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AWS CodeDeploy vs Terraform: What are the differences?

Introduction

This markdown code provides a comparison between AWS CodeDeploy and Terraform, highlighting their key differences.

  1. Deployment Flexibility: AWS CodeDeploy is a fully managed deployment service that allows for deploying applications to various compute environments, such as EC2 instances, ECS containers, and Lambda functions. It provides built-in deployment features and supports both blue/green and in-place deployments. On the other hand, Terraform is an infrastructure as code tool that enables the provision and management of resources across multiple cloud platforms, including AWS. It focuses on automating infrastructure provisioning and configuration, but does not provide direct deployment capabilities like CodeDeploy.

  2. Declarative vs Procedural: CodeDeploy takes a declarative approach to deployments, meaning the desired end state is defined, and the service handles the necessary steps to reach that state. It allows for defining deployment configurations using YAML or JSON files. In contrast, Terraform uses a procedural approach where the infrastructure is described through "HCL" (HashiCorp Configuration Language) files. Terraform's configuration files define the series of steps required to provision and manage the desired infrastructure.

  3. Resource Management: CodeDeploy primarily focuses on the deployment and management of applications. It provides options for rolling back deployments, monitoring deployment status, and automating tasks during the deployment process. In comparison, Terraform has a broader scope and allows for managing a wide range of cloud resources beyond just deployments. It can provision and configure infrastructure components such as virtual machines, databases, networks, and more.

  4. Platform Independence: CodeDeploy is a service provided by AWS and is designed specifically for deploying applications on AWS infrastructure. It leverages other AWS services like Auto Scaling, CloudWatch, and Elastic Load Balancing to facilitate the deployment process. On the other hand, Terraform is a cloud-agnostic tool that supports multiple cloud providers, including AWS, Microsoft Azure, Google Cloud Platform, and others. It provides a consistent framework for provisioning and managing resources across different cloud environments.

  5. Integration with CI/CD Pipelines: CodeDeploy is often used as part of a comprehensive CI/CD (Continuous Integration/Continuous Deployment) pipeline. It integrates well with other AWS DevOps services like AWS CodeCommit, AWS CodePipeline, and AWS CodeBuild. CodeDeploy can be used to automate the deployment of application updates triggered by changes in the source code repository. In comparison, Terraform can also be used in CI/CD pipelines to automate infrastructure provisioning and configuration, but it does not have built-in features specifically tailored for deployment like CodeDeploy.

  6. Granularity of Control: CodeDeploy offers a higher level of abstraction when it comes to deployments, enabling users to define deployment groups, deployment configurations, and application revisions. It abstracts away some of the low-level details of the deployment process, making it easier and quicker to set up deployments. In contrast, Terraform provides fine-grained control over infrastructure provisioning and configuration. Users can define specific resource attributes, dependencies, and relationships, giving them more control and flexibility but potentially requiring more time and effort to set up.

In summary, AWS CodeDeploy is a managed deployment service focused on application deployment to various compute environments, while Terraform is an infrastructure as code tool that automates provisioning and management of cloud resources. CodeDeploy offers deployment flexibility and integration with CI/CD pipelines, while Terraform provides capabilities for managing a broader range of resources, platform independence, and fine-grained control over infrastructure configuration.

Decisions about AWS CodeDeploy and Terraform

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.

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Sergey Ivanov
Overview

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.

Advantages

Terraform 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.

Disadvantages

Software 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.

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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.
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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

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Pros of AWS CodeDeploy
Pros of Terraform
  • 17
    Automates code deployments
  • 9
    Backed by Amazon
  • 7
    Adds autoscaling lifecycle hooks
  • 5
    Git integration
  • 122
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
  • 8
    Well-documented
  • 8
    Cloud agnostic
  • 6
    It's like coding your infrastructure in simple English
  • 6
    Immutable infrastructure
  • 5
    Platform agnostic
  • 4
    Extendable
  • 4
    Automation
  • 4
    Automates infrastructure deployments
  • 4
    Portability
  • 2
    Lightweight
  • 2
    Scales to hundreds of hosts

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Cons of AWS CodeDeploy
Cons of Terraform
    Be the first to leave a con
    • 1
      Doesn't have full support to GKE

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