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Address feedback for AWS Runner autoscale article

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doc/articles/index.md
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......@@ -26,7 +26,7 @@ Build, test, and deploy the software you develop with [GitLab CI/CD](../ci/READM
| Article title | Category | Publishing date |
| :------------ | :------: | --------------: |
| [Autoscaling GitLab Runners on AWS](runner_autoscale_aws/index.md) | Tutorial | 2017-11-10 |
| [Autoscaling GitLab Runners on AWS](runner_autoscale_aws/index.md) | Admin guide | 2017-11-24 |
| [How to test and deploy Laravel/PHP applications with GitLab CI/CD and Envoy](laravel_with_gitlab_and_envoy/index.md) | Tutorial | 2017-08-31 |
| [How to deploy Maven projects to Artifactory with GitLab CI/CD](artifactory_and_gitlab/index.md) | Tutorial | 2017-08-15 |
| [Making CI Easier with GitLab](https://about.gitlab.com/2017/07/13/making-ci-easier-with-gitlab/) | Concepts | 2017-07-13 |
......
doc/articles/runner_autoscale_aws/index.md
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---
last_updated: 2017-11-10
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
......@@ -16,38 +21,43 @@ 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](https://aws.amazon.com/ec2/spot/)
which will greatly reduce the costs of the Runner instances while still using
quite powerful autoscaling machines.
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,
so consider the sensitivity of your projects and communication between nodes
when moving forward. This has implications on the AWS security groups you'll
need, your DNS configuration, and other networking factors.
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. Your environment is likely different, so consider what works
best for your situation.
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
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.
This way, you can customize it to your liking ahead of time based on your
networking environment.
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 tied to a user with permission to scale (EC2) and
update the cache (via S3). Create a new user with policies for EC2
(AmazonEC2FullAccess) and S3 (AmazonS3FullAccess). To be more secure, you can
disable console login for that user. Grab the security credentials as we'll use
them later during the Runner configuration.
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
......@@ -70,11 +80,7 @@ Install the prerequisites:
Now that the Runner is installed, it's time to register it.
## Registering 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.
## Registering the GitLab Runner
Before configuring the GitLab Runner, you need to first register it, so that
it connects with your GitLab instance:
......@@ -83,75 +89,29 @@ it connects with your GitLab instance:
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 GitLab Runner.
You can now move on to the most important part, configuring the GitLab Runner.
## Configuring GitLab Runner to use the AWS machine driver
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.
Here's a full example of `/etc/gitlab-runner/config.toml`. Open it with your
editor and edit as you see fit:
Let's first break it down to pieces.
```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-east-1",
"amazonec2-vpc-id=vpc-xxxxx",
"amazonec2-subnet-id=subnet-xxxxx",
"amazonec2-use-private-address=true",
"amazonec2-tags=runner-manager-name,GitLab Runner autoscale,gitlab,true,gitlab-runner-autoscale,true",
"amazonec2-security-group=docker-machine-scaler",
"amazonec2-instance-type=m4.2xlarge",
]
```
Let's break it down to pieces.
### Global section
### 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, and increase its value going
forward.
builds take, etc. You can start with something low like `10`, and increase or
decrease its value going forward.
The `check_interval` setting defines in seconds how often the Runner should
check GitLab for new jobs.
The `check_interval` option defines how often the Runner should check GitLab
for new jobs, in seconds.
Example:
......@@ -163,14 +123,14 @@ check_interval = 0
[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-global-section)
about all the options you can use.
### `[[runners]]` section
### 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 start. For more info check the [relationship between `limit`, `concurrent`
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:
......@@ -187,16 +147,17 @@ Example:
[Read more](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-section)
about all the options you can use under `[[runners]]`.
### `[runners.docker]` section
### 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).
Using `privileged = true`, all Runners will be able to run Docker in Docker
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
below.
in the following section.
Example:
......@@ -210,13 +171,13 @@ Example:
[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]`.
### `[runners.cache]` section
### 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 cache is stored.
demand, it is essential to have a common place where the cache is stored.
In the following example, we use Amazon S3:
......@@ -231,13 +192,13 @@ In the following example, we use Amazon S3:
Shared = true
```
Here's some more info to get you started:
Here's some more info to further explore the cache mechanism:
- [The `[runners.cache]` section reference](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-cache-section)
- [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)
### `[runners.machine]` section
### 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
......@@ -246,10 +207,10 @@ 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
- [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
Example:
Here's an example of the `runners.machine` section:
```toml
[runners.machine]
......@@ -267,11 +228,11 @@ Example:
MachineOptions = [
"amazonec2-access-key=XXXX",
"amazonec2-secret-key=XXXX",
"amazonec2-region=us-east-1",
"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 Runner autoscale,gitlab,true,gitlab-runner-autoscale,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",
]
......@@ -282,17 +243,19 @@ 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`. Let's see the most common ones:
- `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 to launch the instance in, read more in [Docker docs about the VPC ID](https://docs.docker.com/machine/drivers/aws/#vpc-id).
- `amazonec2-subnet-id=subnet-xxxx` - AWS VPC subnet ID.
- `amazonec2-use-private-address=true` - Use the private IP address for docker-machine, but still create a public IP address. Useful to keep the traffic internal and avoid extra costs.
- `amazonec2-tags=runner-manager-name,GitLab Runner autoscale,gitlab,true,gitlab-runner-autoscale,true` - AWS extra tag key-value pairs, useful to identify the instances on the AWS console. 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.
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
......@@ -306,17 +269,68 @@ 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 fine if your
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 exotic configuration. Read
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 Amazon:
As [described by][spot] Amazon:
>
Amazon EC2 Spot instances allow you to bid on spare Amazon EC2 computing capacity.
......@@ -325,7 +339,7 @@ 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]`](#runners-machine-section) options
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:
......@@ -339,8 +353,8 @@ section, add the following:
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. Be sure to check on the current pricing based on the
region you picked.
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:
......@@ -370,17 +384,27 @@ docker-machine ls -q --filter state=Error --format "{{.NAME}}"
```
NOTE: **Note:**
In [issue 2771](https://gitlab.com/gitlab-org/gitlab-runner/issues/2771)
there is a discussion to make GitLab Runner gracefully handle Spot price changes.
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 won't
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 influenced:
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/
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