Alternatives to Azure Resource Manager logo

Alternatives to Azure Resource Manager

AWS CloudFormation, Terraform, PowerShell, Chef, and Kubernetes are the most popular alternatives and competitors to Azure Resource Manager.
31
65
+ 1
8

What is Azure Resource Manager and what are its top alternatives?

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.
Azure Resource Manager is a tool in the Infrastructure Build Tools category of a tech stack.

Top Alternatives to Azure Resource Manager

  • 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. ...

  • Terraform
    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. ...

  • PowerShell
    PowerShell

    A command-line shell and scripting language built on .NET. Helps system administrators and power-users rapidly automate tasks that manage operating systems (Linux, macOS, and Windows) and processes. ...

  • 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. ...

  • Kubernetes
    Kubernetes

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...

  • Packer
    Packer

    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
    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. ...

  • 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. ...

Azure Resource Manager alternatives & related posts

AWS CloudFormation logo

AWS CloudFormation

1.6K
1.2K
88
Create and manage a collection of related AWS resources
1.6K
1.2K
+ 1
88
PROS OF AWS CLOUDFORMATION
  • 43
    Automates infrastructure deployments
  • 21
    Declarative infrastructure and deployment
  • 13
    No more clicking around
  • 3
    Any Operative System you want
  • 3
    Infrastructure as code
  • 3
    Atomic
  • 1
    CDK makes it truly infrastructure-as-code
  • 1
    Automates Infrastructure Deployment
  • 0
    K8s
CONS OF AWS CLOUDFORMATION
  • 4
    Brittle
  • 2
    No RBAC and policies in templates

related AWS CloudFormation posts

Joseph Kunzler
DevOps Engineer at Tillable · | 9 upvotes · 152K views

We use Terraform because we needed a way to automate the process of building and deploying feature branches. We wanted to hide the complexity such that when a dev creates a PR, it triggers a build and deployment without the dev having to worry about any of the 'plumbing' going on behind the scenes. Terraform allows us to automate the process of provisioning DNS records, Amazon S3 buckets, Amazon EC2 instances and AWS Elastic Load Balancing (ELB)'s. It also makes it easy to tear it all down when finished. We also like that it supports multiple clouds, which is why we chose to use it over AWS CloudFormation.

See more

I use Terraform because it hits the level of abstraction pocket of being high-level and flexible, and is agnostic to cloud platforms. Creating complex infrastructure components for a solution with a UI console is tedious to repeat. Using low-level APIs are usually specific to cloud platforms, and you still have to build your own tooling for deploying, state management, and destroying infrastructure.

However, Terraform is usually slower to implement new services compared to cloud-specific APIs. It's worth the trade-off though, especially if you're multi-cloud. I heard someone say, "We want to preference a cloud, not lock in to one." Terraform builds on that claim.

Terraform Google Cloud Deployment Manager AWS CloudFormation

See more
Terraform logo

Terraform

15.1K
10K
327
Describe your complete infrastructure as code and build resources across providers
15.1K
10K
+ 1
327
PROS OF TERRAFORM
  • 113
    Infrastructure as code
  • 73
    Declarative syntax
  • 44
    Planning
  • 27
    Simple
  • 24
    Parallelism
  • 7
    Well-documented
  • 7
    Cloud agnostic
  • 6
    It's like coding your infrastructure in simple English
  • 5
    Platform agnostic
  • 4
    Immutable infrastructure
  • 4
    Automates infrastructure deployments
  • 3
    Automation
  • 3
    Extendable
  • 3
    Portability
  • 2
    Lightweight
  • 2
    Scales to hundreds of hosts
CONS OF TERRAFORM
  • 1
    Doesn't have full support to GKE

related Terraform posts

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

See more
Praveen Mooli
Engineering Manager at Taylor and Francis · | 17 upvotes · 2.3M views

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

See more
PowerShell logo

PowerShell

2.9K
804
0
A task automation and configuration management framework
2.9K
804
+ 1
0
PROS OF POWERSHELL
    Be the first to leave a pro
    CONS OF POWERSHELL
      Be the first to leave a con

      related PowerShell posts

      Shared insights
      on
      PowerShellPowerShellPythonPython

      I currently work helpdesk and have been for about 6 years. I am looking to become more valuable, and I can't decide what route to take? Python is of interest, and so is PowerShell. What are some recommendations? Maybe something that would benefit a helpdesk position or even get into a network administrator.

      See more

      Objective: I am trying to build a custom service that will create VMs in Azure, based on inputs taken from a web interface. I want the backend code that interacts with Azure to be PowerShell.

      Ask: Hoping to find help with deciding the simplest architecture of tools to achieve this.

      What I have so far with my Limited Knowledge: I am new to Azure and Jenkins. I arrived at Jenkins coz it can run PowerShell and has API that can be called to trigger a job. Although integrating with it over the web seems problematic since its on-prem network. I hear it is possible using the VPN. For the Web, I hope to use Azure Web App with Python/Node.js that I can manage to make API calls to Jenkins.

      Is there a better way? I just need help getting the right directions; I will walk the way.

      See more
      Chef logo

      Chef

      1.1K
      1K
      344
      Build, destroy and rebuild servers on any public or private cloud
      1.1K
      1K
      + 1
      344
      PROS OF CHEF
      • 109
        Dynamic and idempotent server configuration
      • 76
        Reusable components
      • 47
        Integration testing with Vagrant
      • 43
        Repeatable
      • 30
        Mock testing with Chefspec
      • 14
        Ruby
      • 8
        Can package cookbooks to guarantee repeatability
      • 7
        Works with AWS
      • 3
        Has marketplace where you get readymade cookbooks
      • 3
        Matured product with good community support
      • 2
        Less declarative more procedural
      • 2
        Open source configuration mgmt made easy(ish)
      CONS OF CHEF
        Be the first to leave a con

        related Chef posts

        In late 2013, the Operations Engineering team at PagerDuty was made up of 4 engineers, and was comprised of generalists, each of whom had one or two areas of depth. Although the Operations Team ran its own on-call, each engineering team at PagerDuty also participated on the pager.

        The Operations Engineering Team owned 150+ servers spanning multiple cloud providers, and used Chef to automate their infrastructure across the various cloud providers with a mix of completely custom cookbooks and customized community cookbooks.

        Custom cookbooks were managed by Berkshelf, andach custom cookbook contained its own tests based on ChefSpec 3, coupled with Rspec.

        Jenkins was used to GitHub for new changes and to handle unit testing of those features.

        See more
        Marcel Kornegoor

        Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.

        For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.

        For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.

        Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.

        See more
        Kubernetes logo

        Kubernetes

        44.3K
        38.1K
        634
        Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
        44.3K
        38.1K
        + 1
        634
        PROS OF KUBERNETES
        • 161
          Leading docker container management solution
        • 126
          Simple and powerful
        • 102
          Open source
        • 75
          Backed by google
        • 56
          The right abstractions
        • 24
          Scale services
        • 19
          Replication controller
        • 9
          Permission managment
        • 7
          Simple
        • 7
          Supports autoscaling
        • 6
          Cheap
        • 4
          Self-healing
        • 4
          No cloud platform lock-in
        • 4
          Reliable
        • 3
          Open, powerful, stable
        • 3
          Scalable
        • 3
          Quick cloud setup
        • 3
          Promotes modern/good infrascture practice
        • 2
          Backed by Red Hat
        • 2
          Cloud Agnostic
        • 2
          Runs on azure
        • 2
          Custom and extensibility
        • 2
          Captain of Container Ship
        • 2
          A self healing environment with rich metadata
        • 1
          Golang
        • 1
          Easy setup
        • 1
          Everything of CaaS
        • 1
          Sfg
        • 1
          Expandable
        • 1
          Gke
        CONS OF KUBERNETES
        • 14
          Poor workflow for development
        • 12
          Steep learning curve
        • 6
          Orchestrates only infrastructure
        • 3
          High resource requirements for on-prem clusters

        related Kubernetes posts

        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber · | 40 upvotes · 4.8M views

        How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

        Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

        Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

        https://eng.uber.com/distributed-tracing/

        (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

        Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

        See more
        Yshay Yaacobi

        Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

        Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

        After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

        See more
        Packer logo

        Packer

        540
        501
        42
        Create identical machine images for multiple platforms from a single source configuration
        540
        501
        + 1
        42
        PROS OF PACKER
        • 27
          Cross platform builds
        • 9
          Vm creation automation
        • 4
          Bake in security
        • 1
          Good documentation
        • 1
          Easy to use
        CONS OF PACKER
          Be the first to leave a con

          related Packer posts

          John Kodumal

          LaunchDarkly is almost a five year old company, and our methodology for deploying was state of the art... for 2014. We recently undertook a project to modernize the way we #deploy our software, moving from Ansible-based deploy scripts that executed on our local machines, to using Spinnaker (along with Terraform and Packer) as the basis of our deployment system. We've been using Armory's enterprise Spinnaker offering to make this project a reality.

          See more
          Pulumi logo

          Pulumi

          146
          228
          14
          Modern Infrastructure as Code
          146
          228
          + 1
          14
          PROS OF PULUMI
          • 5
            Infrastructure as code with less pain
          • 3
            Best-in-class kubernetes support
          • 1
            Can use many languages
          • 1
            Can be self-hosted
          • 1
            Built-in secret management
          • 1
            Simple
          • 1
            Multi-cloud
          • 1
            Great CLI
          CONS OF PULUMI
            Be the first to leave a con

            related Pulumi posts

            AWS Cloud Development Kit logo

            AWS Cloud Development Kit

            109
            56
            0
            A framework for defining cloud infrastructure in code
            109
            56
            + 1
            0
            PROS OF AWS CLOUD DEVELOPMENT KIT
              Be the first to leave a pro
              CONS OF AWS CLOUD DEVELOPMENT KIT
                Be the first to leave a con

                related AWS Cloud Development Kit posts