Navigating IAC: A Guide To The 22 Best Tools Of 2024
10 Best IAC Tools Shortlist
Here's my pick of the 10 best software from the 22 tools reviewed.
Our one-on-one guidance will help you find the perfect fit.
As someone who has navigated the ins and outs of infrastructure management, I fully appreciate the pain points you're likely experiencing. Modern software development requires managing a lot of moving parts - dependencies, cloud resources, on-premises hardware, operating systems, and the list goes on.
Tools like Amazon's CLI, Microsoft's Azure Resource Manager, and others on GitHub have become indispensable. They help provision infrastructure across cloud environments and handle the automation necessary for efficient software delivery.
Let's talk about Infrastructure as Code (IAC) tools - they transform infrastructure configuration into source code. I can't overstate how transformative this is; it enables automation of infrastructure deployments, making them as manageable as version-controlled code.
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We can use familiar programming languages like Ruby, JavaScript, or TypeScript, or domain-specific languages (DSL) like HashiCorp Configuration Language.
These tools, some of which are becoming quite popular, allow us to declare our infrastructure requirements, and they create and manage the necessary cloud resources or virtual machines to meet those requirements.
We can set up dependencies, manage different operating systems, and create SSH keys all with code, reducing the risk of manual errors. This declarative approach to defining our infrastructure is the game changer, as it assures the state of our systems matches our source code declarations.
This is why you'll want to seriously consider the IAC options I'm going to share.
What Are IAC Tools?
Infrastructure as Code (IAC) tools are digital powerhouses, transforming the way technology practitioners manage and provision their IT resources. At their core, these tools allow IT infrastructure to be managed programmatically, making the entire process more efficient, repeatable, and secure. IAC tools are favored by system administrators, developers, and DevOps professionals who strive to automate the setup, deployment, and management of servers and networks.
They're used to maintain consistency across different environments, speed up deployment times, and minimize potential human error during configuration. Whether you're managing a small-scale project or a large, complex system, IAC tools offer a way to streamline operations and drive high-performing digital environments.
Best IAC Tools Summary
| Tools | Price | |
|---|---|---|
| Docker | From $5/user/month (billed annually) | Website |
| Chef | From $137/node/year (billed annually) | Website |
| Terraform | From $20/user/month (billed annually) | Website |
| GitLab | From $4/user/month (billed annually) | Website |
| Google Cloud Deployment Manager (GCP) | Open source project and available for free | Website |
| Vagrant | Open source project and available for free | Website |
| CloudFormation (AWS) | Pricing upon request | Website |
| Kubernetes | Open source project and available for free | Website |
| Ansible | From $10,000/year (billed annually) | Website |
| Jenkins | Open source project and available for free | Website |
Compare Software Specs Side by Side
Use our comparison chart to review and evaluate software specs side-by-side.
Compare SoftwareBest IAC Tools Reviews
Docker
Best for enabling developers to package applications into containers
Docker is an open-source platform that allows developers to automate the deployment, scaling, and running of applications by containerizing them. Its ability to isolate applications into separate containers makes it the perfect tool for developers to package applications, thus proving its worth in the 'best for' statement.
Why I Picked Docker:
Docker caught my attention due to its distinct advantage of enabling application isolation, which helps in reducing conflicts between systems. I chose Docker for its unique proposition of packaging applications into separate containers to ensure seamless deployment across multiple environments. This led me to decide that Docker stands out as the best tool for enabling developers to package applications into containers.
Standout features and integrations:
One of Docker's prominent features is the Dockerfile, which automates the creation of Docker images. It also provides a Docker Compose tool that simplifies the process of running multi-container applications.
Docker integrates with many CI/CD tools like Jenkins and GitLab, enhancing the development and deployment pipeline. It also pairs well with Kubernetes for container orchestration.
Pros and cons
Pros:
- Wide range of integrations, especially with CI/CD tools
- Docker Compose simplifies multi-container application deployment
- Application isolation reduces system conflicts
Cons:
- Some concerns about the security of containerization
- Not all applications are suitable for containerization
- Initial learning curve can be steep
Chef
Best for achieving speed, scalability, and consistency in your automation
Chef is an open-source automation platform that transforms infrastructure into code. It allows you to automate how you build, deploy, and manage your infrastructure. Chef excels in offering speed, scalability, and consistency, which is precisely why I deem it best for these aspects in automation.
Why I Picked Chef:
I chose Chef due to its vibrant, supportive community and its robust testing and deployment pipeline. Chef has distinguished itself with its 'cookbook' approach to scripting, allowing for reusable code pieces. Moreover, its procedural style of coding makes it a standout for achieving speed, scalability, and consistency, making it a reliable tool for comprehensive infrastructure automation.
Standout features and integrations:
Chef's key features include its powerful 'cookbook' style of scripting, a vibrant community for support, and its testing and deployment capabilities. Chef integrates well with cloud services like AWS, Google Cloud, and Azure, and it plays nicely with other DevOps tools such as Jenkins, Docker, and Git.
Pros and cons
Pros:
- Robust testing and deployment pipeline
- Strong community support
- Procedural style of coding for granular control
Cons:
- May be complex for smaller environments
- Needs significant initial setup
- Learning curve can be steep
Terraform is an open-source tool that allows you to define and provide data center infrastructure using a declarative configuration language. It gives you an easy way to manage existing service providers as well as custom in-house solutions.
Why I Picked Terraform:
I selected Terraform due to its versatile approach to Infrastructure as Code (IaC). It stands out because it's cloud-agnostic, supporting numerous service providers, and its ability to manage complex and interdependent infrastructure safely and efficiently is exceptional. This tool is 'best for' codifying API-driven infrastructure across multiple providers due to its high compatibility and ease of integration with various platforms.
Standout features and integrations:
Terraform enables you to create, combine, and manage infrastructure resources from various providers in a seamless way. It features a robust plan command that generates an execution plan, outlining what it will do to reach the desired state of infrastructure. Terraform's most notable integrations include major cloud providers like AWS, Google Cloud, Azure, and several other third-party services like Cloudflare, Heroku, and Datadog.
Pros and cons
Pros:
- Offers detailed visibility into changes before implementation
- Uses a declarative language to describe infrastructure
- Supports multiple cloud service providers
Cons:
- No central UI for monitoring and managing deployments
- State management can become complicated in large environments
- Complex syntax can be difficult for beginners
GitLab
Best for an all-in-one package with features like issue tracking, CI/CD pipelines, and more
GitLab is a single application for the entire DevOps lifecycle. It provides a unified experience for various activities involved in software development, such as version control, issue tracking, continuous integration, and deployment. The fact that it serves as an all-in-one package for multiple aspects of a project lifecycle positions it well for the 'best for' statement.
Why I Picked GitLab:
I chose GitLab for its comprehensive suite of tools that support all stages of the DevOps lifecycle. Its uniqueness lies in its ability to offer features like issue tracking, CI/CD pipelines, and more within a single application. This makes it stand out amongst other tools. Furthermore, my judgment of GitLab as the best tool for a comprehensive package of features is derived from its holistic approach to project management.
Standout features and integrations:
GitLab's standout features include built-in continuous integration and continuous deployment, auto DevOps to automate the entire DevOps lifecycle, and comprehensive issue tracking and project management tools.
GitLab integrates seamlessly with a multitude of tools, such as Kubernetes, Jira, Slack, and more. These integrations enhance its capabilities and offer extended versatility.
Pros and cons
Pros:
- Offers a wide range of integrations
- Provides robust CI/CD capabilities
- All-in-one tool for the entire DevOps lifecycle
Cons:
- Some advanced features are only available in the higher-priced tiers
- User interface could be more intuitive
- Can be overwhelming for beginners due to its comprehensive features
Best for modeling and deploying resources to Google Cloud
Google Cloud Deployment Manager is a service offered by Google that allows you to specify all the resources needed for your application in a declarative format using yaml. This service facilitates the consistent deployment of resources on Google Cloud, justifying its position as the go-to tool for resource deployment on the Google Cloud Platform.
Why I Picked Google Cloud Deployment Manager (GCP):
When selecting this tool, I prioritized its native integration with Google Cloud Platform (GCP) services. As an intrinsic part of GCP, Deployment Manager stands out for its capacity to streamline the deployment process within the Google Cloud ecosystem. Thus, I chose it for its aptitude in effectively modeling and deploying resources to Google Cloud.
Standout features and integrations:
Google Cloud Deployment Manager provides features like composite types and template language flexibility, supporting both Python and Jinja2. It integrates proficiently with various Google Cloud Services such as Compute Engine, Cloud Storage, and BigQuery, ensuring a comprehensive management solution within the Google Cloud ecosystem.
Pros and cons
Pros:
- Supports both Python and Jinja2 for templates
- Provides consistent deployment of resources
- Excellent integration with GCP services
Cons:
- Deployment changes might require significant time to apply
- Can have a steep learning curve for beginners
- Limited to Google Cloud Platform
Vagrant is a tool designed to set up and provision virtual environments for developers, making it easier to manage and share development settings across teams. Its primary function is to create portable and reproducible environments, making it ideal for managing virtual development spaces.
Why I Picked Vagrant:
After comparing various options, I selected Vagrant due to its ability to simplify the process of setting up development environments. This ability makes it stand out as it eases the burden of configuring systems for developers, increasing efficiency and productivity. Therefore, I found Vagrant to be the best for creating and managing virtual development environments.
Standout features and integrations:
One of the essential features of Vagrant is its seamless compatibility with various virtualization tools like VMware and Docker, as well as system configuration tools like Chef, Puppet, and Ansible. This compatibility greatly enhances its versatility and usability.
Pros and cons
Pros:
- Supports multiple platforms and systems
- Compatible with various virtualization tools
- Open-source and free to use
Cons:
- Some features may not be intuitive for first-time users
- Troubleshooting issues can be complex
- May require a learning curve for beginners
Best for leveraging AWS resources to create and manage a collection of related AWS resources
CloudFormation is an AWS-native service designed to use AWS resources to create and manage a collection of related resources. With CloudFormation, you can model and provision your AWS resources in a predictable, repeatable way. I believe it is particularly efficient in making full use of AWS resources to manage your cloud infrastructure.
Why I Picked CloudFormation (AWS):
In my comparison of IaC tools, CloudFormation stood out due to its seamless integration with AWS resources. As an AWS native tool, it offers unparalleled functionality within its ecosystem, leading to a more efficient workflow and resource management. Its unique standing as a tool that can harness the full power of AWS resources renders it ideal for users deeply embedded in the AWS ecosystem.
Standout features and integrations:
CloudFormation provides features like rollback on failure, fine-grained access controls, and nested stacks. These features contribute significantly to resource management efficiency and error handling. Given its AWS-centric nature, CloudFormation integrates flawlessly with the full suite of AWS services, including but not limited to S3, EC2, RDS, and Lambda.
Pros and cons
Pros:
- Robust error management with rollback features
- Allows for easy modeling and provisioning of resources
- Seamless integration with AWS services
Cons:
- Difficult to test changes before applying them
- Complex JSON or YAML syntax might be challenging for beginners
- Specific to the AWS ecosystem
Kubernetes is an open-source platform designed to automate the deployment, scaling, and management of containerized applications. The core premise of Kubernetes revolves around the principles of predictability, scalability, and high availability, aligning perfectly with its standing as the best tool for orchestrating and managing containerized applications.
Why I Picked Kubernetes:
I picked Kubernetes as part of this list after considering its broad adoption in the industry and its capabilities in terms of application orchestration. What makes it distinct is its focus on automating deployment processes and managing the lifecycle of containerized applications, which makes it extremely efficient. For these reasons, I deemed Kubernetes as the top tool for managing and orchestrating containerized applications.
Standout features and integrations:
Kubernetes' standout features include its automatic bin packing, self-healing, horizontal scaling, and service discovery and load balancing. These features provide the foundation for the orchestration of containerized applications.
Kubernetes can also be integrated with various cloud providers like Google Cloud, AWS, and Azure, which further extends its capabilities.
Pros and cons
Pros:
- Compatible with various cloud providers
- Offers robust application orchestration capabilities
- Open-source and widely adopted
Cons:
- Error messages can be difficult to decipher
- Can be overkill for small applications
- Requires significant expertise to configure correctly
Ansible is an open-source software provisioning, configuration management, and application deployment tool. It utilizes a simple yet powerful language that allows you to describe your automation jobs in a way that approaches plain English.
Why I Picked Ansible:
I chose Ansible for this list for its simplicity and powerful capabilities in automating complex IT workflows. It sets itself apart with its agentless architecture, which means you don't have to install any other software on the nodes you're managing. Furthermore, Ansible is 'best for' automating deployment, scaling, and management of applications because of its straightforward playbook syntax, and it comes with a massive library of modules supporting various use cases.
Standout features and integrations:
Ansible’s standout features include its agentless architecture and idempotency - the concept that operations can be repeated or retried as often as necessary without affecting the outcome. The tool's ad-hoc command execution allows you to execute simple tasks instantly. As for integrations, Ansible plays well with other major IaC tools and can work seamlessly with cloud platforms like AWS, GCP, and Azure, among others.
Pros and cons
Pros:
- Agentless, no extra software required on servers
- Massive library of modules for diverse use cases
- Simple, human-readable syntax
Cons:
- Learning curve can be steep for non-programmers
- Debugging can be complex
- Less suited for managing large server fleets
Jenkins is a widely-used open-source automation server that facilitates continuous integration and continuous delivery in software projects. It allows developers to integrate changes to projects more efficiently, thereby aligning perfectly with the 'best for' statement of quickly finding issues in project changes.
Why I Picked Jenkins:
I selected Jenkins for its reputation as a stalwart in the CI/CD field. Its robustness in managing complex pipelines and flexibility through numerous plugins gives it a distinct edge. Furthermore, I determined Jenkins to be the best tool for easily integrating project changes and finding issues swiftly due to its well-established use in many development environments.
Standout features and integrations:
Jenkins excels in pipeline management, offering both declarative and scripted pipelines. It also provides a multitude of plugins to extend its capabilities.
The tool integrates well with a plethora of development, testing, and deployment technologies, including but not limited to Git, Docker, and Kubernetes. This makes it a versatile tool in any DevOps toolbox.
Pros and cons
Pros:
- Integrates well with a range of development, testing, and deployment tools
- Provides numerous plugins to extend functionality
- Excellent for managing complex pipelines
Cons:
- Requires careful maintenance, especially when using numerous plugins
- The interface may not be as modern or user-friendly as some other tools
- Could be complicated for beginners to set up and configure
Other IAC Tools
Below is a list of additional IAC tools I shortlisted but did not make it to the top 10. Definitely worth checking them out.
- Puppet
For IT automation management, enabling you to manage infrastructure as code
- Octopus Deploy
For automating deployment of ASP.NET applications, Java
- Cloudify
Good for orchestrating complex network functions
- HashiCorp Nomad
Good for flexible workload orchestration with easy deployment
- Serverless Framework
Good for simplifying building and deploying serverless applications
- Spinnaker
Good for multi-cloud continuous delivery and powerful pipeline management
- Pulumi
Good for infrastructure as code across any cloud using familiar languages
- AWS Elastic Beanstalk
Good for developers seeking a quick, simple deployment for cloud applications
- BOSH
Good for lifecycle management of large-scale distributed services
- CFengine
Good for lightweight configuration management at large scale
- Juju
Good for model-driven cloud-native application management
- Heat (OpenStack)
Good for orchestrating composite cloud applications using templates
Selection Criteria For IAC Tools
In software deployment and infrastructure management, I've evaluated and tested dozens of tools, striving to find those that truly stand out in terms of core functionality, key features, and usability. Each tool I've selected for this list has undergone rigorous scrutiny to ensure it provides substantial value in these critical areas.
Core Functionality
A software deployment and infrastructure management tool should enable you to:
- Deploy applications and services across different environments
- Automate repetitive tasks and processes
- Manage and orchestrate complex systems and network functions
- Provide capabilities for configuration management
Key Features
The following features are critical to effective software deployment and infrastructure management:
- Multi-Cloud Support: The tool should be able to work with multiple cloud providers. This is important for organizations that leverage multiple cloud platforms for their operations.
- Scalability: As your operations grow, the tool should be able to handle an increasing load and adapt to larger systems.
- Security: Given the sensitive nature of deployment and infrastructure, robust security features are critical to protect your data and systems.
- Integration Capabilities: The tool should be able to integrate with other tools you use, such as CI/CD tools, version control systems, monitoring tools, and more.
Usability
For a software deployment and infrastructure management tool, usability factors that matter include:
- Clear and Intuitive Interface: These tools often deal with complex systems, so it's important for the interface to present information in a clear and digestible way. A cluttered or confusing interface can lead to errors and inefficiencies.
- Documentation and Support: Given the complex nature of these tools, strong documentation is vital. It should be easy for new users to get up to speed and for experienced users to find information on more advanced topics.
- Ease of Configuration: Setting up and configuring the tool to match your specific requirements should be straightforward. It's a bonus if the tool provides a simple graphical interface or easy-to-use scripting options for configuration.
People Also Ask
What are the benefits of using Infrastructure as Code (IaC) tools?
There are several key benefits to using IaC tools, such as:
- Automating repetitive tasks: IaC allows for the automation of building, deploying, and managing infrastructure, which can significantly reduce human error and increase efficiency.
- Consistency and reliability: With IaC, you can ensure that your environments are provisioned consistently, which increases reliability and reduces troubleshooting time.
- Version Control: Just like with code, you can track changes to your infrastructure, see who made changes, and even revert back to previous states if necessary.
- Improved collaboration: IaC allows developers and operations to work together more closely, as changes can be reviewed and approved in the same way as code changes.
- Scalability: IaC makes it easy to scale your infrastructure up or down, depending on your current needs.
How much do IaC tools typically cost?
Pricing for IaC tools can vary greatly depending on the features, scale, and provider. Some tools offer a free tier or open-source version, while others may charge based on the number of resources managed, the size of the infrastructure, or on a per-user basis.
What are the typical pricing models for IaC tools?
The pricing models for IaC tools can be quite varied. Some operate on a subscription basis, typically charged monthly or annually. Others use a consumption-based model where you pay for what you use, often calculated on the number of resources or nodes managed.
What is the typical range of pricing for IaC tools?
The price of IaC tools can range anywhere from free for basic or open-source tools to several hundred dollars per month for enterprise-level solutions.
What are some of the cheapest and most expensive IaC tools?
While pricing can fluctuate and depends on the specific needs of your organization, tools like Terraform and Ansible offer free tiers or are open-source and can be considered among the more affordable options. On the other hand, enterprise-grade solutions like AWS CloudFormation or Azure Resource Manager can be quite expensive, particularly for large-scale deployments.
Are there any free IaC tool options?
Yes, there are several free options available. Terraform and Ansible, for example, are open-source tools and can be used for free. Similarly, Chef and Puppet also offer free tiers. However, keep in mind that while these tools may be free to use, there may still be costs associated with the resources they manage, such as cloud services.
Other IAC Tools Reviews
Summary
In conclusion, Infrastructure as Code (IaC) tools are indispensable for any organization looking to automate and streamline the process of infrastructure management. They aid in maintaining consistency, reducing human error, and fostering better collaboration among teams.
- Understand your needs: One of the key takeaways from this guide is the importance of understanding your specific needs before choosing an IaC tool. Different tools excel in different areas, and the "best" tool for your organization will be the one that best aligns with your specific use case. Be clear about your requirements and select the tool that best addresses those needs.
- Consider pricing and scalability: Cost is a significant factor in any buying decision. Many IaC tools offer a range of pricing options, from free tiers to enterprise-level plans. However, also consider scalability. You want a tool that fits not just your current needs but also can scale as your organization grows.
- Assess usability and support: Finally, take into account the usability of the tool and the support provided. A tool with an intuitive interface and robust customer support will make your IaC journey smoother and more successful. Consider factors such as onboarding, user experience, and the availability of resources like documentation or community support when choosing your IaC tool.
What Do You Think?
Absolutely, this field is vast and ever-evolving, and it's possible that there are other great Infrastructure as Code tools out there that I may have missed. So, I encourage you, dear readers, to share your experiences and recommendations in the comments below.
If you've found a tool that works particularly well for your use case, I would love to hear about it. After all, the best advice often comes from those in the trenches, using these tools day in and day out. So, don't hesitate to share - your insights could help others find the perfect tool for their needs.