==================== Mercurial Automation ==================== This directory contains code and utilities for building and testing Mercurial on remote machines. The ``automation.py`` Script ============================ ``automation.py`` is an executable Python script (requires Python 3.5+) that serves as a driver to common automation tasks. When executed, the script will *bootstrap* a virtualenv in ``/build/venv-automation`` then re-execute itself using that virtualenv. So there is no need for the caller to have a virtualenv explicitly activated. This virtualenv will be populated with various dependencies (as defined by the ``requirements.txt`` file). To see what you can do with this script, simply run it:: $ ./automation.py Local State =========== By default, local state required to interact with remote servers is stored in the ``~/.hgautomation`` directory. We attempt to limit persistent state to this directory. Even when performing tasks that may have side-effects, we try to limit those side-effects so they don't impact the local system. e.g. when we SSH into a remote machine, we create a temporary directory for the SSH config so the user's known hosts file isn't updated. AWS Integration =============== Various automation tasks integrate with AWS to provide access to resources such as EC2 instances for generic compute. This obviously requires an AWS account and credentials to work. We use the ``boto3`` library for interacting with AWS APIs. We do not employ any special functionality for telling ``boto3`` where to find AWS credentials. See https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html for how ``boto3`` works. Once you have configured your environment such that ``boto3`` can find credentials, interaction with AWS should *just work*. .. hint:: Typically you have a ``~/.aws/credentials`` file containing AWS credentials. If you manage multiple credentials, you can override which *profile* to use at run-time by setting the ``AWS_PROFILE`` environment variable. Resource Management ------------------- Depending on the task being performed, various AWS services will be accessed. This of course requires AWS credentials with permissions to access these services. The following AWS services can be accessed by automation tasks: * EC2 * IAM * Simple Systems Manager (SSM) Various resources will also be created as part of performing various tasks. This also requires various permissions. The following AWS resources can be created by automation tasks: * EC2 key pairs * EC2 security groups * EC2 instances * IAM roles and instance profiles * SSM command invocations When possible, we prefix resource names with ``hg-`` so they can easily be identified as belonging to Mercurial. .. important:: We currently assume that AWS accounts utilized by *us* are single tenancy. Attempts to have discrete users of ``automation.py`` (including sharing credentials across machines) using the same AWS account can result in them interfering with each other and things breaking. Cost of Operation ----------------- ``automation.py`` tries to be frugal with regards to utilization of remote resources. Persistent remote resources are minimized in order to keep costs in check. For example, EC2 instances are often ephemeral and only live as long as the operation being performed. Under normal operation, recurring costs are limited to: * Storage costs for AMI / EBS snapshots. This should be just a few pennies per month. When running EC2 instances, you'll be billed accordingly. Default instance types vary by operation. We try to be respectful of your money when choosing defaults. e.g. for Windows instances which are billed per hour, we use e.g. ``t3.medium`` instances, which cost ~$0.07 per hour. For operations that scale well to many CPUs like running Linux tests, we may use a more powerful instance like ``c5.9xlarge``. However, since Linux instances are billed per second and the cost of running an e.g. ``c5.9xlarge`` for half the time of a ``c5.4xlarge`` is roughly the same, the choice is justified. .. note:: When running Windows EC2 instances, AWS bills at the full hourly cost, even if the instance doesn't run for a full hour (per-second billing doesn't apply to Windows AMIs). Managing Remote Resources ------------------------- Occassionally, there may be an error purging a temporary resource. Or you may wish to forcefully purge remote state. Commands can be invoked to manually purge remote resources. To terminate all EC2 instances that we manage:: $ automation.py terminate-ec2-instances To purge all EC2 resources that we manage:: $ automation.py purge-ec2-resources Remote Machine Interfaces ========================= The code that connects to a remote machine and executes things is theoretically machine agnostic as long as the remote machine conforms to an *interface*. In other words, to perform actions like running tests remotely or triggering packaging, it shouldn't matter if the remote machine is an EC2 instance, a virtual machine, etc. This section attempts to document the interface that remote machines need to provide in order to be valid *targets* for remote execution. These interfaces are often not ideal nor the most flexible. Instead, they have often evolved as the requirements of our automation code have evolved. Linux ----- Remote Linux machines expose an SSH server on port 22. The SSH server must allow the ``hg`` user to authenticate using the SSH key generated by the automation code. The ``hg`` user should be part of the ``hg`` group and it should have ``sudo`` access without password prompting. The SSH channel must support SFTP to facilitate transferring files from client to server. ``/bin/bash`` must be executable and point to a bash shell executable. The ``/hgdev`` directory must exist and all its content owned by ``hg::hg``. The ``/hgdev/pyenv`` directory should contain an installation of ``pyenv``. Various Python distributions should be installed. The exact versions shouldn't matter. ``pyenv global`` should have been run so ``/hgdev/pyenv/shims/`` is populated with redirector scripts that point to the appropriate Python executable. The ``/hgdev/venv-bootstrap`` directory must contain a virtualenv with Mercurial installed. The ``/hgdev/venv-bootstrap/bin/hg`` executable is referenced by various scripts and the client. The ``/hgdev/src`` directory MUST contain a clone of the Mercurial source code. The state of the working directory is not important. In order to run tests, the ``/hgwork`` directory will be created. This may require running various ``mkfs.*`` executables and ``mount`` to provision a new filesystem. This will require elevated privileges via ``sudo``. Various dependencies to run the Mercurial test harness are also required. Documenting them is beyond the scope of this document. Various tests also require other optional dependencies and missing dependencies will be printed by the test runner when a test is skipped.