Need advice about which tool to choose?Ask the StackShare community!
Docker Machine vs Terraform: What are the differences?
Introduction
This Markdown document provides a comparison between Docker Machine and Terraform, outlining the key differences between these two tools. Docker Machine is a command-line tool used for provisioning and managing Docker hosts, while Terraform is an infrastructure as code tool designed for deploying and managing infrastructure across multiple service providers.
Docker Machine: Docker Machine is specifically focused on managing Docker hosts. It allows the user to create, provision, and manage Docker hosts on a variety of platforms, including local machines, cloud providers, and virtual machines. The primary advantage of Docker Machine is its ability to quickly and easily create and manage Docker hosts without having to manually install and configure Docker on each individual host. This makes it a convenient option for developers who want to quickly spin up Docker hosts for testing and development purposes.
Terraform: Terraform, on the other hand, is a more comprehensive infrastructure as code tool that allows users to define, provision, and manage infrastructure resources across a wide range of service providers. Unlike Docker Machine, which focuses solely on Docker hosts, Terraform supports a vast array of resources, including virtual machines, containers, storage, networks, and more. Terraform uses a declarative syntax to define the desired state of the infrastructure, which it then provisions and manages. This makes Terraform a powerful tool for managing infrastructure across multiple platforms and providers in a consistent and reproducible manner.
Resource Provisioning: When it comes to provisioning resources, Docker Machine primarily focuses on creating and managing Docker hosts. It provisions minimum necessary resources required to run Docker and sets up the Docker daemon. On the other hand, Terraform provides a more extensive set of resource provisioning capabilities. It supports creating and managing a wide range of resources, such as virtual machines, containers, storage, networks, load balancers, and more. This makes Terraform well-suited for managing complex infrastructure setups that go beyond just Docker hosts.
Provider Support: Docker Machine offers a variety of supported drivers, which are responsible for creating and managing Docker hosts on different platforms. These drivers include native drivers for platforms like VirtualBox and VMware, as well as cloud-specific drivers for platforms like AWS and Azure. In contrast, Terraform provides a vast ecosystem of providers that allow users to create and manage resources across different service providers, cloud platforms, and infrastructure technologies. This gives users more flexibility and choice when it comes to provisioning infrastructure resources.
Configuration Language: Docker Machine uses a command-line interface with specific flags and options to provision Docker hosts. While it does support some level of automation through scripts, the process of creating and managing Docker hosts is mainly done through command-line commands. On the other hand, Terraform uses its own configuration language called HashiCorp Configuration Language (HCL), which is a declarative language for describing infrastructure resources and their configurations. With HCL, users can define complex infrastructure setups, dependencies, and variables in a human-readable and version-controlled manner.
Scope and Use Cases: Due to its focused nature, Docker Machine is primarily used for managing Docker hosts on different platforms, making it ideal for developers and teams who primarily work with Docker containers. It simplifies the process of creating and managing Docker hosts, allowing developers to focus more on containerization. On the other hand, Terraform's broader scope and capabilities make it suitable for managing complex infrastructure setups that include various resources and service providers. It is often used by DevOps teams looking to manage infrastructure as code across multiple environments and platforms.
In summary, Docker Machine is a tool focused on quickly provisioning and managing Docker hosts on different platforms, while Terraform is an infrastructure as code tool that provides a wider range of resource provisioning capabilities and supports multiple service providers. Docker Machine simplifies the management of Docker hosts, while Terraform enables the management of complex infrastructure setups in a consistent and reproducible manner.
Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.
We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.
Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.
AdvantagesTerraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.
Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.
Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.
DisadvantagesSoftware is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.
Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.
Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.
I personally am not a huge fan of vendor lock in for multiple reasons:
- I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
- I've seen S3 failures nearly take down half the internet.
- I've seen companies get stuck in the cloud because they aren't built cloud agnostic.
I choose to use terraform for my cloud provisioning for these reasons:
- It's cloud agnostic so I can use it no matter where I am.
- It isn't difficult to use and uses a relatively easy to read language.
- It tests infrastructure before running it, and enables me to see and keep changes up to date.
- It runs from the same CLI I do most of my CM work from.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
Pros of Docker Machine
- Easy docker hosts management12
Pros of Terraform
- Infrastructure as code121
- Declarative syntax73
- Planning45
- Simple28
- Parallelism24
- Well-documented8
- Cloud agnostic8
- It's like coding your infrastructure in simple English6
- Immutable infrastructure6
- Platform agnostic5
- Extendable4
- Automation4
- Automates infrastructure deployments4
- Portability4
- Lightweight2
- Scales to hundreds of hosts2
Sign up to add or upvote prosMake informed product decisions
Cons of Docker Machine
Cons of Terraform
- Doesn't have full support to GKE1