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chore: fix multiple typos (#4889)
Hi, I finally cloned the repo and will create one big PR for the rest of my typo fixes. Editing via github web UI does not scale for either of us. 😅 Leaving this as draft until I managed to go through the whole documentation. Cheers Pascal --------- Co-authored-by: Niek Palm <npalm@users.noreply.github.com>
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CONTRIBUTING.md

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## <a name="issue"></a> Found an Issue?
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If you find a bug in the source code or a mistake in the documentation, you can help us by submitting an issue to our [Github Repository][github]. Even better you can submit a Pull Request with a fix.
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If you find a bug in the source code or a mistake in the documentation, you can help us by submitting an issue to our [GitHub Repository][github]. Even better you can submit a Pull Request with a fix.
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**Please see the [Submission Guidelines](#submit) below.**
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## <a name="feature"></a> Want a Feature?
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You can request a new feature by submitting an issue to our [Github Repository][github]. If you would like to implement a new feature then consider what kind of change it is:
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You can request a new feature by submitting an issue to our [GitHub Repository][github]. If you would like to implement a new feature then consider what kind of change it is:
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* **Major Changes** that you wish to contribute to the project should be discussed first on our [Slack group][slack] so that we can better coordinate our efforts, prevent duplication of work, and help you to craft the change so that it is successfully accepted into the project.
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* **Small Changes** can be crafted and submitted to the [Github Repository][github] as a Pull Request.
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* **Small Changes** can be crafted and submitted to the [GitHub Repository][github] as a Pull Request.
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## <a name="docs"></a> Want a Doc Fix?
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cd ..
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```
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* Push your branch to Github:
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* Push your branch to GitHub:
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```shell
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git push origin my-fix-branch
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```
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In Github, send a pull request to original main branch: f.e. `terraform-aws-github-runner:main`.
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In GitHub, send a pull request to original main branch: f.e. `terraform-aws-github-runner:main`.
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If we suggest changes, then:
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* Make the required updates.
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* Re-run the test suite to ensure tests are still passing.
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* Commit your changes to your branch (e.g. `my-fix-branch`).
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* Push the changes to your Github repository (this will update your Pull Request).
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* Push the changes to your GitHub repository (this will update your Pull Request).
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If the PR gets too outdated we may ask you to rebase and force push to update the PR:
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git push origin my-fix-branch -f
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```
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_WARNING: Squashing or reverting commits and force-pushing thereafter may remove Github comments on code that were previously made by you or others in your commits. Avoid any form of rebasing unless necessary.
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_WARNING: Squashing or reverting commits and force-pushing thereafter may remove GitHub comments on code that were previously made by you or others in your commits. Avoid any form of rebasing unless necessary.
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That's it! Thank you for your contribution!
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After your pull request is merged, you can safely delete your branch and pull the changes
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from the main (upstream) repository:
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* Delete the remote branch on Github either through the Github web UI or your local shell as follows:
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* Delete the remote branch on GitHub either through the GitHub web UI or your local shell as follows:
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```shell
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git push origin --delete my-fix-branch

README.md

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docs/additional_notes.md

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# Runner Labels
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Some CI systems require that all labels match between a job and a runner. In the case of GitHub Actions, workflows will be assigned to runners which have all the labels requested by the workflow, however it is not necessary the workflow mentions all labels.
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Some CI systems require that all labels match between a job and a runner. In the case of GitHub Actions, workflows will be assigned to runners which have all the labels requested by the workflow, however it is not necessary that the workflow mentions all labels.
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Labels specify the capabilities the runners have. The labels in the workflow are the capabilities needed. If the capabilities requested by the workflow are provided by the runners, there is match.
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Labels specify the capabilities the runners have. The labels in the workflow are the capabilities needed. If the capabilities requested by the workflow are provided by the runners, there is match.
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Examples:
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docs/configuration.md

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- Reuse vs Ephemeral. By default runners are reused, until detected idle. Once idle they will be removed from the pool. To improve security we are introducing ephemeral runners. Those runners are only used for one job. Ephemeral runners only work in combination with the workflow job event. For ephemeral runners the lambda requests a JIT (just in time) configuration via the GitHub API to register the runner. [JIT configuration](https://docs.github.com/en/actions/security-guides/security-hardening-for-github-actions#using-just-in-time-runners) is limited to ephemeral runners (and currently not supported by GHES). For non-ephemeral runners, a registration token is always requested. In both cases the configuration is made available to the instance via the same SSM parameter. To disable JIT configuration for ephemeral runners set `enable_jit_config` to `false`. We also suggest using a pre-build AMI to improve the start time of jobs for ephemeral runners.
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- Job retry (**Beta**). By default the scale-up lambda will discard the message when it is handled. Meaning in the ephemeral use-case an instance is created. The created runner will ask GitHub for a job, no guarantee it will run the job for which it was scaling. Result could be that with small system hick-up the job is keeping waiting for a runner. Enable a pool (org runners) is one option to avoid this problem. Another option is to enable the job retry function. Which will retry the job after a delay for a configured number of times.
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- GitHub Cloud vs GitHub Enterprise Server (GHES). The runners support GitHub Cloud (Public GitHub - github.com), GitHub Data Residency instances (ghe.com), and GitHub Enterprise Server. For GHES, we rely on our community for support and testing. We have no capability to test GHES ourselves.
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- Spot vs on-demand. The runners use either the EC2 spot or on-demand life cycle. Runners will be created via the AWS [CreateFleet API](https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_CreateFleet.html). The module (scale up lambda) will request via the CreateFleet API to create instances in one of the subnets and of the specified instance types.
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- Spot vs on-demand. The runners use either the EC2 spot or on-demand lifecycle. Runners will be created via the AWS [CreateFleet API](https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_CreateFleet.html). The module (scale up lambda) will request via the CreateFleet API to create instances in one of the subnets and of the specified instance types.
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- ARM64 support via Graviton/Graviton2 instance-types. When using the default example or top-level module, specifying `instance_types` that match a Graviton/Graviton 2 (ARM64) architecture (e.g. a1, t4g or any 6th-gen `g` or `gd` type), you must also specify `runner_architecture = "arm64"` and the sub-modules will be automatically configured to provision with ARM64 AMIs and leverage GitHub's ARM64 action runner. See below for more details.
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- Disable default labels for the runners (os, architecture and `self-hosted`) can achieve by setting `runner_disable_default_labels` = true. If enabled, the runner will only have the extra labels provided in `runner_extra_labels`. In case you on own start script is used, this configuration parameter needs to be parsed via SSM.
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## AMI Configuration
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> **Note:** By default, a runner AMI update requires a re-apply of the terraform configuration, as the runner AMI ID is looked up by a terraform data source. To avoid this, you can use or `ami.id_ssm_parameter_arn` to have the scale-up lambda dynamically lookup the runner AMI ID from an SSM parameter at instance launch time. Said SSM parameter is managed outside of this module (e.g. by a runner AMI build workflow).
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> **Note:** The old way of configuring AMIs using individual variables (`ami_filter`, `ami_owners`, `ami_kms_key_arn`) is deprecated and will be removed in a future version. It is recommended to migrate to the new consolidated `ami` object.
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> **Note:** The old way of configuring AMIs using individual variables (`ami_filter`, `ami_owners`, `ami_kms_key_arn`, `ami_id_ssm_parameter_arn`, `ami_id_ssm_parameter_name`) is deprecated and will be removed in a future version. It is recommended to migrate to the new consolidated `ami` object. Support for `ami_id_ssm_parameter_name` will be dropped, please specify an arn via `ami.id_ssm_parameter_arn` instead.
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## Logging
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- Traces for Github API calls (can be configured by capture_http_requests).
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- Traces for GitHub API calls (can be configured by capture_http_requests).
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### Multiple runner module in your AWS account
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The watcher will act on all spot termination notificatins and log all onses relevant to the runner module. Therefor we suggest to only deploy the watcher once. You can either deploy the watcher by enabling in one of your deployments or deploy the watcher as a stand alone module.
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The watcher will act on all spot termination notifications and log the ones relevant to the runner module. Therefor we suggest to only deploy the watcher once. You can either deploy the watcher by enabling in one of your deployments or deploy the watcher as a stand alone module.
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## Metrics
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The module supports metrics (experimental feature) to monitor the system. The metrics are disabled by default. To enable the metrics set `metrics.enable = true`. If set to true, all module managed metrics are used, you can configure the one by one via the `metrics` object. The metrics are created in the namespace `GitHub Runners`.
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The module supports metrics (experimental feature) to monitor the system. The metrics are disabled by default. To enable the metrics set `metrics.enable = true`. If set to true, all module managed metrics are used, you can configure them one by one via the `metrics` object. The metrics are created in the namespace `GitHub Runners`.
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This feature is in early stage and therefore disabled by default. To enable the watcher, set `instance_termination_watcher.enable = true`.
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The termination watcher is currently watching for spot terminations. The module is only taken events into account for instances tagged with `ghr:environment` by default when deployment the module as part of one of the main modules (root or multi-runner). The module can also be deployed stand-alone, in this case, the tag filter needs to be tuned.
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The termination watcher is currently watching for spot terminations. The module only takes events into account for instances tagged with `ghr:environment` by default, when the module is deployed as part of one of the main modules (root or multi-runner). The module can also be deployed stand-alone, in this case, the tag filter needs to be tuned.
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The watcher is listening for spot termination warnings and create a log message and optionally a metric. The watcher is disabled by default. The feature is enabled once the watcher is enabled, the feature can be disabled explicit by setting `instance_termination_watcher.features.enable_spot_termination_handler = false`.
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The watcher is listening for spot termination warnings and creates a log message and optionally a metric. The watcher is disabled by default. The feature is enabled once the watcher is enabled. It can be disabled explicitly by setting `instance_termination_watcher.features.enable_spot_termination_handler = false`.
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- Logs: The module will log all termination notifications. For each warning it will look up instance details and log the environment, instance type and time the instance is running. As well some other details.
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- Metrics: Metrics are disabled by default, this to avoid costs. Once enabled a metric will be created for each warning with at least dimensions for the environment and instance type. THe metric name space can be configured via the variables. The metric name used is `SpotInterruptionWarning`.
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- Logs: The module will log all termination notifications. For each warning it will look up instance details and log the environment, instance type and time the instance is running, as well as some other details.
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- Metrics: Metrics are disabled by default, in order to avoid costs. Once enabled a metric will be created for each warning with at least dimensions for the environment and instance type. The metric name space can be configured via the variables. The metric name used is `SpotInterruptionWarning`.
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This feature will only work once CloudTrail is enabled.
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The termination handler is listening for spot terminations by capturing the `BidEvictedEvent` via CloudTrail. The handler will log and optionally create a metric for each termination. The intent is to enhance the logic to inform the user about the termination via the GitHub Job or Workflow run. The feature is disabled by default. The feature is enabled once the watcher is enabled. It can be disabled explicitly by setting `instance_termination_watcher.features.enable_spot_termination_handler = false`.
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- Logs: The module will log all termination notifications. For each warning it will look up instance details and log the environment, instance type and time the instance is running, as well as some other details.
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- Metrics: Metrics are disabled by default, in order to avoid costs. Once enabled a metric will be created for each termination with at least dimensions for the environment and instance type. THe metric name space can be configured via the variables. The metric name used is `SpotTermination`.
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Below is an example of the log messages created.
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This module can be deployed in using the mode `EventBridge`. The `EventBridge` mode will publish an event to a eventbus. Within the eventbus, there is a target rule set, sending events to the dispatch lambda. The `EventBridge` mode is enabled by default.
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This module can be deployed in `EventBridge` mode. The `EventBridge` mode will publish an event to an eventbus. Within the eventbus, there is a target rule set, sending events to the dispatch lambda. The `EventBridge` mode is enabled by default.
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NOTE: By default, a runner AMI update requires a re-apply of this terraform config (the runner AMI ID is looked up by a terraform data source). To avoid this, you can use `ami_id_ssm_parameter_name` to have the scale-up lambda dynamically lookup the runner AMI ID from an SSM parameter at instance launch time. Said SSM parameter is managed outside of this module (e.g. by a runner AMI build workflow).

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