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AWS CLI vs Terraform: What are the differences?
Key Differences between AWS CLI and Terraform
AWS CLI and Terraform are two popular tools used in the realm of cloud computing. While both tools serve as command-line interfaces for managing cloud resources, there are several key differences between them.
Language and Approach: AWS CLI is written in Python and provides a simple command-line interface to interact with AWS services. On the other hand, Terraform is a declarative language that uses HashiCorp Configuration Language (HCL) to define and provision infrastructure resources. The difference in language and approach gives Terraform the ability to manage resources across different cloud providers.
Resource Provisioning: AWS CLI mainly focuses on provisioning AWS resources. It allows users to create, modify, and delete resources using specific commands and parameters. In contrast, Terraform provides a more powerful and holistic approach to provisioning resources. It uses configuration files to define infrastructure as code, enabling users to manage resources across multiple cloud providers, including AWS.
State Management: AWS CLI does not explicitly manage state, requiring manual tracking of resource configurations and changes. When a resource is provisioned or modified, the developer needs to track and maintain the state manually. Terraform, on the other hand, maintains a state file that keeps track of the resources it provisions. This state file allows Terraform to plan, update, and destroy resources more efficiently.
Infrastructure as Code: While AWS CLI allows users to create scripts, it is primarily focused on managing resources individually. Terraform, with its infrastructure as code approach, enables users to treat their infrastructure as a whole. By defining and versioning infrastructure configurations, Terraform allows for repeatable and consistent deployments, as well as collaborative development of infrastructure code.
Ease of Use: AWS CLI provides a straightforward command-line interface that requires users to memorize specific commands and parameters for managing resources. Terraform, on the other hand, requires users to learn the HCL syntax and follow the Terraform workflow for managing infrastructure. The learning curve for Terraform can be steeper initially but provides a more powerful and scalable solution for managing complex infrastructure.
Community Support and Ecosystem: AWS CLI benefits from being an Amazon Web Services product, with a large community and extensive documentation. It is widely adopted and has a vast ecosystem of plugins and tools. Terraform, although not specific to AWS, also has a vibrant community with support for multiple cloud providers. It offers numerous community-contributed modules and a rich ecosystem that allows users to share and reuse infrastructure code.
In summary, AWS CLI and Terraform differ in their programming languages, resource provisioning approaches, state management capabilities, infrastructure as code philosophies, ease of use, and community support. Terraform's focus on infrastructure as code and its ability to manage resources across different cloud providers sets it apart as a more flexible and scalable option for managing complex infrastructures.
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 AWS CLI
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 AWS CLI
Cons of Terraform
- Doesn't have full support to GKE1
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