Docker vs Packer

Overview

Docker

Stacks194.2K

Followers143.8K

Votes3.9K

Packer

Stacks573

Followers566

Votes41

Docker vs Packer: What are the differences?

Introduction

Docker and Packer are both popular tools used in software development and deployment, but they serve different purposes and have distinct features. In this article, we will explore the key differences between Docker and Packer.

Architecture and Purpose: Docker is a containerization platform that allows developers to package their applications and their dependencies into lightweight, portable containers. These containers can be run on any operating system with Docker installed, providing a consistent runtime environment. On the other hand, Packer is an open-source tool for creating machine images across multiple platforms. It allows you to automate the process of building images for different virtualization providers like Amazon EC2, Google Compute Engine, and more.
Build Process: In Docker, the build process involves creating a Dockerfile, which is a text file that contains a set of instructions for building a Docker image. These instructions define the base image, dependencies, environment variables, and other configurations needed for the application. Packer, on the other hand, uses a JSON template to define the build process. This template specifies the builders (e.g., AWS, Azure, VirtualBox) and the source image, along with any provisioning steps required.
Image Types: Docker builds and runs application containers, which are lightweight and efficient. These containers are isolated from the host system and can be easily deployed and scaled. Packer, on the other hand, builds machine images that can be used to create new instances (e.g., virtual machines) on various platforms. These images are typically larger and contain the entire operating system, software dependencies, and configurations.
Orchestration: Docker provides built-in orchestration capabilities through Docker Swarm or Kubernetes, allowing you to manage and scale containers across multiple machines. It also offers a centralized container registry (Docker Hub) for sharing and distributing Docker images. Packer, on the other hand, focuses on the creation of machine images and does not provide built-in orchestration. However, you can integrate Packer with other orchestration tools like Terraform or Ansible to automate the deployment and management of infrastructure.
Use Cases: Docker is widely used in applications that require fast, consistent, and isolated deployments, such as microservices architectures or containerized development environments. It is commonly used in DevOps environments for continuous integration and continuous deployment (CI/CD). Packer, on the other hand, is primarily used for infrastructure automation and image creation. It is useful for provisioning new instances in cloud environments or creating virtual machines for development and testing.
Security and Isolation: Docker provides built-in security features like container isolation, resource limitations, and user namespaces to protect the host system and other containers. It also allows you to use custom security profiles and policies. Packer, on the other hand, focuses on creating images and does not provide built-in isolation features. However, you can use configuration management tools like Chef or Puppet in combination with Packer to apply security configurations and harden the machine images.

In summary, Docker and Packer are both powerful tools for software development and infrastructure automation. Docker is primarily focused on containerization and running applications, while Packer is specialized in image creation for various platforms. While Docker is commonly used for lightweight deployments, Packer is more suited for infrastructure automation and provisioning new instances.

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Advice on Docker, Packer

Florian

IT DevOp at Agitos GmbH

Oct 22, 2019

Decided

lxd/lxc and Docker aren't congruent so this comparison needs a more detailed look; but in short I can say: the lxd-integrated administration of storage including zfs with its snapshot capabilities as well as the system container (multi-process) approach of lxc vs. the limited single-process container approach of Docker is the main reason I chose lxd over Docker.

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Detailed Comparison

Docker	Packer
The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere	Packer automates the creation of any type of machine image. It embraces modern configuration management by encouraging you to use automated scripts to install and configure the software within your Packer-made images.
Integrated developer tools; open, portable images; shareable, reusable apps; framework-aware builds; standardized templates; multi-environment support; remote registry management; simple setup for Docker and Kubernetes; certified Kubernetes; application templates; enterprise controls; secure software supply chain; industry-leading container runtime; image scanning; access controls; image signing; caching and mirroring; image lifecycle; policy-based image promotion	Super fast infrastructure deployment. Packer images allow you to launch completely provisioned and configured machines in seconds, rather than several minutes or hours.;Multi-provider portability. Because Packer creates identical images for multiple platforms, you can run production in AWS, staging/QA in a private cloud like OpenStack, and development in desktop virtualization solutions such as VMware or VirtualBox.;Improved stability. Packer installs and configures all the software for a machine at the time the image is built. If there are bugs in these scripts, they'll be caught early, rather than several minutes after a machine is launched.;Greater testability. After a machine image is built, that machine image can be quickly launched and smoke tested to verify that things appear to be working. If they are, you can be confident that any other machines launched from that image will function properly.
Statistics
Stacks 194.2K	Stacks 573
Followers 143.8K	Followers 566
Votes 3.9K	Votes 41
Pros & Cons
Pros 823 Rapid integration and build up 692 Isolation 521 Open source 505 Testability and reproducibility 460 Lightweight Cons 8 New versions == broken features 6 Unreliable networking 6 Documentation not always in sync 4 Moves quickly 3 Not Secure	Pros 27 Cross platform builds 8 Vm creation automation 4 Bake in security 1 Good documentation 1 Easy to use
Integrations
Java Docker Compose VirtualBox Linux Amazon EC2 Container Service Docker Swarm boot2docker Kubernetes Docker Machine Vagrant	Amazon EC2 DigitalOcean Google Compute Engine OpenStack VirtualBox

What are some alternatives to Docker, Packer?

AWS CloudFormation

You can use AWS CloudFormation’s sample templates or create your own templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run your application. You don’t need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.

LXD

LXD isn't a rewrite of LXC, in fact it's building on top of LXC to provide a new, better user experience. Under the hood, LXD uses LXC through liblxc and its Go binding to create and manage the containers. It's basically an alternative to LXC's tools and distribution template system with the added features that come from being controllable over the network.

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

Pulumi

Pulumi is a cloud development platform that makes creating cloud programs easy and productive. Skip the YAML and just write code. Pulumi is multi-language, multi-cloud and fully extensible in both its engine and ecosystem of packages.

LXC

LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers.

Azure Resource Manager

It is the deployment and management service for Azure. It provides a management layer that enables you to create, update, and delete resources in your Azure subscription. You use management features, like access control, locks, and tags, to secure and organize your resources after deployment.

rkt

Rocket is a cli for running App Containers. The goal of rocket is to be composable, secure, and fast.

Habitat

Habitat is a new approach to automation that focuses on the application instead of the infrastructure it runs on. With Habitat, the apps you build, deploy, and manage behave consistently in any runtime — metal, VMs, containers, and PaaS. You'll spend less time on the environment and more time building features.

Google Cloud Deployment Manager

Google Cloud Deployment Manager allows you to specify all the resources needed for your application in a declarative format using yaml.

Vagrant Cloud

Vagrant Cloud pairs with Vagrant to enable access, insight and collaboration across teams, as well as to bring exposure to community contributions and development environments.

Related Comparisons

Docker vs Packer: What are the differences?

Introduction

Architecture and Purpose: Docker is a containerization platform that allows developers to package their applications and their dependencies into lightweight, portable containers. These containers can be run on any operating system with Docker installed, providing a consistent runtime environment. On the other hand, Packer is an open-source tool for creating machine images across multiple platforms. It allows you to automate the process of building images for different virtualization providers like Amazon EC2, Google Compute Engine, and more.
Build Process: In Docker, the build process involves creating a Dockerfile, which is a text file that contains a set of instructions for building a Docker image. These instructions define the base image, dependencies, environment variables, and other configurations needed for the application. Packer, on the other hand, uses a JSON template to define the build process. This template specifies the builders (e.g., AWS, Azure, VirtualBox) and the source image, along with any provisioning steps required.
Image Types: Docker builds and runs application containers, which are lightweight and efficient. These containers are isolated from the host system and can be easily deployed and scaled. Packer, on the other hand, builds machine images that can be used to create new instances (e.g., virtual machines) on various platforms. These images are typically larger and contain the entire operating system, software dependencies, and configurations.
Orchestration: Docker provides built-in orchestration capabilities through Docker Swarm or Kubernetes, allowing you to manage and scale containers across multiple machines. It also offers a centralized container registry (Docker Hub) for sharing and distributing Docker images. Packer, on the other hand, focuses on the creation of machine images and does not provide built-in orchestration. However, you can integrate Packer with other orchestration tools like Terraform or Ansible to automate the deployment and management of infrastructure.
Use Cases: Docker is widely used in applications that require fast, consistent, and isolated deployments, such as microservices architectures or containerized development environments. It is commonly used in DevOps environments for continuous integration and continuous deployment (CI/CD). Packer, on the other hand, is primarily used for infrastructure automation and image creation. It is useful for provisioning new instances in cloud environments or creating virtual machines for development and testing.
Security and Isolation: Docker provides built-in security features like container isolation, resource limitations, and user namespaces to protect the host system and other containers. It also allows you to use custom security profiles and policies. Packer, on the other hand, focuses on creating images and does not provide built-in isolation features. However, you can use configuration management tools like Chef or Puppet in combination with Packer to apply security configurations and harden the machine images.

Docker vs Packer

Overview

Docker vs Packer: What are the differences?