Alternatives to RightScale logo

Alternatives to RightScale

Scalr, Cloudability, Terraform, CloudCheckr, and Morpheus are the most popular alternatives and competitors to RightScale.
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What is RightScale and what are its top alternatives?

Automation is the core of RightScale, freeing you to run efficient, scalable, and highly-available applications. Our multi-cloud integration enables you to choose your own clouds, providing freedom to work with any vendor in a rapidly changing market. And rest assured knowing that you have visibility and control over all of your resources in one place. To take advantage of best practices, we encourage you to tap into cloud expertise provided by our service, support, and partner networks when building and managing your infrastructure.
RightScale is a tool in the Cloud Management category of a tech stack.

Top Alternatives to RightScale

  • Scalr

    Scalr

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

  • Cloudability

    Cloudability

    Cloudability aggregates expenditures into accessible and comprehensive reports, helps identify new opportunities for reducing spend and increasing cloud efficiency, offers budget alerts and recommendations via SMS and email, provides APIs for connecting cloud billing and usage data to any business or financial system, and more. ...

  • 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. ...

  • CloudCheckr

    CloudCheckr

    CloudCheckr provides otherwise unavailable visibility and analytics to remove the complexity from AWS usage. Our users quickly and efficiently gain control of their deployment, reduce costs, and optimize infrastructure performance. ...

  • Morpheus

    Morpheus

    Morpheus is a cloud application management and orchestration platform that works on any cloud or infrastructure, from AWS to bare metal. Enjoy complete cloud freedom with Morpheus. ...

  • Ansible

    Ansible

    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. ...

  • CloudBolt

    CloudBolt

    Deploys in minutes. Simple to use. Easy to extend. Centralize workload automation and orchestration, achieve unparalleled hybrid cloud visibility and cost-savings, and deliver self-service IT for your developers. ...

  • MongoDB Cloud Manager

    MongoDB Cloud Manager

    It is a hosted platform for managing MongoDB on the infrastructure of your choice. It saves you time, money, and helps you protect your customer experience by eliminating the guesswork from running MongoDB. ...

RightScale alternatives & related posts

Scalr logo

Scalr

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Scalr is a remote state & operations backend for Terraform with access controls and policy as code
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PROS OF SCALR
  • 5
    Image Builder
  • 3
    Auto Scaling
  • 2
    Orchestration
  • 2
    Open Source
  • 2
    Multi-Cloud Support
  • 2
    Cost Analytics
  • 2
    Chef Integration
  • 2
    Hybrid Cloud Management
  • 2
    User Friendly
  • 1
    Terraform CLI Integration
  • 1
    Open Policy Agent
  • 1
    Cost
CONS OF SCALR
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    related Scalr posts

    Cloudability logo

    Cloudability

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    Cloud management made easy
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    PROS OF CLOUDABILITY
    • 5
      Cloud usage stats
    • 3
      Cloud cost monitoring
    • 2
      Track costs
    • 1
      Suggestions on which instances should be reserved
    • 0
      Ability to build dashboards (public or private)
    • 0
      Easy setup
    • 0
      Container friendly
    • 0
      Datadog and JIRA Integration
    • 0
      AWS, GCP, and Azure support
    CONS OF CLOUDABILITY
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      related Cloudability posts

      Terraform logo

      Terraform

      11.1K
      8.8K
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      Describe your complete infrastructure as code and build resources across providers
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      PROS OF TERRAFORM
      • 109
        Infrastructure as code
      • 73
        Declarative syntax
      • 44
        Planning
      • 27
        Simple
      • 24
        Parallelism
      • 7
        Cloud agnostic
      • 6
        It's like coding your infrastructure in simple English
      • 6
        Well-documented
      • 5
        Platform agnostic
      • 4
        Automates infrastructure deployments
      • 4
        Immutable infrastructure
      • 3
        Portability
      • 3
        Extendable
      • 3
        Automation
      • 2
        Scales to hundreds of hosts
      • 2
        Lightweight
      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
      Emanuel Evans
      Senior Architect at Rainforest QA · | 17 upvotes · 740K views

      We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

      We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

      Read the blog post to go more in depth.

      See more
      CloudCheckr logo

      CloudCheckr

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      Analyze your AWS deployment to track resources, control costs, maintain security, and predict future needs.
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      PROS OF CLOUDCHECKR
      • 2
        Powerful S3 reports
      • 1
        Powerful Reserved Instances reports
      • 1
        Easy setup
      • 1
        CloudTrail integration
      • 1
        Cost Tracking
      CONS OF CLOUDCHECKR
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        Morpheus logo

        Morpheus

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        Orchestrate, Automate, and Manage Across Any Cloud
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        PROS OF MORPHEUS
        • 2
          Easy to deploy and use
        • 1
          Hybrid Cloud Management
        • 1
          Life cycle management
        • 1
          App provisioning
        • 1
          UI, API and CLI
        • 1
          Governance
        • 1
          SDN - ACI, NSX, Neutron
        • 1
          Config Management-Chef,Puppet,Salt,Ansible,AnsibleTower
        • 1
          Reporting
        • 1
          Analytics
        • 1
          Scheduling
        • 1
          Tagging, Env variables, cypher
        • 1
          Automation - Tasks and Workflows
        • 1
          Image builder
        • 1
          Infrastrcuture as Code
        • 1
          Platform as a Service
        • 1
          Infrastructure as Code, Platform as a Service
        CONS OF MORPHEUS
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          Ansible logo

          Ansible

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          Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine
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          PROS OF ANSIBLE
          • 276
            Agentless
          • 204
            Great configuration
          • 195
            Simple
          • 173
            Powerful
          • 151
            Easy to learn
          • 66
            Flexible
          • 54
            Doesn't get in the way of getting s--- done
          • 34
            Makes sense
          • 29
            Super efficient and flexible
          • 27
            Powerful
          • 11
            Dynamic Inventory
          • 8
            Backed by Red Hat
          • 7
            Works with AWS
          • 6
            Cloud Oriented
          • 6
            Easy to maintain
          • 4
            Because SSH
          • 4
            Multi language
          • 4
            Easy
          • 4
            Simple
          • 4
            Procedural or declarative, or both
          • 4
            Simple and powerful
          • 3
            Consistency
          • 3
            Vagrant provisioner
          • 2
            Fast as hell
          • 2
            Masterless
          • 2
            Well-documented
          • 2
            Merge hash to get final configuration similar to hiera
          • 2
            Debugging is simple
          • 1
            Work on windows, but difficult to manage
          • 1
            Certified Content
          CONS OF ANSIBLE
          • 5
            Dangerous
          • 5
            Hard to install
          • 3
            Bloated
          • 3
            Backward compatibility
          • 2
            Doesn't Run on Windows
          • 2
            No immutable infrastructure

          related Ansible posts

          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 23 upvotes · 4.8M views

          Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

          It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

          I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

          We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

          If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

          The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

          Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

          See more
          Sebastian Gębski

          Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

          See more
          CloudBolt logo

          CloudBolt

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          Enterprise Hybrid Cloud Management Platform
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          PROS OF CLOUDBOLT
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              MongoDB Cloud Manager logo

              MongoDB Cloud Manager

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              A hosted platform for managing MongoDB
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              PROS OF MONGODB CLOUD MANAGER
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