Ansible vs Packer

Overview

Ansible

Stacks19.5K

Followers15.6K

Votes1.3K

GitHub Stars66.9K

Forks24.1K

Packer

Stacks573

Followers566

Votes41

Ansible vs Packer: What are the differences?

Ansible and Packer are both widely used tools in the world of DevOps and infrastructure automation. Let's explore the key differences between them.

Provisioning vs Configuration Management: Packer is primarily used for creating machine images or artifacts, allowing users to quickly provision new instances with pre-configured software and settings. On the other hand, Ansible is primarily a configuration management tool, used to automate the setup and maintenance of software and systems on existing instances.
Image vs Agent-based: Packer creates self-contained machine images, which can be directly deployed onto cloud platforms or virtualization systems. These images contain the necessary software and configurations to run applications without the need for a separate agent. In contrast, Ansible is agentless and operates by executing tasks remotely on target systems using SSH or WinRM, making it more suitable for managing existing instances.
Language and Configuration: Packer uses a configuration language called HashiCorp Configuration Language (HCL) or JSON, allowing users to define the image creation process, including the base image, provisioners, and post-processing steps. On the other hand, Ansible uses a declarative language called YAML, which allows users to describe the desired state of systems and specify tasks to bring them into that state.
Domain-specific vs General Purpose: Packer is specifically designed for creating machine images and focuses on system-level tasks like installing software, configuring settings, and performing disk optimizations. In contrast, Ansible is a more general-purpose tool that can be used for a wide range of automation tasks, including system configuration, application deployment, and orchestration of multi-tier infrastructures.
Parallelism and Dependency Management: Packer builds images in parallel, exploiting the available resources to minimize the time required to create the images. It also supports dependency management by allowing builders to be defined in stages, ensuring that the necessary components are built in the correct order. Ansible, on the other hand, performs tasks sequentially by default, but can be configured to run tasks in parallel. It also supports dependency management through its modular structure, allowing tasks to be executed in a specific order.
Community and Ecosystem: Both Ansible and Packer have vibrant communities and extensive ecosystems. Ansible has a large collection of pre-built roles and modules maintained by the community, making it easier to automate common tasks. Packer, on the other hand, provides builders and provisioners for various cloud platforms and virtualization technologies, enabling users to quickly create images for different environments.

In summary, Ansible is a powerful configuration management tool that operates on existing instances using an agentless approach, while Packer is primarily used for creating self-contained machine images.

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Advice on Ansible, Packer

Anonymous

Sep 17, 2019

Needs advice

I'm just getting started using Vagrant to help automate setting up local VMs to set up a Kubernetes cluster (development and experimentation only). (Yes, I do know about minikube)

I'm looking for a tool to help install software packages, setup users, etc..., on these VMs. I'm also fairly new to Ansible, Chef, and Puppet. What's a good one to start with to learn? I might decide to try all 3 at some point for my own curiosity.

The most important factors for me are simplicity, ease of use, shortest learning curve.

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Detailed Comparison

Ansible	Packer
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.	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.
Ansible's natural automation language allows sysadmins, developers, and IT managers to complete automation projects in hours, not weeks.;Ansible uses SSH by default instead of requiring agents everywhere. Avoid extra open ports, improve security, eliminate "managing the management", and reclaim CPU cycles.;Ansible automates app deployment, configuration management, workflow orchestration, and even cloud provisioning all from one system.	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
GitHub Stars 66.9K	GitHub Stars -
GitHub Forks 24.1K	GitHub Forks -
Stacks 19.5K	Stacks 573
Followers 15.6K	Followers 566
Votes 1.3K	Votes 41
Pros & Cons
Pros 284 Agentless 210 Great configuration 199 Simple 176 Powerful 155 Easy to learn Cons 8 Dangerous 5 Hard to install 3 Backward compatibility 3 Bloated 3 Doesn't Run on Windows	Pros 27 Cross platform builds 8 Vm creation automation 4 Bake in security 1 Easy to use 1 Good documentation
Integrations
Nexmo Stackdriver VMware vSphere Docker OpenStack Amazon EC2 Rackspace Cloud Servers Google Compute Engine New Relic PagerDuty	Amazon EC2 DigitalOcean Docker Google Compute Engine OpenStack VirtualBox

What are some alternatives to Ansible, Packer?

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.

Terraform

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.

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 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 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.

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.

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

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

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.

Related Comparisons

Ansible vs Packer: What are the differences?

Ansible and Packer are both widely used tools in the world of DevOps and infrastructure automation. Let's explore the key differences between them.

Provisioning vs Configuration Management: Packer is primarily used for creating machine images or artifacts, allowing users to quickly provision new instances with pre-configured software and settings. On the other hand, Ansible is primarily a configuration management tool, used to automate the setup and maintenance of software and systems on existing instances.
Image vs Agent-based: Packer creates self-contained machine images, which can be directly deployed onto cloud platforms or virtualization systems. These images contain the necessary software and configurations to run applications without the need for a separate agent. In contrast, Ansible is agentless and operates by executing tasks remotely on target systems using SSH or WinRM, making it more suitable for managing existing instances.
Language and Configuration: Packer uses a configuration language called HashiCorp Configuration Language (HCL) or JSON, allowing users to define the image creation process, including the base image, provisioners, and post-processing steps. On the other hand, Ansible uses a declarative language called YAML, which allows users to describe the desired state of systems and specify tasks to bring them into that state.
Domain-specific vs General Purpose: Packer is specifically designed for creating machine images and focuses on system-level tasks like installing software, configuring settings, and performing disk optimizations. In contrast, Ansible is a more general-purpose tool that can be used for a wide range of automation tasks, including system configuration, application deployment, and orchestration of multi-tier infrastructures.
Parallelism and Dependency Management: Packer builds images in parallel, exploiting the available resources to minimize the time required to create the images. It also supports dependency management by allowing builders to be defined in stages, ensuring that the necessary components are built in the correct order. Ansible, on the other hand, performs tasks sequentially by default, but can be configured to run tasks in parallel. It also supports dependency management through its modular structure, allowing tasks to be executed in a specific order.
Community and Ecosystem: Both Ansible and Packer have vibrant communities and extensive ecosystems. Ansible has a large collection of pre-built roles and modules maintained by the community, making it easier to automate common tasks. Packer, on the other hand, provides builders and provisioners for various cloud platforms and virtualization technologies, enabling users to quickly create images for different environments.

Ansible vs Packer

Overview