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  1. Stackups
  2. DevOps
  3. Continuous Deployment
  4. Server Configuration And Automation
  5. AWS CodeDeploy vs Terraform

AWS CodeDeploy vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K
AWS CodeDeploy
AWS CodeDeploy
Stacks380
Followers624
Votes38

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.

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Advice on Terraform, AWS CodeDeploy

Sung Won
Sung Won

Nov 4, 2019

DecidedonGoogle Cloud IoT CoreGoogle Cloud IoT CoreTerraformTerraformPythonPython

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

2.25M views2.25M
Comments
Timothy
Timothy

SRE

Mar 20, 2020

Decided

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.
385k views385k
Comments
Daniel
Daniel

May 4, 2020

Decided

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.

426k views426k
Comments

Detailed Comparison

Terraform
Terraform
AWS CodeDeploy
AWS CodeDeploy

With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel.

AWS CodeDeploy is a service that automates code deployments to Amazon EC2 instances. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during deployment, and handles the complexity of updating your applications.

Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.;Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.;Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.;Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors
AWS CodeDeploy fully automates your code deployments, allowing you to deploy reliably and rapidly;AWS CodeDeploy helps maximize your application availability by performing rolling updates across your Amazon EC2 instances and tracking application health according to configurable rules;AWS CodeDeploy allows you to easily launch and track the status of your deployments through the AWS Management Console or the AWS CLI;AWS CodeDeploy is platform and language agnostic and works with any application. You can easily reuse your existing setup code
Statistics
GitHub Stars
47.0K
GitHub Stars
-
GitHub Forks
10.1K
GitHub Forks
-
Stacks
22.9K
Stacks
380
Followers
14.7K
Followers
624
Votes
344
Votes
38
Pros & Cons
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Pros
  • 17
    Automates code deployments
  • 9
    Backed by Amazon
  • 7
    Adds autoscaling lifecycle hooks
  • 5
    Git integration
Integrations
Heroku
Heroku
Amazon EC2
Amazon EC2
CloudFlare
CloudFlare
DNSimple
DNSimple
Microsoft Azure
Microsoft Azure
Consul
Consul
Equinix Metal
Equinix Metal
DigitalOcean
DigitalOcean
OpenStack
OpenStack
Google Compute Engine
Google Compute Engine
CircleCI
CircleCI
Codeship
Codeship
GitHub
GitHub
Jenkins
Jenkins
Solano CI
Solano CI
Travis CI
Travis CI
Amazon EC2
Amazon EC2
Ansible
Ansible
Chef
Chef
Puppet Labs
Puppet Labs

What are some alternatives to Terraform, AWS CodeDeploy?

Ansible

Ansible

Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.

Chef

Chef

Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others.

Capistrano

Capistrano

Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows.

Puppet Labs

Puppet Labs

Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.

Salt

Salt

Salt is a new approach to infrastructure management. Easy enough to get running in minutes, scalable enough to manage tens of thousands of servers, and fast enough to communicate with them in seconds. Salt delivers a dynamic communication bus for infrastructures that can be used for orchestration, remote execution, configuration management and much more.

Octopus Deploy

Octopus Deploy

Octopus Deploy helps teams to manage releases, automate deployments, and operate applications with automated runbooks. It's free for small teams.

Fabric

Fabric

Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution.

AWS OpsWorks

AWS OpsWorks

Start from templates for common technologies like Ruby, Node.JS, PHP, and Java, or build your own using Chef recipes to install software packages and perform any task that you can script. AWS OpsWorks can scale your application using automatic load-based or time-based scaling and maintain the health of your application by detecting failed instances and replacing them. You have full control of deployments and automation of each component

Distelli

Distelli

Build, test, and deploy your code from GitHub and BitBucket (or no repository at all) to any server in the world regardless of provider. Distelli customers iterate and ship faster with complete transparency.

cPanel

cPanel

It is an industry leading hosting platform with world-class support. It is globally empowering hosting providers through fully-automated point-and-click hosting platform by hosting-centric professionals

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