Conductrics vs Kubernetes

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What is Conductrics?

It offers an API that allows users to create targeted, self-optimizing, customer-facing web and mobile applications.

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 Conductrics?
Why do developers choose Kubernetes?
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      What are some alternatives to Conductrics and Kubernetes?
      Optimizely
      Optimizely is the market leader in digital experience optimization, helping digital leaders and Fortune 100 companies alike optimize their digital products, commerce, and campaigns with a fully featured experimentation platform.
      Visual Website Optimizer
      Visual Website Optimizer is an easy to use A/B testing tool that allows marketing professionals to create different versions of their websites and landing pages using a point-and-click editor (no HTML knowledge needed!) and then see which version produces maximum conversion rate or sales
      Optimize
      Whether it’s a custom-tailored message at checkout or a completely revamped homepage,it shows you which site experiences engage and delight your customers, and gives you the solutions you need to deliver them.
      AB Tasty
      It is an all-inclusive platform for conversion rate optimization, personalization, customer activation, and testing. We serve as your digital lab.
      Adobe Target
      A/B and multivariate testing. Personalization. AI-powered automation at scale. Testing and personalization with features that optimize, automate, and predict the best experiences for your audiences.
      See all alternatives
      Decisions about Conductrics and Kubernetes
      Yshay Yaacobi
      Yshay Yaacobi
      Software Engineer · | 27 upvotes · 338.5K views
      atSolutoSoluto
      Docker Swarm
      Docker Swarm
      .NET
      .NET
      F#
      F#
      C#
      C#
      JavaScript
      JavaScript
      TypeScript
      TypeScript
      Go
      Go
      Visual Studio Code
      Visual Studio Code
      Kubernetes
      Kubernetes

      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
      Sebastian Gębski
      Sebastian Gębski
      CTO at Shedul/Fresha · | 6 upvotes · 56.3K views
      atFresha EngineeringFresha Engineering
      Docker
      Docker
      Docker Compose
      Docker Compose
      Kubernetes
      Kubernetes
      Terraform
      Terraform
      Ansible
      Ansible
      Amazon EC2
      Amazon EC2
      Amazon EKS
      Amazon EKS
      Amazon S3
      Amazon S3
      Amazon RDS
      Amazon RDS

      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
      Emanuel Evans
      Emanuel Evans
      Senior Architect at Rainforest QA · | 12 upvotes · 153.3K views
      atRainforest QARainforest QA
      Heroku
      Heroku
      Kubernetes
      Kubernetes
      Google Kubernetes Engine
      Google Kubernetes Engine
      Google Cloud SQL for PostgreSQL
      Google Cloud SQL for PostgreSQL
      PostgreSQL
      PostgreSQL
      Google Cloud Memorystore
      Google Cloud Memorystore
      Redis
      Redis
      CircleCI
      CircleCI
      Google Cloud Build
      Google Cloud Build
      Helm
      Helm
      Terraform
      Terraform

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

      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 · 64.1K views
      atDailyDaily
      Kubernetes
      Kubernetes
      GitHub
      GitHub
      CircleCI
      CircleCI
      Docker
      Docker
      Helm
      Helm

      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 · 2.1K views
      atStackShareStackShare
      Heroku
      Heroku
      Kubernetes
      Kubernetes
      Amazon EKS
      Amazon EKS
      Google Kubernetes Engine
      Google Kubernetes Engine
      Slack
      Slack
      Helm
      Helm
      CircleCI
      CircleCI
      Amazon EC2 Container Service
      Amazon EC2 Container Service

      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.

      See more
      Robert Zuber
      Robert Zuber
      CTO at CircleCI · | 6 upvotes · 16.4K views
      atCircleCICircleCI
      Docker
      Docker
      Kubernetes
      Kubernetes
      Nomad
      Nomad
      Helm
      Helm

      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.

      See more
      Interest over time
      Reviews of Conductrics 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 Conductrics 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 Conductrics cost?
      How much does Kubernetes cost?
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