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  1. Stackups
  2. DevOps
  3. Build Automation
  4. Infrastructure Build Tools
  5. Packer vs Pulumi

Packer vs Pulumi

OverviewDecisionsComparisonAlternatives

Overview

Packer
Packer
Stacks573
Followers566
Votes41
Pulumi
Pulumi
Stacks306
Followers293
Votes25
GitHub Stars24.1K
Forks1.3K

Packer vs Pulumi: What are the differences?

Key Differences between Packer and Pulumi

Packer and Pulumi are two popular DevOps tools used for infrastructure provisioning and management. While both tools can be used to automate infrastructure deployment, they have distinct differences. Here are the key differences between Packer and Pulumi:

  1. Functionality and Purpose: Packer is primarily used for creating machine images across multiple platforms, such as Amazon EC2, Google Compute Engine, and Docker. It focuses on building immutable infrastructure. On the other hand, Pulumi is a multi-language infrastructure as code platform that allows you to define, deploy, and manage cloud infrastructure using popular programming languages like TypeScript, Python, and Go.

  2. Language Support: Packer has its own configuration language called HashiCorp Configuration Language (HCL), which is used to describe infrastructure configurations as code. Pulumi, on the other hand, supports multiple programming languages like JavaScript, TypeScript, Python, Go, and .NET, giving you the flexibility to choose a language you are comfortable with.

  3. Declarative vs Imperative: Packer follows a more declarative approach, where you define the desired state of the infrastructure and Packer takes care of building the machine image accordingly. Pulumi, on the other hand, allows you to use imperative code to define and manage your infrastructure, giving you more control and flexibility in the provisioning process.

  4. Scope of Provisioning: Packer focuses on the creation of machine images and doesn't provide native support for continuous deployment or managing infrastructure resources. Pulumi, on the other hand, allows for provisioning and managing a wide range of cloud resources, including virtual machines, databases, networking components, and more.

  5. Vendor Support: Packer supports a wide range of cloud providers, including AWS, Azure, Google Cloud, and VMware, making it a popular choice for multi-cloud and hybrid cloud environments. Pulumi also supports various cloud providers, but it also offers some specific components and integrations for certain cloud platforms, like the AWS Cloud Development Kit (CDK) for easier AWS resource provisioning.

  6. Community and Ecosystem: Packer has a large and mature community with extensive documentation, plugins, and integrations developed by the community. Pulumi is relatively newer but has been gaining popularity with its active community and an ecosystem of libraries and examples developed by the team and the community.

In summary, Packer focuses on building machine images across multiple platforms and follows a more declarative approach, while Pulumi is a multi-language infrastructure as code platform that allows for provisioning and managing cloud resources using imperative code. Packer has its own configuration language (HCL), while Pulumi supports multiple programming languages. Pulumi offers a wider scope of provisionable resources and has specific and deeper integrations with certain cloud platforms, while Packer supports a wide range of cloud providers. Packer has a larger and more mature community, while Pulumi is gaining popularity with its active community and expanding ecosystem.

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Advice on Packer, Pulumi

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
Sergey
Sergey

Contractor at Adaptive

Apr 17, 2020

Decided

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.

426k views426k
Comments

Detailed Comparison

Packer
Packer
Pulumi
Pulumi

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.

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.

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.
Containers - Deploy a Docker container to production in 5 minutes using your favorite orchestrator.; Serverless - Stand up a serverless API or event handler in 5 minutes using a real lambda in code.; Infrastructure - Manage cloud infrastructure or hosted services using infrastructure as code.; CoLaDa - Embrace containers, lambdas, and data, using a modern, multi-cloud framework.
Statistics
GitHub Stars
-
GitHub Stars
24.1K
GitHub Forks
-
GitHub Forks
1.3K
Stacks
573
Stacks
306
Followers
566
Followers
293
Votes
41
Votes
25
Pros & Cons
Pros
  • 27
    Cross platform builds
  • 8
    Vm creation automation
  • 4
    Bake in security
  • 1
    Easy to use
  • 1
    Good documentation
Pros
  • 8
    Infrastructure as code with less pain
  • 4
    Best-in-class kubernetes support
  • 3
    Simple
  • 3
    Can use many languages
  • 2
    Can be self-hosted
Integrations
Amazon EC2
Amazon EC2
DigitalOcean
DigitalOcean
Docker
Docker
Google Compute Engine
Google Compute Engine
OpenStack
OpenStack
VirtualBox
VirtualBox
No integrations available

What are some alternatives to Packer, Pulumi?

AWS CloudFormation

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.

Scalr

Scalr

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

Azure Resource Manager

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.

Habitat

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

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

AWS Cloud Development Kit

AWS Cloud Development Kit

It is an open source software development framework to model and provision your cloud application resources using familiar programming languages. It uses the familiarity and expressive power of programming languages for modeling your applications. It provides you with high-level components that preconfigure cloud resources with proven defaults, so you can build cloud applications without needing to be an expert.

Yocto

Yocto

It is an open source collaboration project that helps developers create custom Linux-based systems regardless of the hardware architecture. It provides a flexible set of tools and a space where embedded developers worldwide can share technologies, software stacks, configurations, and best practices that can be used to create tailored Linux images for embedded and IOT devices, or anywhere a customized Linux OS is needed.

GeoEngineer

GeoEngineer

GeoEngineer uses Terraform to plan and execute changes, so the DSL to describe resources is similar to Terraform's. GeoEngineer's DSL also provides programming and object oriented features like inheritance, abstraction, branching and looping.

Atlas

Atlas

Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.

Buildroot

Buildroot

It is a tool that simplifies and automates the process of building a complete Linux system for an embedded system, using cross-compilation.

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