The Importance of Idempotency in DevOps and Platform Engineering

This entry is part 4 of 4 in the series Best Practices

Introduction Idempotency is a fundamental principle of modern software development practices, particularly in DevOps and platform engineering. In simple terms, an idempotent function or script is one that produces the same output regardless of how many times it is executed with the same input. In other words, an idempotent script will leave a system in the same state every time it is run. This article explores the importance of idempotency in DevOps and platform engineering, how it can be applied in practice, and some of the tools available to support idempotent code.

Applying Idempotency in Practice Idempotency is particularly important in DevOps and platform engineering where scripts are often used to automate infrastructure deployment, configuration management, and other routine tasks. In these scenarios, it is crucial that scripts are idempotent to ensure that the system is left in a consistent state regardless of how many times the script is run.

One way to achieve idempotency is to use conditional logic in the script to check whether an operation has already been performed before attempting to perform it again. For example, in a Bash script, the “test” command can be used to check whether a file exists before attempting to create it. If the file already exists, the script will not attempt to create it again, making the script idempotent.

Example of Idempotent Bash Script:

if [ ! -f /tmp/myfile.txt ]; then
  echo "Creating file..."
  touch /tmp/myfile.txt
fi

Similarly, in PowerShell, the “Test-Path” cmdlet can be used to check whether a file or directory exists before attempting to create it.

Example of Idempotent PowerShell Script:

if (!(Test-Path -Path "C:\Temp\myfile.txt")) {
  Write-Output "Creating file..."
  New-Item -Path "C:\Temp\myfile.txt" -ItemType File
}

Idempotency in Configuration Management Tools Configuration management tools like Ansible and Chef have idempotency built in by design. These tools are designed to ensure that systems are left in a consistent state regardless of how many times a configuration management script is run. This is achieved by checking the current state of the system against the desired state defined in the script and only making changes that are necessary to bring the system into the desired state. This approach ensures that the system remains consistent even if the script is run multiple times.

Using Idempotency in Immutable Infrastructure Idempotency is particularly important in immutable infrastructure, where systems are built from pre-defined images that cannot be modified once they are deployed. In this scenario, idempotent scripts are used to ensure that the images are created in the same way every time, so that the resulting systems are consistent and predictable.

Table of Configuration Management Tools

ToolBenefits
AnsibleAgentless, idempotent, easy to learn
ChefSupports multiple platforms, idempotent, strong community support
PuppetSupports declarative language, idempotent, strong community support
SaltStackFast and scalable, idempotent, strong community support
TerraformSupports infrastructure as code, idempotent, strong community support

Other Tools for Idempotent Practices There are many other tools that can be used to conform to idempotent practices, including taskfile, a task runner that allows users to define idempotent tasks in YAML format. Taskfile provides a simple and consistent way to define and run tasks in a project, making it easy to create and maintain idempotent scripts.

Example of Idempotent Task

In addition to configuration management tools, other tooling such as Taskfile can be used to conform to idempotent practices. Taskfile is a simple and lightweight task runner that can be used to define and run tasks in a consistent and reproducible manner.

Here’s an example Taskfile to setup and build a Go project locally, with steps to prepare, configure, run, build, and version an application:

version: '3'

tasks:
  prepare:
    desc: Install project dependencies
    cmds:
      - go mod download

  configure:
    desc: Configure the application
    cmds:
      - go generate ./...
      - go build ./...
  
  run:
    desc: Run the application
    cmds:
      - ./myapp

  build:
    desc: Build the application
    cmds:
      - go build -o myapp

  version:
    desc: Display the application version
    cmds:
      - ./myapp -v

In conclusion, idempotency is a critical concept in DevOps and platform engineering. It helps ensure that systems are configured consistently and reproducibly, and can save time and resources by avoiding unnecessary work. By using idempotent tooling like configuration management tools and Taskfile, you can improve the reliability and efficiency of your infrastructure management practices.

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A Guide to Git Best Practices for Engineers

This entry is part 3 of 4 in the series Best Practices

Introduction

Git is a widely used distributed version control system that provides powerful tools to manage changes in a codebase, collaborate with other developers, and track the history of a project. As a platform engineer, you will likely work with Git on a daily basis, so it’s important to establish best practices to ensure a smooth and efficient workflow. In this article, we will cover several best practices for using Git as a platform engineer.

Setting up a repository

The first step in using Git is to set up a repository for your project. This can be done either locally or on a remote server, such as GitHub or GitLab. When setting up a repository, it’s important to choose an appropriate name and structure for your project.

To create a new repository on GitHub, for example, you can follow these steps:

  1. Sign in to your GitHub account and click the “+” icon in the top-right corner of the screen.
  2. Select “New repository” from the dropdown menu.
  3. Choose a name and description for your repository.
  4. Select the “Public” or “Private” option, depending on your needs.
  5. Click the “Create repository” button.

Adding protection to the main branch

It’s important to protect the main branch (usually named “master” or “main”) to prevent accidental or unauthorized changes. This can be done by setting up branch protection rules in your repository settings. You can require pull requests to be reviewed before merging, enforce certain checks (such as passing tests or code quality checks) before merging, and limit who can push to the main branch.

To set up branch protection rules on GitHub, for example, you can follow these steps:

  1. Go to your repository’s settings page.
  2. Click on the “Branches” tab.
  3. Select the main branch (e.g. “master” or “main”).
  4. Click the “Edit” button next to “Branch protection rules”.
  5. Choose the protections you want to enable, such as requiring pull request reviews, enforcing status checks, or restricting who can push to the branch.

Branch naming

When creating a new branch, it’s important to choose an appropriate name that reflects the work being done. A common convention is to use a prefix to indicate the type of branch (such as “feature/”, “bugfix/”, or “hotfix/”), followed by a brief description of the work being done. For example, “feature/add-login-page” or “bugfix/fix-typo-in-readme”.

Tagging

Tagging is a way to mark a specific commit as important or significant, such as a release or a milestone in the project. Tags can be annotated (with a message and metadata) or lightweight (just a name). Annotated tags are recommended for releases, as they provide more information about the tag and are easier to search and filter.

To create an annotated tag in Git, you can use the following command:

git tag -a <tagname> -m "<message>" <commit>

Commit messages best practices

Commit messages are an important way to communicate the changes being made to a codebase. Good commit messages should be clear, concise, and provide enough information to understand the change being made. A common convention is to use a short summary in the first line (limited to 50-72 characters), followed by a longer description if needed, and optionally a footer with references to issues or other related changes.

Example:

Add login page

This commit adds a new login page to the website, with a form for entering
username and password. The form is validated on the client side with
JavaScript.

Fixes #123

Using issues to refine the problem before the work is completed

Issues are a way to track and organize work

in your Git repository. They can be used to report bugs, suggest new features, or discuss improvements to the project. Using issues can help refine the problem before the work is completed, as it allows for discussions and feedback from other team members or stakeholders.

To create a new issue in GitHub, for example, you can follow these steps:

  1. Go to your repository on GitHub.
  2. Click on the “Issues” tab.
  3. Click the “New issue” button.
  4. Enter a title and description for the issue.
  5. Optionally assign the issue to a team member, label it, or add it to a project board.
  6. Click the “Submit new issue” button.

Using pull requests to merge in changes

Pull requests are a way to propose changes to a codebase and request them to be merged into the main branch. Pull requests can be reviewed and discussed by other team members before they are merged, which helps ensure the quality of the codebase.

To create a new pull request in GitHub, for example, you can follow these steps:

  1. Go to your repository on GitHub.
  2. Create a new branch for your changes.
  3. Make the desired changes to the codebase.
  4. Commit the changes and push them to the new branch.
  5. Go to the “Pull requests” tab and click the “New pull request” button.
  6. Select the base branch (usually the main branch) and the new branch with your changes.
  7. Enter a title and description for the pull request.
  8. Optionally assign the pull request to a team member, label it, or add it to a project board.
  9. Click the “Create pull request” button.

Using rebase to bring older repositories up to date before raising a PR

Before creating a pull request, it’s important to make sure your branch is up to date with the latest changes in the main branch. This can be done by using the “rebase” command to integrate the changes from the main branch into your branch.

To rebase your branch in Git, you can use the following command:

git checkout <your-branch>
git rebase <main-branch>

This will replay your changes on top of the latest changes in the main branch, creating a linear history of the changes.

Viewing previous commits and editing git history

Git allows you to view the history of a project, including all the previous commits and changes. This can be done using the “git log” command,

which shows a list of all the commits in reverse chronological order.

To view the git log in Git, you can use the following command:

git log

If you need to edit the history of a project, such as removing a commit or changing a commit message, you can use the “git rebase -i” command to interactively edit the history.

To edit the git history interactively in Git, you can use the following command:

git rebase -i <commit>

This will open a text editor with a list of all the commits in your history, allowing you to edit the commit messages or remove commits.

Amending the last commit

If you need to make a quick change to the last commit, such as fixing a typo or adding a file, you can use the “git commit –amend” command to add the changes to the last commit.

To amend the last commit in Git, you can use the following command:

git add <file>
git commit --amend

This will open a text editor with the commit message for the last commit, allowing you to edit it if needed.

Reverting a branch to a previous commit

If you need to revert a branch to a previous commit, such

as to undo a mistake or rollback changes, you can use the “git revert” command. This will create a new commit that undoes the changes introduced by a previous commit.

To revert a commit in Git, you can use the following command:

git revert <commit>

This will create a new commit that undoes the changes introduced by the specified commit.

Keeping a changelog in a repository

A changelog is a file in a repository that documents all the changes made to the project over time. It can help track the evolution of the project, and make it easier for team members and stakeholders to understand what changes have been made and when.

The Keep a Changelog website provides a recommended format for creating a changelog file in a repository, which includes sections for different types of changes, such as “Added”, “Changed”, “Deprecated”, “Removed”, “Fixed”, and “Security”.

Using semantic versioning

Semantic versioning is a system for assigning version numbers to software releases, based on a set of rules for how the version number should be incremented depending on the type of changes made to the codebase.

The Semantic Versioning website provides a specification for semantic versioning, which includes three numbers separated by dots: major, minor, and patch. The major version number is incremented for incompatible changes, the minor version number is incremented for backwards-compatible additions, and the patch version number is incremented for backwards-compatible bug fixes.

Using pre-commit to introduce git hooks

Pre-commit is a tool for introducing git hooks into a repository, which can help validate the codebase before allowing a commit to be made. Git hooks are scripts that are run automatically by Git at certain points in the workflow, such as before a commit is made.

Pre-commit provides a collection of pre-made hooks that can be used to check for common issues, such as trailing whitespace, missing or malformed docstrings, and syntax errors.

To use pre-commit in a Git repository, you can follow these steps:

  1. Install pre-commit using pip:
pip install pre-commit
  1. Create a “.pre-commit-config.yaml” file in the root of your repository, with the desired hooks:
repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v4.0.1
    hooks:
      - id: trailing-whitespace
      - id: end-of-file-fixer
  1. Run “pre-commit install” to install the hooks:
pre-commit install
  1. Make a change to the codebase and try to commit it. Pre-commit will run the configured hooks before allowing the commit to be made.

Conclusion

Git is a powerful tool for version control and collaboration, and understanding best practices for using Git can help improve the quality and reliability of a codebase. By setting up a repository, adding protection to the main branch, using branch naming, tagging, and commit messages best practices, using issues and pull requests, and using tools like pre-commit, you can create a more efficient and effective workflow for your team.

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Best Practices: Ansible

This entry is part 2 of 4 in the series Best Practices

Synopsis

This technical guide provides a detailed overview of best practices for working with Ansible in a busy DevOps team. It covers important concepts such as idempotency and how to secure sensitive information using Ansible Vault. The guide also includes information on how to organize Ansible code in a git repository and best practices for committing changes to a repository.

Summary

This technical guide provides best practices for working with Ansible in a busy DevOps team. It covers important concepts such as idempotency and how to use Ansible Vault to secure sensitive information. The guide also includes information on how to organize Ansible code in a git repository and best practices for committing changes to a repository.

Introduction

Ansible is a popular tool for automating the configuration and management of systems. In a busy DevOps team, it is important to follow best practices when working with Ansible to ensure that the codebase is maintainable and easy to work with.

One key concept to keep in mind when working with Ansible is idempotency. An idempotent operation is one that has the same result whether it is performed once or multiple times. In other words, if an operation is idempotent, it will not change the system
state if it is run multiple times with the same parameters. This is important in Ansible because it allows you to run plays multiple times without causing unintended changes to the system.

To ensure idempotency in ansible, it is important to use the state parameter in tasks. The state the parameter allows you to specify the desired state of a resource, such as whether a package should be installed or uninstalled. Using the state parameter ensures that ansible will only make changes to the system if the specified state is not already met.

Another important aspect of working with ansible is securing sensitive information. It is important to not store sensitive information such as passwords and access keys in plaintext in the ansible codebase. Instead, you can use ansible vault to encrypt sensitive information and store it securely. To use ansible vault, you can create a vault file and use the ansible-vault command to encrypt and decrypt the file as needed.

It is also important to consider how to organize ansible code in a git repository. One way to do this is to create a separate directory for each environment, such as production, staging, and development. This can make it easier to manage and track changes to the ansible codebase.

When committing changes to a git repository, it is important to follow best practices for commit messages and branch names. Commit messages should be concise and describe the changes made in the commit. Branch names should be descriptive and follow a consistent naming convention.

In addition to following best practices for commit messages and branch names, it is also important to use tickets to track development updates. Tickets should include a clear description of the work to be done and any relevant details such as links to relevant resources or dependencies.

Conclusion

By following best practices such as ensuring idempotency and securing sensitive information using ansible vault, and organizing ansible code in a git repository in a structured way, DevOps teams can effectively work with ansible to automate the configuration and management of systems. By following these guidelines, teams can ensure that their codebase is maintainable and easy to work with, enabling them to deliver new features and updates more efficiently.

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Best Practices: Packer

This entry is part 1 of 4 in the series Best Practices

Synopsis

This technical guide provides a detailed overview of best practices for working with Packer in a busy DevOps team. It includes information on concepts such as idempotency and naming standards, as well as code examples and templates for organizing Packer code in a git repository. The guide also covers considerations for security and provides templates for a README file, HCL file, and .gitignore file for a Packer repository.

Summary

This technical guide provides best practices for working with Packer in a busy DevOps team. It covers important concepts such as idempotency and naming standards, as well as providing code examples and structured into appropriate sections. The guide also includes information on how to organize Packer code in a git repository, including considerations for security, as well as templates for a README file, HCL file, and .gitignore file for a Packer repository.

Introduction

Packer is a popular tool for automating the creation of machine images. In a busy DevOps team, it is important to follow best practices when working with Packer to ensure that the codebase is maintainable and easy to work with.

One key concept to keep in mind when working with Packer is idempotency. An idempotent operation is one that has the same result whether it is performed once or multiple times. In other words, if an operation is idempotent, it will not change the system state if it is run multiple times with the same parameters. This is important in Packer because it allows you to run builds multiple times without causing unintended changes to the system.

To ensure idempotency in Packer, it is important to use the only and except parameters in the provisioner block. The only and except parameters allow you to specify the conditions under which a provisioner should run, such as the operating system or the type of machine image being built. Using these parameters ensures that Packer will only run a provisioner if the specified conditions are met.

Naming standards are another important aspect of working with Packer in a busy DevOps team. It is a good idea to use consistent naming conventions for Packer templates and variables to make the codebase easier to read and understand.

Code Examples

Here is an example of a Packer template that follows a consistent naming convention:

{
  "variables": {
    "aws_access_key": "{{env `AWS_ACCESS_KEY_ID`}}",
    "aws_secret_key": "{{env `AWS_SECRET_ACCESS_KEY`}}",
    "aws_region": "us-east-1"
  },
  "builders": [
    {
      "type": "amazon-ebs",
      "access_key": "{{aws_access_key}}",
      "secret_key": "{{aws_secret_key}}",
      "region": "{{aws_region}}",
      "source_ami": "ami-0f2176987ee50226e",
      "instance_type": "t2.micro",
      "ssh_username": "ec2-user",
      "ami_name": "packer-example {{timestamp}}"
    }
  ],
  "provisioners": [
    {
      "type": "shell",
      "inline": [
        "sudo yum update -y",
        "sudo yum install -y nginx"
      ]
    }
  ]
}

In this example, the variables are named aws_access_key, aws_secret_key, and aws_region, and the Packer template is named packer-template.json.

Organizing Packer Code in a Git Repo

When working with Packer in a busy DevOps team, it is important to organize the codebase in a way that is maintainable and easy to work with. One way to do this is to split the Packer code into different files and directories within a git repository.

One way to organize the Packer code is to separate the provisioners, builders, and variables into different files. This can make it easier to find and modify specific parts of the codebase. For example, you could create a provisioners directory to store all of the provisioner scripts, a builders directory to store the Packer templates, and a variables directory to store the variable definitions.

It is also important to consider security when organizing the Packer code in a git repository. Sensitive information such as access keys and secrets should not be stored in the repository in plaintext. Instead, you can use tools such as Hashicorp’s Vault to securely store and manage sensitive information.

Template README.md for a Packer Repo:

# Packer Repository

This repository contains Packer templates and scripts for building machine images.

## Directory Structure

The repository is organized as follows:

- `builders`: Packer templates for building machine images
- `provisioners`: Scripts for provisioning machine images
- `variables`: Variable definitions for Packer templates

## Usage

To build a machine image using a Packer template, run the following command:

```bash
packer build -var-file=variables/example.json builders/example.json
```

Replace example.json with the appropriate file names for your build.

## Contributing

To contribute to this repository, follow these steps:

+ Fork the repository
+ Create a new branch for your changes
+ Make your changes and commit them to the new branch
+ Push the branch to your fork
+ Create a pull request from your fork to the main repository

Please make sure to follow the repository's style guidelines and to run any relevant tests before submitting a pull request.

## License

This repository is licensed under the MIT License.

## Template HCL file with Headers Summarized:

## Packer Template

This Packer template is used to build a machine image.

### Builders

The following builders are used in this template:

 + Amazon Elastic Block Store (EBS)

### Provisioners

The following provisioners are used in this template:

 + Shell

### Variables

The following variables are used in this template:

+ `aws_access_key: AWS access key`
+ `aws_secret_key: AWS secret key`
+ `aws_region: AWS region`

### Usage

To build a machine image using this Packer template, run the following command:

```bash
packer build -var-file=variables/example.json template.json
```

Replace example.json with the appropriate file name for your variables.

### Contributing

To contribute to this Packer template, follow these steps:

+ Fork the repository
+ Create a new branch for your changes
+ Make your changes and commit them to the new branch
+ Push the branch to your fork
+ Create a pull request from your

Conclusion

By following best practices such as ensuring idempotency and using consistent naming conventions, and organizing Packer code in a git repository in a structured and secure way, DevOps teams can effectively work with Packer to automate the creation of machine images. By following these guidelines, teams can ensure that their codebase is maintainable and easy to work with, enabling them to deliver new features and updates more efficiently.

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