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Docker Compose vs Terraform: What are the differences?
Docker Compose and Terraform are two popular tools used in the field of DevOps and infrastructure management. Let's explore the key differences between them.
Ease of Use: Docker Compose is primarily used for managing and deploying Docker containers, providing a simple way to define and run multi-container applications. It focuses on managing containers and the services they provide. On the other hand, Terraform is a more comprehensive infrastructure provisioning tool that allows users to automate the setup and configuration of various cloud services and resources. It is used to manage infrastructure as code and handle the entire lifecycle of resources.
Scope: Docker Compose has a narrower scope compared to Terraform. It primarily focuses on simplifying the deployment and management of containers within a single host system or cluster. It provides an easy way to define and link multiple containers within a single application. In contrast, Terraform has a broader scope and can be used to define and manage infrastructure resources across multiple cloud providers and services.
Infrastructure Provisioning: Docker Compose does not have built-in capabilities for provisioning infrastructure resources. It primarily focuses on containerization and application deployment aspects. Terraform, on the other hand, specializes in infrastructure provisioning and configuration management. It allows users to define and manage cloud resources such as virtual machines, storage, networking, and more.
Declarative vs Imperative: Docker Compose follows a declarative approach where users define the desired state of the application and let Docker Compose handle the provisioning and orchestration automatically. In contrast, Terraform follows an imperative approach, allowing users to explicitly define the steps and actions required to provision and configure resources.
Resource Type Support: Docker Compose primarily focuses on managing containers and their interconnections, providing functionality for services, networks, and volumes. It has limited support for other resource types. In comparison, Terraform supports a wide range of resource types across various cloud providers, including virtual machines, databases, serverless functions, DNS records, and more. This makes Terraform more suitable for managing complex infrastructure setups.
Community and Ecosystem: Docker Compose has a large and active community, primarily focused on containerization and application deployment. It benefits from the vast Docker ecosystem and integration with other Docker tools. Terraform also has a thriving community but is more diverse in terms of use cases since it can manage resources beyond containers. It integrates with various cloud providers and has a wide range of community-maintained provider plugins.
In summary, Docker Compose is a tool dedicated to managing and deploying containers, with a focus on simplicity and easy orchestration within a single host or cluster. On the other hand, Terraform is a comprehensive infrastructure provisioning tool that allows users to automate the setup of various cloud resources across multiple providers, going beyond containerization.
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 Compose
- Multi-container descriptor123
- Fast development environment setup110
- Easy linking of containers79
- Simple yaml configuration68
- Easy setup60
- Yml or yaml format16
- Use Standard Docker API12
- Open source8
- Go from template to application in minutes5
- Can choose Discovery Backend5
- Scalable4
- Easy configuration4
- Kubernetes integration4
- Quick and easy3
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
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Cons of Docker Compose
- Tied to single machine9
- Still very volatile, changing syntax often5
Cons of Terraform
- Doesn't have full support to GKE1
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What is Docker Compose?
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