Need advice about which tool to choose?Ask the StackShare community!
AWS CloudFormation vs Packer: What are the differences?
Key Differences Between AWS CloudFormation and Packer
AWS CloudFormation and Packer are both widely used tools in the field of cloud computing, but they have key differences that distinguish them from each other. Here are the six main differences between AWS CloudFormation and Packer:
Deployment Approach: AWS CloudFormation is a service that allows you to provision and manage a collection of AWS resources in a repeatable and consistent way. It is used for infrastructure as code and focuses on creating and managing resources within AWS. In contrast, Packer is a tool for creating machine images across different platforms. It focuses on the creation and customization of images that can be used for deployments on various platforms.
Scope of Control: CloudFormation provides a higher level of control as it allows the creation, update, and deletion of infrastructure resources as a whole. It manages the entire lifecycle of a stack, including dependencies and resource management. On the other hand, Packer focuses solely on the creation of machine images and does not provide the same level of control over infrastructure resources.
Configurability: AWS CloudFormation provides extensive configuration options, allowing you to define resources, properties, dependencies, and outputs using a declarative JSON or YAML template. It offers a wide range of pre-defined resources that can be customized as per requirements. In contrast, Packer provides more flexibility when it comes to image creation and customization. It supports multiple provisioners, builders, and custom scripts to configure images.
Supported Cloud Providers: CloudFormation is exclusively designed for managing AWS resources and supports various AWS services. It integrates seamlessly with other AWS services, allowing you to create and manage resources across different services within the AWS ecosystem. Packer, on the other hand, is cloud-agnostic and supports multiple cloud providers. It allows image creation for platforms like AWS, Azure, Google Cloud, and more.
Image Types: CloudFormation primarily focuses on the creation and management of infrastructure resources, while Packer specializes in creating machine images. Packer supports the creation of different types of images, including machine images, containers, and virtual machine templates. This flexibility allows you to create images for various deployment scenarios, such as virtual machines for on-premises environments or container images for cloud-native applications.
Integration with CI/CD: AWS CloudFormation can integrate well with various CI/CD tools and processes. It enables you to streamline the infrastructure provisioning and management as part of your overall CI/CD pipeline. Packer, on the other hand, is often used as a building block within the CI/CD process. It provides the capability to create consistent and reproducible machine images, which can then be deployed using CI/CD tools.
In summary, AWS CloudFormation and Packer differ in their approach to deployment, scope of control, configurability, supported cloud providers, image types, and integration with CI/CD. While CloudFormation focuses on managing AWS resources and infrastructure using declarative templates, Packer specializes in the creation of machine images across multiple platforms.
Ok, so first - AWS Copilot is CloudFormation under the hood, but the way it works results in you not thinking about CFN anymore. AWS found the right balance with Copilot - it's insanely simple to setup production-ready multi-account environment with many services inside, with CI/CD out of the box etc etc. It's pretty new, but even now it was enough to launch Transcripto, which uses may be a dozen of different AWS services, all bound together by Copilot.
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.
Pros of AWS CloudFormation
- Automates infrastructure deployments43
- Declarative infrastructure and deployment21
- No more clicking around13
- Any Operative System you want3
- Atomic3
- Infrastructure as code3
- CDK makes it truly infrastructure-as-code1
- Automates Infrastructure Deployment1
- K8s0
Pros of Packer
- Cross platform builds27
- Vm creation automation9
- Bake in security4
- Good documentation1
- Easy to use1
Sign up to add or upvote prosMake informed product decisions
Cons of AWS CloudFormation
- Brittle4
- No RBAC and policies in templates2
Cons of Packer
Sign up to add or upvote consMake informed product decisions
What is AWS CloudFormation?
What is Packer?
Need advice about which tool to choose?Ask the StackShare community!
What companies use AWS CloudFormation?
What companies use Packer?
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with AWS CloudFormation?
What tools integrate with Packer?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+23
+29
+42+47
+26
+23
+39
+35