Docs: move article "Autoscaling Runners on AWS" to its topic-related dir

1 files changed, 1 insertions, 410 deletions

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--- a/doc/articles/runner_autoscale_aws/index.md
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----
-last_updated: 2017-11-24
----
-
-> **[Article Type](../../development/writing_documentation.html#types-of-technical-articles):** Admin guide ||
-> **Level:** intermediary ||
-> **Author:** [Achilleas Pipinellis](https://gitlab.com/axil) ||
-> **Publication date:** 2017/11/24
-
-# Autoscaling GitLab Runner on AWS
-
-One of the biggest advantages of GitLab Runner is its ability to automatically
-spin up and down VMs to make sure your builds get processed immediately. It's a
-great feature, and if used correctly, it can be extremely useful in situations
-where you don't use your Runners 24/7 and want to have a cost-effective and
-scalable solution.
-
-## Introduction
-
-In this tutorial, we'll explore how to properly configure a GitLab Runner in
-AWS that will serve as the bastion where it will spawn new Docker machines on
-demand.
-
-In addition, we'll make use of [Amazon's EC2 Spot instances][spot] which will
-greatly reduce the costs of the Runner instances while still using quite
-powerful autoscaling machines.
-
-## Prerequisites
-
-NOTE: **Note:**
-A familiarity with Amazon Web Services (AWS) is required as this is where most
-of the configuration will take place.
-
-Your GitLab instance is going to need to talk to the Runners over the network,
-and that is something you need think about when configuring any AWS security
-groups or when setting up your DNS configuration.
-
-For example, you can keep the EC2 resources segmented away from public traffic
-in a different VPC to better strengthen your network security. Your environment
-is likely different, so consider what works best for your situation.
-
-### AWS security groups
-
-Docker Machine will attempt to use a
-[default security group](https://docs.docker.com/machine/drivers/aws/#security-group)
-with rules for port `2376`, which is required for communication with the Docker
-daemon. Instead of relying on Docker, you can create a security group with the
-rules you need and provide that in the Runner options as we will
-[see below](#the-runners-machine-section). This way, you can customize it to your
-liking ahead of time based on your networking environment.
-
-### AWS credentials
-
-You'll need an [AWS Access Key](https://docs.aws.amazon.com/general/latest/gr/managing-aws-access-keys.html)
-tied to a user with permission to scale (EC2) and update the cache (via S3).
-Create a new user with [policies](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/iam-policies-for-amazon-ec2.html)
-for EC2 (AmazonEC2FullAccess) and S3 (AmazonS3FullAccess). To be more secure,
-you can disable console login for that user. Keep the tab open or copy paste the
-security credentials in an editor as we'll use them later during the
-[Runner configuration](#the-runners-machine-section).
-
-## Prepare the bastion instance
-
-The first step is to install GitLab Runner in an EC2 instance that will serve
-as the bastion that spawns new machines. This doesn't have to be a powerful
-machine since it will not run any jobs itself, a `t2.micro` instance will do.
-This machine will be a dedicated host since we need it always up and running,
-thus it will be the only standard cost.
-
-NOTE: **Note:**
-For the bastion instance, choose a distribution that both Docker and GitLab
-Runner support, for example either Ubuntu, Debian, CentOS or RHEL will work fine.
-
-Install the prerequisites:
-
-1. Log in to your server
-1. [Install GitLab Runner from the official GitLab repository](https://docs.gitlab.com/runner/install/linux-repository.html)
-1. [Install Docker](https://docs.docker.com/engine/installation/#server)
-1. [Install Docker Machine](https://docs.docker.com/machine/install-machine/)
-
-Now that the Runner is installed, it's time to register it.
-
-## Registering the GitLab Runner
-
-Before configuring the GitLab Runner, you need to first register it, so that
-it connects with your GitLab instance:
-
-1. [Obtain a Runner token](../../ci/runners/README.md)
-1. [Register the Runner](https://docs.gitlab.com/runner/register/index.html#gnu-linux)
-1. When asked the executor type, enter `docker+machine`
-
-You can now move on to the most important part, configuring the GitLab Runner.
-
-TIP: **Tip:**
-If you want every user in your instance to be able to use the autoscaled Runners,
-register the Runner as a shared one.
-
-## Configuring the GitLab Runner
-
-Now that the Runner is registered, you need to edit its configuration file and
-add the required options for the AWS machine driver.
-
-Let's first break it down to pieces.
-
-### The global section
-
-In the global section, you can define the limit of the jobs that can be run
-concurrently across all Runners (`concurrent`). This heavily depends on your
-needs, like how many users your Runners will accommodate, how much time your
-builds take, etc. You can start with something low like `10`, and increase or
-decrease its value going forward.
-
-The `check_interval` option defines how often the Runner should check GitLab
-for new jobs, in seconds.
-
-Example:
-
-```toml
-concurrent = 10
-check_interval = 0
-```
-
-[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-global-section)
-about all the options you can use.
-
-### The `runners` section
-
-From the `[[runners]]` section, the most important part is the `executor` which
-must be set to `docker+machine`. Most of those settings are taken care of when
-you register the Runner for the first time.
-
-`limit` sets the maximum number of machines (running and idle) that this Runner
-will spawn. For more info check the [relationship between `limit`, `concurrent`
-and `IdleCount`](https://docs.gitlab.com/runner/configuration/autoscale.html#how-concurrent-limit-and-idlecount-generate-the-upper-limit-of-running-machines).
-
-Example:
-
-```toml
-[[runners]]
-  name = "gitlab-aws-autoscaler"
-  url = "<URL of your GitLab instance>"
-  token = "<Runner's token>"
-  executor = "docker+machine"
-  limit = 20
-```
-
-[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-section)
-about all the options you can use under `[[runners]]`.
-
-### The `runners.docker` section
-
-In the `[runners.docker]` section you can define the default Docker image to
-be used by the child Runners if it's not defined in [`.gitlab-ci.yml`](../../ci/yaml/README.md).
-By using `privileged = true`, all Runners will be able to run
-[Docker in Docker](../../ci/docker/using_docker_build.md#use-docker-in-docker-executor)
-which is useful if you plan to build your own Docker images via GitLab CI/CD.
-
-Next, we use `disable_cache = true` to disable the Docker executor's inner
-cache mechanism since we will use the distributed cache mode as described
-in the following section.
-
-Example:
-
-```toml
-  [runners.docker]
-    image = "alpine"
-    privileged = true
-    disable_cache = true
-```
-
-[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-docker-section)
-about all the options you can use under `[runners.docker]`.
-
-### The `runners.cache` section
-
-To speed up your jobs, GitLab Runner provides a cache mechanism where selected
-directories and/or files are saved and shared between subsequent jobs.
-While not required for this setup, it is recommended to use the distributed cache
-mechanism that GitLab Runner provides. Since new instances will be created on
-demand, it is essential to have a common place where the cache is stored.
-
-In the following example, we use Amazon S3:
-
-```toml
-  [runners.cache]
-    Type = "s3"
-    ServerAddress = "s3.amazonaws.com"
-    AccessKey = "<your AWS Access Key ID>"
-    SecretKey = "<your AWS Secret Access Key>"
-    BucketName = "<the bucket where your cache should be kept>"
-    BucketLocation = "us-east-1"
-    Shared = true
-```
-
-Here's some more info to further explore the cache mechanism:
-
-- [Reference for `runners.cache`](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-cache-section)
-- [Deploying and using a cache server for GitLab Runner](https://docs.gitlab.com/runner/configuration/autoscale.html#distributed-runners-caching)
-- [How cache works](../../ci/yaml/README.md#cache)
-
-### The `runners.machine` section
-
-This is the most important part of the configuration and it's the one that
-tells GitLab Runner how and when to spawn new or remove old Docker Machine
-instances.
-
-We will focus on the AWS machine options, for the rest of the settings read
-about the:
-
-- [Autoscaling algorithm and the parameters it's based on](https://docs.gitlab.com/runner/configuration/autoscale.html#autoscaling-algorithm-and-parameters) - depends on the needs of your organization
-- [Off peak time configuration](https://docs.gitlab.com/runner/configuration/autoscale.html#off-peak-time-mode-configuration) - useful when there are regular time periods in your organization when no work is done, for example weekends
-
-Here's an example of the `runners.machine` section:
-
-```toml
-  [runners.machine]
-    IdleCount = 1
-    IdleTime = 1800
-    MaxBuilds = 10
-    OffPeakPeriods = [
-      "* * 0-9,18-23 * * mon-fri *",
-      "* * * * * sat,sun *"
-    ]
-    OffPeakIdleCount = 0
-    OffPeakIdleTime = 1200
-    MachineDriver = "amazonec2"
-    MachineName = "gitlab-docker-machine-%s"
-    MachineOptions = [
-      "amazonec2-access-key=XXXX",
-      "amazonec2-secret-key=XXXX",
-      "amazonec2-region=us-central-1",
-      "amazonec2-vpc-id=vpc-xxxxx",
-      "amazonec2-subnet-id=subnet-xxxxx",
-      "amazonec2-use-private-address=true",
-      "amazonec2-tags=runner-manager-name,gitlab-aws-autoscaler,gitlab,true,gitlab-runner-autoscale,true",
-      "amazonec2-security-group=docker-machine-scaler",
-      "amazonec2-instance-type=m4.2xlarge",
-    ]
-```
-
-The Docker Machine driver is set to `amazonec2` and the machine name has a
-standard prefix followed by `%s` (required) that is replaced by the ID of the
-child Runner: `gitlab-docker-machine-%s`.
-
-Now, depending on your AWS infrastructure, there are many options you can set up
-under `MachineOptions`. Below you can see the most common ones.
-
-| Machine option | Description |
-| -------------- | ----------- |
-| `amazonec2-access-key=XXXX` | The AWS access key of the user that has permissions to create EC2 instances, see [AWS credentials](#aws-credentials). |
-| `amazonec2-secret-key=XXXX` | The AWS secret key of the user that has permissions to create EC2 instances, see [AWS credentials](#aws-credentials). |
-| `amazonec2-region=eu-central-1` | The region to use when launching the instance. You can omit this entirely and the default `us-east-1` will be used. |
-| `amazonec2-vpc-id=vpc-xxxxx` | Your [VPC ID](https://docs.docker.com/machine/drivers/aws/#vpc-id) to launch the instance in. |
-| `amazonec2-subnet-id=subnet-xxxx` | The AWS VPC subnet ID. |
-| `amazonec2-use-private-address=true` | Use the private IP address of Docker Machines, but still create a public IP address. Useful to keep the traffic internal and avoid extra costs.|
-| `amazonec2-tags=runner-manager-name,gitlab-aws-autoscaler,gitlab,true,gitlab-runner-autoscale,true` | AWS extra tag key-value pairs, useful to identify the instances on the AWS console. The "Name" tag is set to the machine name by default. We set the "runner-manager-name" to match the Runner name set in `[[runners]]`, so that we can filter all the EC2 instances created by a specific manager setup. Read more about [using tags in AWS](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/Using_Tags.html). |
-| `amazonec2-security-group=docker-machine-scaler` | AWS VPC security group name, see [AWS security groups](#aws-security-groups). |
-| `amazonec2-instance-type=m4.2xlarge` | The instance type that the child Runners will run on. |
-
-TIP: **Tip:**
-Under `MachineOptions` you can add anything that the [AWS Docker Machine driver
-supports](https://docs.docker.com/machine/drivers/aws/#options). You are highly
-encouraged to read Docker's docs as your infrastructure setup may warrant
-different options to be applied.
-
-NOTE: **Note:**
-The child instances will use by default Ubuntu 16.04 unless you choose a
-different AMI ID by setting `amazonec2-ami`.
-
-NOTE: **Note:**
-If you specify `amazonec2-private-address-only=true` as one of the machine
-options, your EC2 instance won't get assigned a public IP. This is ok if your
-VPC is configured correctly with an Internet Gateway (IGW) and routing is fine,
-but it’s something to consider if you've got a more complex configuration. Read
-more in [Docker docs about VPC connectivity](https://docs.docker.com/machine/drivers/aws/#vpc-connectivity).
-
-[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-machine-section)
-about all the options you can use under `[runners.machine]`.
-
-### Getting it all together
-
-Here's the full example of `/etc/gitlab-runner/config.toml`:
-
-```toml
-concurrent = 10
-check_interval = 0
-
-[[runners]]
-  name = "gitlab-aws-autoscaler"
-  url = "<URL of your GitLab instance>"
-  token = "<Runner's token>"
-  executor = "docker+machine"
-  limit = 20
-  [runners.docker]
-    image = "alpine"
-    privileged = true
-    disable_cache = true
-  [runners.cache]
-    Type = "s3"
-    ServerAddress = "s3.amazonaws.com"
-    AccessKey = "<your AWS Access Key ID>"
-    SecretKey = "<your AWS Secret Access Key>"
-    BucketName = "<the bucket where your cache should be kept>"
-    BucketLocation = "us-east-1"
-    Shared = true
-  [runners.machine]
-    IdleCount = 1
-    IdleTime = 1800
-    MaxBuilds = 100
-    OffPeakPeriods = [
-      "* * 0-9,18-23 * * mon-fri *",
-      "* * * * * sat,sun *"
-    ]
-    OffPeakIdleCount = 0
-    OffPeakIdleTime = 1200
-    MachineDriver = "amazonec2"
-    MachineName = "gitlab-docker-machine-%s"
-    MachineOptions = [
-      "amazonec2-access-key=XXXX",
-      "amazonec2-secret-key=XXXX",
-      "amazonec2-region=us-central-1",
-      "amazonec2-vpc-id=vpc-xxxxx",
-      "amazonec2-subnet-id=subnet-xxxxx",
-      "amazonec2-use-private-address=true",
-      "amazonec2-tags=runner-manager-name,gitlab-aws-autoscaler,gitlab,true,gitlab-runner-autoscale,true",
-      "amazonec2-security-group=docker-machine-scaler",
-      "amazonec2-instance-type=m4.2xlarge",
-    ]
-```
-
-## Cutting down costs with Amazon EC2 Spot instances
-
-As [described by][spot] Amazon:
-
->
-Amazon EC2 Spot instances allow you to bid on spare Amazon EC2 computing capacity.
-Since Spot instances are often available at a discount compared to On-Demand
-pricing, you can significantly reduce the cost of running your applications,
-grow your application’s compute capacity and throughput for the same budget,
-and enable new types of cloud computing applications.
-
-In addition to the [`runners.machine`](#the-runners-machine-section) options
-you picked above, in `/etc/gitlab-runner/config.toml` under the `MachineOptions`
-section, add the following:
-
-```toml
-    MachineOptions = [
-      "amazonec2-request-spot-instance=true",
-      "amazonec2-spot-price=0.03",
-      "amazonec2-block-duration-minutes=60"
-    ]
-```
-
-With this configuration, Docker Machines are created on Spot instances with a
-maximum bid price of $0.03 per hour and the duration of the Spot instance is
-capped at 60 minutes. The `0.03` number mentioned above is just an example, so
-be sure to check on the current pricing based on the region you picked.
-
-To learn more about Amazon EC2 Spot instances, visit the following links:
-
-- https://aws.amazon.com/ec2/spot/
-- https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot-requests.html
-- https://aws.amazon.com/blogs/aws/focusing-on-spot-instances-lets-talk-about-best-practices/
-
-### Caveats of Spot instances
-
-While Spot instances is a great way to use unused resources and minimize the
-costs of your infrastructure, you must be aware of the implications.
-
-Running CI jobs on Spot instances may increase the failure rates because of the
-Spot instances pricing model. If the price exceeds your bid, the existing Spot
-instances will be immediately terminated and all your jobs on that host will fail.
-
-As a consequence, the auto-scale Runner would fail to create new machines while
-it will continue to request new instances. This eventually will make 60 requests
-and then AWS won't accept any more. Then once the Spot price is acceptable, you
-are locked out for a bit because the call amount limit is exceeded.
-
-If you encounter that case, you can use the following command in the bastion
-machine to see the Docker Machines state:
-
-```sh
-docker-machine ls -q --filter state=Error --format "{{.NAME}}"
-```
-
-NOTE: **Note:**
-There are some issues regarding making GitLab Runner gracefully handle Spot
-price changes, and there are reports of `docker-machine` attempting to
-continually remove a Docker Machine. GitLab has provided patches for both cases
-in the upstream project. For more information, see issues
-[#2771](https://gitlab.com/gitlab-org/gitlab-runner/issues/2771) and
-[#2772](https://gitlab.com/gitlab-org/gitlab-runner/issues/2772).
-
-## Conclusion
-
-In this guide we learned how to install and configure a GitLab Runner in
-autoscale mode on AWS.
-
-Using the autoscale feature of GitLab Runner can save you both time and money.
-Using the Spot instances that AWS provides can save you even more, but you must
-be aware of the implications. As long as your bid is high enough, there shouldn't
-be an issue.
-
-You can read the following use cases from which this tutorial was (heavily)
-influenced:
-
-- [HumanGeo - Scaling GitLab CI](http://blog.thehumangeo.com/gitlab-autoscale-runners.html)
-- [subtrakt Health - Autoscale GitLab CI Runners and save 90% on EC2 costs](https://substrakthealth.com/news/gitlab-ci-cost-savings/)
-
-[spot]: https://aws.amazon.com/ec2/spot/
+This document was moved to [another location](https://docs.gitlab.com/runner/configuration/runner_autoscale_aws/index.html).