Container Factory vs Kubernetes

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Container Factory vs Kubernetes: What are the differences?

Container Factory: Turn your Github repo into a published container image. container-factory produces Docker images from tarballs of application source code. It accepts archives with Dockerfiles, but if your application's language is supported, it can automatically add a suitable Dockerfile; Kubernetes: Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops. 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.

Container Factory and Kubernetes can be categorized as "Container" tools.

Container Factory and Kubernetes are both open source tools. It seems that Kubernetes with 55K GitHub stars and 19.1K forks on GitHub has more adoption than Container Factory with 56 GitHub stars and 2 GitHub forks.

What is Container Factory?

container-factory produces Docker images from tarballs of application source code. It accepts archives with Dockerfiles, but if your application's language is supported, it can automatically add a suitable Dockerfile.

What is 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.
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Why do developers choose Container Factory?
Why do developers choose Kubernetes?
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        What are some alternatives to Container Factory and Kubernetes?
        Docker Compose
        With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.
        Rancher
        Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.
        Docker Swarm
        Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.
        Docker Machine
        Machine lets you create Docker hosts on your computer, on cloud providers, and inside your own data center. It creates servers, installs Docker on them, then configures the Docker client to talk to them.
        Helm
        Helm is the best way to find, share, and use software built for Kubernetes.
        See all alternatives
        Decisions about Container Factory and Kubernetes
        Yshay Yaacobi
        Yshay Yaacobi
        Software Engineer · | 27 upvotes · 218.9K views
        atSolutoSoluto
        Docker Swarm
        Docker Swarm
        Kubernetes
        Kubernetes
        Visual Studio Code
        Visual Studio Code
        Go
        Go
        TypeScript
        TypeScript
        JavaScript
        JavaScript
        C#
        C#
        F#
        F#
        .NET
        .NET

        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...

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        Sebastian Gębski
        Sebastian Gębski
        CTO at Shedul/Fresha · | 6 upvotes · 41.9K views
        atFresha EngineeringFresha Engineering
        Amazon RDS
        Amazon RDS
        Amazon S3
        Amazon S3
        Amazon EKS
        Amazon EKS
        Amazon EC2
        Amazon EC2
        Ansible
        Ansible
        Terraform
        Terraform
        Kubernetes
        Kubernetes
        Docker Compose
        Docker Compose
        Docker
        Docker

        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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        Emanuel Evans
        Emanuel Evans
        Senior Architect at Rainforest QA · | 12 upvotes · 103.9K views
        atRainforest QARainforest QA
        Terraform
        Terraform
        Helm
        Helm
        Google Cloud Build
        Google Cloud Build
        CircleCI
        CircleCI
        Redis
        Redis
        Google Cloud Memorystore
        Google Cloud Memorystore
        PostgreSQL
        PostgreSQL
        Google Cloud SQL for PostgreSQL
        Google Cloud SQL for PostgreSQL
        Google Kubernetes Engine
        Google Kubernetes Engine
        Kubernetes
        Kubernetes
        Heroku
        Heroku

        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.

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        GitHub
        GitHub
        nginx
        nginx
        ESLint
        ESLint
        AVA
        AVA
        Semantic UI React
        Semantic UI React
        Redux
        Redux
        React
        React
        PostgreSQL
        PostgreSQL
        ExpressJS
        ExpressJS
        Node.js
        Node.js
        FeathersJS
        FeathersJS
        Heroku
        Heroku
        Amazon EC2
        Amazon EC2
        Kubernetes
        Kubernetes
        Jenkins
        Jenkins
        Docker Compose
        Docker Compose
        Docker
        Docker
        #Frontend
        #Stack
        #Backend
        #Containers
        #Containerized

        Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

        We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

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        Ido Shamun
        Ido Shamun
        at The Elegant Monkeys · | 6 upvotes · 33.8K views
        atDailyDaily
        Helm
        Helm
        Docker
        Docker
        CircleCI
        CircleCI
        GitHub
        GitHub
        Kubernetes
        Kubernetes

        Kubernetes powers our #backend services as it is very easy in terms of #devops (the managed version). We deploy everything using @helm charts as it provides us to manage deployments the same way we manage our code on GitHub . On every commit a CircleCI job is triggered to run the tests, build Docker images and deploy them to the registry. Finally on every master commit CircleCI also deploys the relevant service using Helm chart to our Kubernetes cluster

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        Russel Werner
        Russel Werner
        Lead Engineer at StackShare · | 0 upvotes · 4K views
        atStackShareStackShare
        Amazon EC2 Container Service
        Amazon EC2 Container Service
        CircleCI
        CircleCI
        Helm
        Helm
        Slack
        Slack
        Google Kubernetes Engine
        Google Kubernetes Engine
        Amazon EKS
        Amazon EKS
        Kubernetes
        Kubernetes
        Heroku
        Heroku

        We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.

        We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.

        The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.

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        Robert Zuber
        Robert Zuber
        CTO at CircleCI · | 6 upvotes · 10.6K views
        atCircleCICircleCI
        Helm
        Helm
        Nomad
        Nomad
        Kubernetes
        Kubernetes
        Docker
        Docker

        Our backend consists of two major pools of machines. One pool hosts the systems that run our site, manage jobs, and send notifications. These services are deployed within Docker containers orchestrated in Kubernetes. Due to Kubernetes’ ecosystem and toolchain, it was an obvious choice for our fairly statically-defined processes: the rate of change of job types or how many we may need in our internal stack is relatively low.

        The other pool of machines is for running our users’ jobs. Because we cannot dynamically predict demand, what types of jobs our users need to have run, nor the resources required for each of those jobs, we found that Nomad excelled over Kubernetes in this area.

        We’re also using Helm to make it easier to deploy new services into Kubernetes. We create a chart (i.e. package) for each service. This lets us easily roll back new software and gives us an audit trail of what was installed or upgraded.

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        Interest over time
        Reviews of Container Factory and Kubernetes
        Review ofKubernetesKubernetes

        It's a little bit complex to onboard, but once you grasp all the different concepts the platform is really powerful, and infrastructure stops being an issue.

        Service discovery, auto-recovery, scaling and orchestration are just a few of the features you get.

        How developers use Container Factory and Kubernetes
        Avatar of Matt Welke
        Matt Welke uses KubernetesKubernetes

        Just tinkering with it for personal use at this stage based on positive experience using it at work. Plan to use it for high traffic distributed systems if not using a managed hosting service like Heroku, AWS Lambda, or Google Cloud Functions. Reasons for using instead of these alternatives would be cheaper cost at higher scale.

        Avatar of realcloudratics
        realcloudratics uses KubernetesKubernetes

        Good existential question. Kubernetes is painful in the extreme - especially when combined with Ansible. The layers of indirection are truly mind altering. But hey - containers are kewl!

        Avatar of Japan Digital Design
        Japan Digital Design uses KubernetesKubernetes

        Our developer experience system is on Kubernetes (Google Kubernetes Engine at the moment). We would like to expand our Kubernetes clusters over other Kubernetes engine.

        Avatar of ShareThis
        ShareThis uses KubernetesKubernetes

        Kubernetes is used for managing microclusters within our AWS infrastructure. This allows us to deploy new infrastructure in seconds.

        Avatar of papaver
        papaver uses KubernetesKubernetes

        minor experience with kubernetes. helped a client setup a kubernetes infrastructure. love the elegance of the system.

        How much does Container Factory cost?
        How much does Kubernetes cost?
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