Alternatives to InSpec logo

Alternatives to InSpec

Serverspec, RSpec, Ansible, JUnit, and xUnit are the most popular alternatives and competitors to InSpec.
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What is InSpec and what are its top alternatives?

It is an open-source testing framework for infrastructure with a human- and machine-readable language for specifying compliance, security and policy requirements.
InSpec is a tool in the Testing Frameworks category of a tech stack.
InSpec is an open source tool with 2.6K GitHub stars and 670 GitHub forks. Here’s a link to InSpec's open source repository on GitHub

Top Alternatives to InSpec

  • Serverspec
    Serverspec

    With Serverspec, you can write RSpec tests for checking your servers are configured correctly. Serverspec tests your servers’ actual state by executing command locally, via SSH, via WinRM, via Docker API and so on. ...

  • RSpec
    RSpec

    Behaviour Driven Development for Ruby. Making TDD Productive and Fun.

  • 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. ...

  • JUnit
    JUnit

    JUnit is a simple framework to write repeatable tests. It is an instance of the xUnit architecture for unit testing frameworks. ...

  • xUnit
    xUnit

    It is a free, open source, community-focused unit testing tool for the .NET Framework. It is the latest technology for unit testing C#, F#, VB.NET and other .NET languages. It works with ReSharper, CodeRush, TestDriven.NET and Xamarin. ...

  • Moq
    Moq

    It is a mocking library for .NET developed from scratch to take full advantage of .NET Linq expression trees and lambda expressions, which makes it the most productive, type-safe and refactoring-friendly mocking library available. And it supports mocking interfaces as well as classes. ...

  • Mockito
    Mockito

    It is a mocking framework that tastes really good. It lets you write beautiful tests with a clean & simple API. It doesn’t give you hangover because the tests are very readable and they produce clean verification errors. ...

  • pytest
    pytest

    A framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. It is a mature full-featured Python testing tool. ...

InSpec alternatives & related posts

Serverspec logo

Serverspec

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Tests for your servers configured by Puppet, Chef or anything else
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      RSpec

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      Behaviour Driven Development for Ruby
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          I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

          We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

          Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

          We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

          Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

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          Simon Bettison
          Managing Director at Bettison.org Limited · | 7 upvotes · 318.2K views

          In 2010 we made the very difficult decision to entirely re-engineer our existing monolithic LAMP application from the ground up in order to address some growing concerns about it's long term viability as a platform.

          Full application re-write is almost always never the answer, because of the risks involved. However the situation warranted drastic action as it was clear that the existing product was going to face severe scaling issues. We felt it better address these sooner rather than later and also take the opportunity to improve the international architecture and also to refactor the database in. order that it better matched the changes in core functionality.

          PostgreSQL was chosen for its reputation as being solid ACID compliant database backend, it was available as an offering AWS RDS service which reduced the management overhead of us having to configure it ourselves. In order to reduce read load on the primary database we implemented an Elasticsearch layer for fast and scalable search operations. Synchronisation of these indexes was to be achieved through the use of Sidekiq's Redis based background workers on Amazon ElastiCache. Again the AWS solution here looked to be an easy way to keep our involvement in managing this part of the platform at a minimum. Allowing us to focus on our core business.

          Rails ls was chosen for its ability to quickly get core functionality up and running, its MVC architecture and also its focus on Test Driven Development using RSpec and Selenium with Travis CI providing continual integration. We also liked Ruby for its terse, clean and elegant syntax. Though YMMV on that one!

          Unicorn was chosen for its continual deployment and reputation as a reliable application server, nginx for its reputation as a fast and stable reverse-proxy. We also took advantage of the Amazon CloudFront CDN here to further improve performance by caching static assets globally.

          We tried to strike a balance between having control over management and configuration of our core application with the convenience of being able to leverage AWS hosted services for ancillary functions (Amazon SES , Amazon SQS Amazon Route 53 all hosted securely inside Amazon VPC of course!).

          Whilst there is some compromise here with potential vendor lock in, the tasks being performed by these ancillary services are no particularly specialised which should mitigate this risk. Furthermore we have already containerised the stack in our development using Docker environment, and looking to how best to bring this into production - potentially using Amazon EC2 Container Service

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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
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            Agentless
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            Great configuration
          • 196
            Simple
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            Powerful
          • 152
            Easy to learn
          • 67
            Flexible
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            Doesn't get in the way of getting s--- done
          • 34
            Makes sense
          • 30
            Super efficient and flexible
          • 27
            Powerful
          • 11
            Dynamic Inventory
          • 8
            Backed by Red Hat
          • 7
            Works with AWS
          • 6
            Easy to maintain
          • 6
            Cloud Oriented
          • 4
            Easy
          • 4
            Procedural or declarative, or both
          • 4
            Simple and powerful
          • 4
            Because SSH
          • 4
            Multi language
          • 4
            Simple
          • 3
            Consistency
          • 3
            Vagrant provisioner
          • 2
            Well-documented
          • 2
            Masterless
          • 2
            Debugging is simple
          • 2
            Merge hash to get final configuration similar to hiera
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            Fast as hell
          • 1
            Manage any OS
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            Work on windows, but difficult to manage
          • 1
            Certified Content
          CONS OF ANSIBLE
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            Dangerous
          • 5
            Hard to install
          • 3
            Doesn't Run on Windows
          • 3
            Bloated
          • 3
            Backward compatibility
          • 2
            No immutable infrastructure

          related Ansible posts

          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 23 upvotes · 5.4M 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.

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          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.

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          JUnit logo

          JUnit

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          A programmer-oriented testing framework for Java
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              We are looking for a Testing Tool that can integrate with Java/ React/ Go/ Python/ Node.js. Which amongst the three tools JUnit, NUnit & Selenium would be the best for this use case?

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              Joshua Dean Küpper
              CEO at Scrayos UG (haftungsbeschränkt) · | 1 upvote · 187.5K views

              We use JUnit for our Java Unit and Integration tests in Version 5. Combined with @JMockit2 and @truth (from Google) we perform all kinds of tests on our minecraft, standalone and microservice architecture.

              We prefer JUnit over TestNG because of the bigger community, better support and the generally more agile development. JUnit integrates nicely with most software, while TestNG support is a little more limited.

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              xUnit logo

              xUnit

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              An open source, community-focused unit testing tool
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                  Moq

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                  The most popular and friendly mocking framework for .NET
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                      Mockito

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                      Tasty mocking framework for unit tests in Java
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                          pytest

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                          A full-featured Python testing tool to help you write better programs
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