code so developers, designers, QA, product managers, and other
reviewers can actually see and interact with code changes as part of the review
process. Auto Review Apps create a Review App for each branch.
The Review App will have a unique URL based on the project name, the branch
name, and a unique number, combined with the Auto DevOps base domain. For
example, `user-project-branch-1234.example.com`. A link to the Review App shows
up in the merge request widget for easy discovery. When the branch is deleted,
for example after the merge request is merged, the Review App will automatically
be deleted.
This is an optional step, since many projects do not have a Kubernetes cluster
available. If the Kubernetes service is not configured, or if the variable
`AUTO_DEVOPS_DOMAIN` is not available (usually set automatically by the Auto
DevOps setting), the job will silently be skipped.
### Auto Deploy
After a branch or merge request is merged into `master`, Auto Deploy deploys the
application to a `production` environment in the Kubernetes cluster, with a
namespace based on the project name and unique project ID. e.g. `project-4321`.
NOTE: **Note:**
This is an optional step, since many projects do not have a Kubernetes cluster
available. If the Kubernetes service is not configured, or if the variable
`AUTO_DEVOPS_DOMAIN` is not available (usually set automatically by the Auto
DevOps setting), the job will silently be skipped.
available. If the [prerequisites](#prerequisites) are not met, the job will
silently be skipped.
CAUTION: **Caution:**
Your apps should *not* be manipulated outside of Helm (using Kubernetes directly.)
This can cause confusion with Helm not detecting the change, and subsequent
deploys with Auto DevOps can undo your changes. Also, if you change something
and want to undo it by deploying again, Helm may not detect that anything changed
in the first place, and thus not realize that it needs to re-apply the old config.
After a branch or merge request is merged into the project's default branch (usually
`master`), Auto Deploy deploys the application to a `production` environment in
the Kubernetes cluster, with a namespace based on the project name and unique
project ID, for example `project-4321`.
Auto Deploy doesn't include deployments to staging or canary by default, but the
Auto DevOps template contains job definitions for these tasks if you want to
[Auto DevOps template] contains job definitions for these tasks if you want to
enable them.
You can make use of [environment variables](#helm-chart-variables) to automatically
scale your pod replicas.
### Auto Monitoring
NOTE: **Note:**
Check the [prerequisites](#prerequisites) for Auto Monitoring to make this stage
work.
Once your application is deployed, Auto Monitoring makes it possible to monitor
your application's server and response metrics right out of the box. Auto
Monitoring uses [Prometheus](../../user/project/integrations/prometheus.md) to
get system metrics such as CPU and memory usage directly from
[Kubernetes](../../user/project/integrations/prometheus_library/kubernetes.md),
and response metrics such as HTTP error rates, latency, and throughput from the
[NGINX
server](../../user/project/integrations/prometheus_library/nginx_ingress.md).
* Response Metrics: latency, throughput, error rate
* System Metrics: CPU utilization, memory utilization
[NGINX server](../../user/project/integrations/prometheus_library/nginx_ingress.md).
To view the metrics, open the [Monitoring dashboard for a deployed environment](../../ci/environments.md#monitoring-environments).
The metrics include:
![Auto Metrics](img/auto_monitoring.png)
- **Response Metrics:** latency, throughput, error rate
- **System Metrics:** CPU utilization, memory utilization
### Configuring Auto Monitoring
If GitLab has been deployed using the
[omnibus-gitlab](../../install/kubernetes/gitlab_omnibus.md) Helm chart, no
If GitLab has been deployed using the [GitLab Omnibus Helm Chart], no
configuration is required.
If you have installed GitLab using a different method:
If you have installed GitLab using a different method, you need to:
1. [Deploy Prometheus](../../user/project/integrations/prometheus.md#configuring-your-own-prometheus-server-within-kubernetes) into your Kubernetes cluster
1. If you would like response metrics, ensure you are running at least version 0.9.0 of NGINX Ingress and [enable Prometheus metrics](https://github.com/kubernetes/ingress/blob/master/examples/customization/custom-vts-metrics/nginx/nginx-vts-metrics-conf.yaml).
1. Finally, [annotate](https://kubernetes.io/docs/concepts/overview/working-with-objects/annotations/) the NGINX Ingress deployment to be scraped by Prometheus using `prometheus.io/scrape: "true"` and `prometheus.io/port: "10254"`.
1. If you would like response metrics, ensure you are running at least version
0.9.0 of NGINX Ingress and
[enable Prometheus metrics](https://github.com/kubernetes/ingress/blob/master/examples/customization/custom-vts-metrics/nginx/nginx-vts-metrics-conf.yaml).
1. Finally, [annotate](https://kubernetes.io/docs/concepts/overview/working-with-objects/annotations/)
the NGINX Ingress deployment to be scraped by Prometheus using
`prometheus.io/scrape: "true"` and `prometheus.io/port: "10254"`.
## Customizing
To view the metrics, open the
[Monitoring dashboard for a deployed environment](../../ci/environments.md#monitoring-environments).
### PostgreSQL Database Support
In order to support applications that require a database,
[PostgreSQL][postgresql] is provisioned by default. Credentials to access the
database are preconfigured, but can be customized by setting the associated
[variables](#postgresql-variables). These credentials can be used for defining a
`DATABASE_URL` of the format:
`postgres://user:password@postgres-host:postgres-port/postgres-database`.
PostgreSQL provisioning can be disabled by creating a project variable
`POSTGRES_ENABLED` set to `false`.
#### PostgreSQL Variables
![Auto Metrics](img/auto_monitoring.png)
Any variables set at the project or group level will override variables set in
the CI/CD configuration.
## Customizing
1. `POSTGRES_ENABLED: "false"`: disable automatic deployment of PostgreSQL
1. `POSTGRES_USER: "my-user"`: use custom username for PostgreSQL
1. `POSTGRES_PASSWORD: "password"`: use custom password for PostgreSQL
1. `POSTGRES_DB: "my-database"`: use custom database name for PostgreSQL
While Auto DevOps provides great defaults to get you started, you can customize
almost everything to fit your needs; from custom [buildpacks](#custom-buildpacks),
to [`Dockerfile`s](#custom-dockerfile), [Helm charts](#custom-helm-chart), or
even copying the complete [CI/CD configuration](#customizing-gitlab-ci-yml)
into your project to enable staging and canary deployments, and more.
### Custom buildpack
### Custom buildpacks
If the automatic buildpack detection fails for your project, or if you want to
use a custom buildpack, you can override the buildpack using a project variable
......@@ -237,12 +295,12 @@ or a `.buildpack` file in your project:
- **Project variable** - Create a project variable `BUILDPACK_URL` with the URL
of the buildpack to use.
- **`.buildpack` file** - Add a file in your project's repo called `.buildpack`
and add the URL of the buildpack to use on a line in the file. If you want to
use multiple buildpacks, you can enter them in, one on each line
use multiple buildpacks, you can enter them in, one on each line.
>**Note:** Using multiple buildpacks may break Auto Test.
CAUTION: **Caution:**
Using multiple buildpacks isn't yet supported by Auto DevOps.
### Custom `Dockerfile`
......@@ -253,37 +311,138 @@ Dockerfile is based on [Alpine](https://hub.docker.com/_/alpine/).
### Custom Helm Chart
Auto DevOps uses Helm to deploy your application to Kubernetes. You can override
the Helm chart used by bundling up a chart into your project repo or by
specifying a project variable.
**Bundled chart** - If your project has a `chart` directory with a `Chart.yaml`
file in it, Auto DevOps will detect the chart and use it instead of the default
chart. This can be a great way to control exactly how your application is
deployed.
Auto DevOps uses [Helm](https://helm.sh/) to deploy your application to Kubernetes.
You can override the Helm chart used by bundling up a chart into your project
repo or by specifying a project variable:
**Project variable** - Create a project variable `AUTO_DEVOPS_CHART` with the
URL of a custom chart to use.
- **Bundled chart** - If your project has a `./charts` directory with a `Chart.yaml`
file in it, Auto DevOps will detect the chart and use it instead of the [default
one](https://gitlab.com/charts/charts.gitlab.io/tree/master/charts/auto-deploy-app).
This can be a great way to control exactly how your application is deployed.
- **Project variable** - Create a [project variable](../../ci/variables/README.md#secret-variables)
`AUTO_DEVOPS_CHART` with the URL of a custom chart to use.
### Enable staging, canaries, and more with custom `.gitlab-ci.yml`
### Customizing `.gitlab-ci.yml`
If you want to modify the CI/CD pipeline used by Auto DevOps, you can copy the
Auto DevOps template into your project's repo and edit as you see fit.
[Auto DevOps template] into your project's repo and edit as you see fit.
From your project home page, click on the `Set up CI` button, or click on the `+`
button and `New file` and pick `.gitlab-ci.yml` as the template type, or view an
existing `.gitlab-ci.yml` file. Then select "Auto DevOps" from the template
dropdown. You will then be able to edit or add any jobs needed.
Assuming that your project is new or it doesn't have a `.gitlab-ci.yml` file
present:
For example, if you want deploys to go to a staging environment instead of
directly to a production environment, you can enable the `staging` job by
1. From your project home page, either click on the "Set up CI" button, or click
on the plus button and (`+`), then "New file"
1. Pick `.gitlab-ci.yml` as the template type
1. Select "Auto-DevOps" from the template dropdown
1. Edit the template or add any jobs needed
1. Give an appropriate commit message and hit "Commit changes"
TIP: **Tip:** The Auto DevOps template includes useful comments to help you
customize it. For example, if you want deployments to go to a staging environment
instead of directly to a production one, you can enable the `staging` job by
renaming `.staging` to `staging`. Then make sure to uncomment the `when` key of
the `production` job to turn it into a manual action instead of deploying
automatically.
### PostgreSQL database support
In order to support applications that require a database,
[PostgreSQL][postgresql] is provisioned by default. The credentials to access
the database are preconfigured, but can be customized by setting the associated
[variables](#environment-variables). These credentials can be used for defining a
`DATABASE_URL` of the format:
```yaml
postgres://user:password@postgres-host:postgres-port/postgres-database
```
### Environment variables
The following variables can be used for setting up the Auto DevOps domain,
providing a custom Helm chart, or scaling your application. PostgreSQL can be
also be customized, and you can easily use a [custom buildpack](#custom-buildpacks).
| **Variable** | **Description** |
| ------------ | --------------- |
| `AUTO_DEVOPS_DOMAIN` | The [Auto DevOps domain](#auto-devops-domain); by default set automatically by the [Auto DevOps setting](#enabling-auto-devops). |
| `AUTO_DEVOPS_CHART` | The Helm Chart used to deploy your apps; defaults to the one [provided by GitLab](https://gitlab.com/charts/charts.gitlab.io/tree/master/charts/auto-deploy-app). |
| `PRODUCTION_REPLICAS` | The number of replicas to deploy in the production environment; defaults to 1. |
| `CANARY_PRODUCTION_REPLICAS`| The number of canary replicas to deploy for [Canary Deployments](../../user/project/canary_deployments.md) in the production environment. |
| `POSTGRES_ENABLED` | Whether PostgreSQL is enabled; defaults to `"true"`. Set to `false` to disable the automatic deployment of PostgreSQL. |
| `POSTGRES_USER` | The PostgreSQL user; defaults to `user`. Set it to use a custom username. |
| `POSTGRES_PASSWORD` | The PostgreSQL password; defaults to `testing-password`. Set it to use a custom password. |
| `POSTGRES_DB` | The PostgreSQL database name; defaults to the value of [`$CI_ENVIRONMENT_SLUG`](../../ci/variables/README.md#predefined-variables-environment-variables). Set it to use a custom database name. |
| `BUILDPACK_URL` | The buildpack's full URL. It can point to either Git repositories or a tarball URL. For Git repositories, it is possible to point to a specific `ref`, for example `https://github.com/heroku/heroku-buildpack-ruby.git#v142`|
TIP: **Tip:**
Set up the replica variables using a
[project variable](../../ci/variables/README.md#secret-variables)
and scale your application by just redeploying it!
CAUTION: **Caution:**
You should *not* scale your application using Kubernetes directly. This can
cause confusion with Helm not detecting the change, and subsequent deploys with
Auto DevOps can undo your changes.
#### Advanced replica variables setup
Apart from the two replica-related variables for production mentioned above,
you can also use others for different environments.
There's a very specific mapping between Kubernetes' label named `track`,
GitLab CI/CD environment names, and the replicas environment variable.
The general rule is: `TRACK_ENV_REPLICAS`. Where:
- `TRACK`: The capitalized value of the `track`
[Kubernetes label](https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/)
in the Helm Chart app definition. If not set, it will not be taken into account
to the variable name.
- `ENV`: The capitalized environment name of the deploy job that is set in
`.gitlab-ci.yml`.
That way, you can define your own `TRACK_ENV_REPLICAS` variables with which
you will be able to scale the pod's replicas easily.
In the example below, the environment's name is `qa` which would result in
looking for the `QA_REPLICAS` environment variable:
```yaml
QA testing:
stage: deploy
environment:
name: qa
script:
- deploy qa
```
If, in addition, there was also a `track: foo` defined in the application's Helm
chart, like:
```yaml
replicaCount: 1
image:
repository: gitlab.example.com/group/project
tag: stable
pullPolicy: Always
secrets:
- name: gitlab-registry
application:
track: foo
tier: web
service:
enabled: true
name: web
type: ClusterIP
url: http://my.host.com/
externalPort: 5000
internalPort: 5000
```
then the environment variable would be `FOO_QA_REPLICAS`.
## Currently supported languages
>**Note:**
NOTE: **Note:**
Not all buildpacks support Auto Test yet, as it's a relatively new
enhancement. All of Heroku's [officially supported
languages](https://devcenter.heroku.com/articles/heroku-ci#currently-supported-languages)
......@@ -294,22 +453,28 @@ multi-buildpack does not.
As of GitLab 10.0, the supported buildpacks are:
```
* heroku-buildpack-multi v1.0.0
* heroku-buildpack-ruby v168
* heroku-buildpack-nodejs v99
* heroku-buildpack-clojure v77
* heroku-buildpack-python v99
* heroku-buildpack-java v53
* heroku-buildpack-gradle v23
* heroku-buildpack-scala v78
* heroku-buildpack-play v26
* heroku-buildpack-php v122
* heroku-buildpack-go v72
* heroku-buildpack-erlang fa17af9
* buildpack-nginx v8
- heroku-buildpack-multi v1.0.0
- heroku-buildpack-ruby v168
- heroku-buildpack-nodejs v99
- heroku-buildpack-clojure v77
- heroku-buildpack-python v99
- heroku-buildpack-java v53
- heroku-buildpack-gradle v23
- heroku-buildpack-scala v78
- heroku-buildpack-play v26
- heroku-buildpack-php v122
- heroku-buildpack-go v72
- heroku-buildpack-erlang fa17af9
- buildpack-nginx v8
```
## Private Project Support - Experimental
## Limitations
The following restrictions apply.
### Private project support
CAUTION: **Caution:** Private project support in Auto DevOps is experimental.
When a project has been marked as private, GitLab's [Container
Registry][container-registry] requires authentication when downloading
......@@ -319,27 +484,10 @@ Authentication credentials will be valid while the pipeline is running, allowing
for a successful initial deployment.
After the pipeline completes, Kubernetes will no longer be able to access the
container registry. **Restarting a pod, scaling a service, or other actions which
require on-going access to the registry will fail**. On-going secure access is
Container Registry. **Restarting a pod, scaling a service, or other actions which
require on-going access to the registry may fail**. On-going secure access is
planned for a subsequent release.
## Disable the banner instance wide
If an administrater would like to disable the banners on an instance level, this
feature can be disabled either through the console:
```basb
$ gitlab-rails console
[1] pry(main)> Feature.get(:auto_devops_banner_disabled).disable
=> true
```
Or through the HTTP API with the admin access token:
```
curl --data "value=true" --header "PRIVATE-TOKEN: 9koXpg98eAheJpvBs5tK" https://gitlab.example.com/api/v4/features/auto_devops_banner_disabled
```
## Troubleshooting
- Auto Build and Auto Test may fail in detecting your language/framework. There
......@@ -347,13 +495,36 @@ curl --data "value=true" --header "PRIVATE-TOKEN: 9koXpg98eAheJpvBs5tK" https://
key files the buildpack is looking for. For example, for ruby apps, you must
have a `Gemfile` to be properly detected, even though it is possible to write a
Ruby app without a `Gemfile`. Try specifying a [custom
buildpack](#custom-buildpack).
buildpack](#custom-buildpacks).
- Auto Test may fail because of a mismatch between testing frameworks. In this
case, you may need to customize your `.gitlab-ci.yml` with your test commands.
### Disable the banner instance wide
If an administrator would like to disable the banners on an instance level, this
feature can be disabled either through the console:
```sh
sudo gitlab-rails console
```
Then run:
```ruby
Feature.get(:auto_devops_banner_disabled).disable
```
Or through the HTTP API with an admin access token:
```sh
curl --data "value=true" --header "PRIVATE-TOKEN: private_token" https://gitlab.example.com/api/v4/features/auto_devops_banner_disabled
```
[ce-37115]: https://gitlab.com/gitlab-org/gitlab-ce/issues/37115
[kubernetes-service]: ../../user/project/integrations/kubernetes.md
[docker-in-docker]: ../../docker/using_docker_build.md#use-docker-in-docker-executor
[review-app]: ../../ci/review_apps/index.md
[container-registry]: ../../user/project/container_registry.md
[postgresql]: https://www.postgresql.org/
[Auto DevOps template]: https://gitlab.com/gitlab-org/gitlab-ci-yml/blob/master/Auto-DevOps.gitlab-ci.yml
[GitLab Omnibus Helm Chart]: ../../install/kubernetes/gitlab_omnibus.md
doc/topics/autodevops/quick_start_guide.md
View file @ 4039c228
# Auto DevOps: quick start guide
> [Introduced][ce-37115] in GitLab 10.0. Auto DevOps is currently in Beta and
**not recommended for production use**.
DANGER: Auto DevOps is currently in **Beta** and _not recommended for production use_.
> [Introduced][ce-37115] in GitLab 10.0.
This is a step-by-step guide to deploying a project hosted on GitLab.com to
Google Cloud, using Auto DevOps.
We made a minimal [Ruby
application](https://gitlab.com/gitlab-examples/minimal-ruby-app) to use as an
example for this guide. It contains two files:
application](https://gitlab.com/auto-devops-examples/minimal-ruby-app) to use
as an example for this guide. It contains two main files:
* `server.rb` - our application. It will start an HTTP server on port 5000 and
render "Hello, world!"
......@@ -113,11 +114,9 @@ assigned to the cluster IP.
In your GitLab.com project, go to **Settings > CI/CD** and find the Auto DevOps
section. Select "Enable Auto DevOps", add in your base domain, and save.
![auto devops settings](img/auto_devops_settings.png)
Next, a pipeline needs to be triggered. Since the test project doesn't have a
`.gitlab-ci.yml`, you need to either push a change to the repository or
manually visit `https://gitlab.com/<username>/minimal-ruby-app/pipelines/run`,
manually visit `https://gitlab.com/<username>/minimal-ruby-app/pipelines/new`,
where `<username>` is your username.
This will create a new pipeline with several jobs: `build`, `test`, `codequality`,
......
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