Commit d98b6a6f authored by Achilleas Pipinellis's avatar Achilleas Pipinellis Committed by Kamil Trzciński

Add Auto DevOps docs

parent 42e48742
......@@ -24,7 +24,7 @@ plus premium features available in each version: **Enterprise Edition Starter**
Shortcuts to GitLab's most visited docs:
| [GitLab CI](ci/README.md) | Other |
| [GitLab CI/CD](ci/README.md) | Other |
| :----- | :----- |
| [Quick start guide](ci/quick_start/README.md) | [API](api/README.md) |
| [Configuring `.gitlab-ci.yml`](ci/yaml/README.md) | [SSH authentication](ssh/README.md) |
......@@ -41,6 +41,7 @@ Shortcuts to GitLab's most visited docs:
- See also [GitLab Workflow - an overview](https://about.gitlab.com/2016/10/25/gitlab-workflow-an-overview/).
- [GitLab Markdown](user/markdown.md): GitLab's advanced formatting system (GitLab Flavored Markdown).
- [GitLab Quick Actions](user/project/quick_actions.md): Textual shortcuts for common actions on issues or merge requests that are usually done by clicking buttons or dropdowns in GitLab's UI.
- [Auto DevOps](topics/autodevops/index.md)
### User account
......
......@@ -44,6 +44,10 @@ digging into specific reference guides.
- [User permissions](../user/permissions.md#gitlab-ci)
- [Jobs permissions](../user/permissions.md#jobs-permissions)
## Auto DevOps
- [Auto DevOps](../topics/autodevops/index.md)
## GitLab CI + Docker
Leverage the power of Docker to run your CI pipelines.
......
# Auto Deploy
>**Notes:**
- [Introduced][mr-8135] in GitLab 8.15.
- Auto deploy is an experimental feature and is not recommended for Production
use at this time.
- As of GitLab 9.1, 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. On-going secure access is planned for
a subsequent release.
> [Introduced][mr-8135] in GitLab 8.15.
> Auto deploy is an experimental feature and is **not recommended for Production use** at this time.
> As of GitLab 9.1, 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**. On-going secure access is planned for a
subsequent release.
> As of GitLab 10.0, Auto Deploy templates are **deprecated** and the
functionality has been included in [Auto
DevOps](../../topics/autodevops/index.md).
Auto deploy is an easy way to configure GitLab CI for the deployment of your
application. GitLab Community maintains a list of `.gitlab-ci.yml`
......@@ -122,4 +125,3 @@ If you have installed GitLab using a different method:
[kube-deploy]: https://gitlab.com/gitlab-examples/kubernetes-deploy "Kubernetes deploy example project"
[container-registry]: https://docs.gitlab.com/ce/user/project/container_registry.html
[postgresql]: https://www.postgresql.org/
# 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)
## 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.
## 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.
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.
## Prerequisites
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.
If you are using GitLab outside of Kubernetes, for example with GitLab.com, then
you should take these prerequisites into account:
1. **Base domain** - You will need a base domain configured with wildcard DNS to
be used by all of your Auto DevOps applications.
1. **GitLab Runner** - 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).
The Runners do not need to be installed in the Kubernetes cluster, but the
Kubernetes executor is easy to use and is automatically autoscaling.
Docker-based Runners can be configured to autoscale as well, using [Docker
Machine](https://docs.gitlab.com/runner/install/autoscaling.html). Runners
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]
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).
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
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)
## Stages of Auto DevOps
The following sections describe the stages of Auto DevOps.
### Auto Build
Auto Build creates a build of the application in one of two ways:
- If there is a `Dockerfile`, it will use `docker build` to create a Docker image.
- Otherwise, it will use [Herokuish](https://github.com/gliderlabs/herokuish)
and [Heroku buildpacks](https://devcenter.heroku.com/articles/buildpacks)
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.
### Auto Test
Auto Test automatically tests 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).
Auto Test uses tests you already have in your application. If there are no
tests, it's up to you to add them.
### Auto Code Quality
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.*
### 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
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`.
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 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
enable them.
### Auto Monitoring
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
To view the metrics, open the [Monitoring dashboard for a deployed environment](../../ci/environments.md#monitoring-environments).
![Auto Metrics](img/auto_monitoring.png)
### Configuring Auto Monitoring
If GitLab has been deployed using the
[omnibus-gitlab](../../install/kubernetes/gitlab_omnibus.md) Helm chart, no
configuration is required.
If you have installed GitLab using a different method:
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"`.
## Customizing
### 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
Any variables set at the project or group level will override variables set in
the CI/CD configuration.
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
### Custom buildpack
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
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
>**Note:** Using multiple buildpacks may break Auto Test.
### Custom `Dockerfile`
If your project has a `Dockerfile` in the root of the project repo, Auto DevOps
will build a Docker image based on the Dockerfile rather than using buildpacks.
This can be much faster and result in smaller images, especially if your
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.
**Project variable** - Create a project variable `AUTO_DEVOPS_CHART` with the
URL of a custom chart to use.
### Enable staging, canaries, and more with custom `.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.
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.
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
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.
## Currently supported languages
>**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)
support it, and some third-party buildpacks as well e.g., Go, Node, Java, PHP,
Python, Ruby, Gradle, Scala, and Elixir all support Auto Test, but notably the
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
```
## Private Project Support - Experimental
When a project has been marked as private, GitLab's [Container
Registry][container-registry] requires authentication when downloading
containers. Auto DevOps will automatically provide the required authentication
information to Kubernetes, allowing temporary access to the registry.
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
planned for a subsequent release.
## Troubleshooting
- Auto Build and Auto Test may fail in detecting your language/framework. There
may be no buildpack for your application, or your application may be missing the
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).
- 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.
[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: quick start guide
> [Introduced][ce-37115] in GitLab 10.0. Auto DevOps is currently in Beta and
**not recommended for production use**.
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:
* `server.rb` - our application. It will start an HTTP server on port 5000 and
render "Hello, world!"
* `Dockerfile` - to build our app into a container image. It will use a ruby
base image and run `server.rb`
## Fork sample project on GitLab.com
Let’s start by forking our sample application. Go to [the project
page](https://gitlab.com/gitlab-examples/minimal-ruby-app) and press the `Fork`
button. Soon you should have a project under your namespace with the necessary
files.
## Setup your own cluster on Google Container Engine
If you do not already have a Google Cloud account, create one at https://console.cloud.google.com.
Visit the [`Container Engine`](https://console.cloud.google.com/kubernetes/list) tab and create a new cluster. You can change the name and leave the rest of the default settings. Once you have your cluster running, you need to connect to the cluster by following the Google interface.
## Connect to Kubernetes cluster
You need to have the Google Cloud SDK installed. e.g.
On OSX, install [homebrew](https://brew.sh):
1. Install Brew Caskroom: `brew install caskroom/cask/brew-cask`
2. Install Google Cloud SDK: `brew cask install google-cloud-sdk`
3. Add `kubectl`: `gcloud components install kubectl`
4. Log in: `gcloud auth login`
Now go back to the Google interface, find your cluster, and follow the instructions under `Connect to the cluster` and open the Kubernetes Dashboard. It will look something like `gcloud container clusters get-credentials ruby-autodeploy \ --zone europe-west2-c --project api-project-XXXXXXX` and then `kubectl proxy`.
![connect to cluster](img/guide_connect_cluster.png)
## Copy credentials to GitLab.com project
Once you have the Kubernetes Dashboard interface running, you should visit `Secrets` under the `Config` section. There you should find the settings we need for GitLab integration: ca.crt and token.
![connect to cluster](img/guide_secret.png)
You need to copy-paste the ca.crt and token into your project on GitLab.com in the Kubernetes integration page under project **Settings > Integrations > Project services > Kubernetes**. Don't actually copy the namespace though. Each project should have a unique namespace, and by leaving it blank, GitLab will create one for you.
![connect to cluster](img/guide_integration.png)
For API URL, you should use the `Endpoint` IP from your cluster page on Google Cloud Platform.
## Expose application to the world
In order to be able to visit your application, you need to install an NGINX ingress controller and point your domain name to its external IP address.
### Set up Ingress controller
You’ll need to make sure you have an ingress controller. If you don’t have one, do:
```sh
brew install kubernetes-helm
helm init
helm install --name ruby-app stable/nginx-ingress
```
This should create several services including `ruby-app-nginx-ingress-controller`. You can list your services by running `kubectl get svc` to confirm that.
### Point DNS at Cluster IP
Find out the external IP address of the `ruby-app-nginx-ingress-controller` by running:
```sh
kubectl get svc ruby-app-nginx-ingress-controller -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
```
Use this IP address to configure your DNS. This part heavily depends on your preferences and domain provider. But in case you are not sure, just create an A record with a wildcard host like `*.<your-domain>`.
Use `nslookup minimal-ruby-app-staging.<yourdomain>` to confirm that domain is assigned to the cluster IP.
## Set up Auto DevOps
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)
Then trigger your first pipeline run. This will create a new pipeline with several jobs: `build`, `test`, `codequality`, and `production`. The `build` job will create a docker image with your new change and push it to the GitLab Container Registry. The `test` job will test your change. The `codequality` job will run static analysis on your change. The `production` job will deploy your change to a production application. Once the deploy job succeeds you should be able to see your application by visiting the Kubernetes dashboard. Select the namespace of your project, which will look like `minimal-ruby-app-23`, but with a unique ID for your project, and your app will be listed as "production" under the Deployment tab.
Once its ready - just visit http://minimal-ruby-app.example.com to see “Hello, world!”
[ce-37115]: https://gitlab.com/gitlab-org/gitlab-ce/issues/37115
......@@ -7,6 +7,7 @@ you through better understanding GitLab's concepts
through our regular docs, and, when available, through articles (guides,
tutorials, technical overviews, blog posts) and videos.
- [Auto DevOps](autodevops/index.md)
- [Authentication](authentication/index.md)
- [Continuous Integration (GitLab CI)](../ci/README.md)
- [Git](git/index.md)
......
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