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AWS CodeCommit vs Terraform: What are the differences?
Introduction
This Markdown code provides a comparison between AWS CodeCommit and Terraform, highlighting the key differences between the two.
Repository Hosting Service: AWS CodeCommit is a fully-managed source control service that enables developers to securely host private Git repositories. It provides built-in integrations with other AWS services, such as AWS CodeBuild and AWS CodePipeline. On the other hand, Terraform is an infrastructure as code tool that allows the provisioning and management of infrastructure resources across various cloud providers. It uses a declarative language to define infrastructure configurations.
Version Control System: CodeCommit uses the Git version control system, which is widely used and well-established in the software development community. Terraform, on the other hand, is not a version control system itself, but it can be used in conjunction with Git or other version control systems to manage infrastructure configurations as code.
Scalability: CodeCommit is a fully-managed service provided by AWS, which means it can automatically scale to handle increasing storage and user demands. It can handle repositories of any size and supports large file storage. Terraform, on the other hand, does not have inherent scalability features, as it relies on external version control systems for managing infrastructure configurations. However, Terraform can be used to provision and manage highly scalable cloud resources.
Compatibility: CodeCommit is specifically designed to work with other AWS services, providing seamless integration with the AWS ecosystem. It provides features like webhook triggers and integration with AWS Identity and Access Management (IAM). In contrast, Terraform is cloud provider-agnostic and can be used to manage infrastructure resources across multiple cloud platforms, including AWS, Azure, and Google Cloud Platform.
Workflow Automation: CodeCommit integrates well with AWS CodePipeline, allowing for the automation of end-to-end software release pipelines. It provides features like pull request reviews, automatic branch merging, and easy collaboration between developers. Terraform, on the other hand, focuses on provisioning and managing infrastructure resources and does not have built-in workflow automation features. However, it can be combined with other DevOps tools to create a complete deployment workflow.
Pricing Model: CodeCommit has a pay-as-you-go pricing model, where users are billed based on the number of active users and storage size for repositories. It provides a free tier for small projects. In contrast, Terraform is an open-source tool and does not have any direct costs associated with its usage. However, users still need to consider the costs of the underlying cloud resources provisioned by Terraform.
In summary, AWS CodeCommit is a managed source control service designed for secure hosting of Git repositories and seamless integration with the AWS ecosystem, while Terraform is an infrastructure as code tool that is cloud provider-agnostic and allows for the provisioning and management of infrastructure resources across multiple cloud platforms.
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 CodeCommit
- Free private repos44
- IAM integration26
- Pay-As-You-Go Pricing24
- Amazon feels the most Secure20
- Repo data encrypted at rest19
- I can make repository by myself if I have AWS account11
- Faster deployments when using other AWS services11
- AWS CodePipeline integration8
- Codebuild integration6
- Does not support web hooks yet! :(6
- Cost Effective4
- No Git LFS! Dealbreaker for me2
- Elastic Beanstalk Integration2
- Integrated with AWS Ecosystem2
- Integration via SQS/SNS for events (replaces webhooks)1
- IAM1
- Issue tracker1
- Available in Ireland (Dublin) region1
- CodeDeploy Integration1
- CodeCommit Trigger for an AWS Lambda Function1
- Open source friendly1
- Only US Region1
- Ui0
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 CodeCommit
- UI sucks12
- SLOW4
- No Issue Tracker3
- Bad diffing/no blame2
- NO LFS support2
- No fork2
- No webhooks2
- Can't download file from UI1
- Only time based triggers1
- Accident-prone UI0
Cons of Terraform
- Doesn't have full support to GKE1