Alternatives to Conduit logo

Alternatives to Conduit

Istio, Conductor, Kubernetes, Docker Compose, and Rancher are the most popular alternatives and competitors to Conduit.
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What is Conduit and what are its top alternatives?

Conduit is a lightweight open source service mesh designed for performance, power, and ease of use when running applications on Kubernetes. Conduit is incredibly fast, lightweight, fundamentally secure, and easy to get started with.
Conduit is a tool in the Container Tools category of a tech stack.
Conduit is an open source tool with GitHub stars and GitHub forks. Here’s a link to Conduit's open source repository on GitHub

Top Alternatives to Conduit

  • Istio
    Istio

    Istio is an open platform for providing a uniform way to integrate microservices, manage traffic flow across microservices, enforce policies and aggregate telemetry data. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes, Mesos, etc. ...

  • Conductor
    Conductor

    Conductor is an orchestration engine that runs in the cloud.

  • 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. ...

  • Docker Compose
    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

    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
    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. ...

  • Spring Cloud
    Spring Cloud

    It provides tools for developers to quickly build some of the common patterns in distributed systems. ...

  • Argo
    Argo

    Argo is an open source container-native workflow engine for getting work done on Kubernetes. Argo is implemented as a Kubernetes CRD (Custom Resource Definition). ...

Conduit alternatives & related posts

Istio logo

Istio

955
1.4K
53
Open platform to connect, manage, and secure microservices, by Google, IBM, and Lyft
955
1.4K
+ 1
53
PROS OF ISTIO
  • 14
    Zero code for logging and monitoring
  • 9
    Service Mesh
  • 8
    Great flexibility
  • 5
    Ingress controller
  • 5
    Powerful authorization mechanisms
  • 4
    Full Security
  • 4
    Resiliency
  • 4
    Easy integration with Kubernetes and Docker
CONS OF ISTIO
  • 15
    Performance

related Istio posts

Shared insights
on
IstioIstioDaprDapr

At my company, we are trying to move away from a monolith into microservices led architecture. We are now stuck with a problem to establish a communication mechanism between microservices. Since, we are planning to use service meshes and something like Dapr/Istio, we are not sure on how to split services between the two. Service meshes offer Traffic Routing or Splitting whereas, Dapr can offer state management and service-service invocation. At the same time both of them provide mLTS, Metrics, Resiliency and tracing. How to choose who should offer what?

See more
Anas MOKDAD
Shared insights
on
KongKongIstioIstio

As for the new support of service mesh pattern by Kong, I wonder how does it compare to Istio?

See more
Conductor logo

Conductor

60
107
0
A microservices orchestration engine that runs in the cloud
60
107
+ 1
0
PROS OF CONDUCTOR
    Be the first to leave a pro
    CONS OF CONDUCTOR
      Be the first to leave a con

      related Conductor posts

      Kubernetes logo

      Kubernetes

      51K
      44.7K
      641
      Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
      51K
      44.7K
      + 1
      641
      PROS OF KUBERNETES
      • 162
        Leading docker container management solution
      • 127
        Simple and powerful
      • 104
        Open source
      • 75
        Backed by google
      • 57
        The right abstractions
      • 24
        Scale services
      • 19
        Replication controller
      • 10
        Permission managment
      • 7
        Cheap
      • 7
        Simple
      • 7
        Supports autoscaling
      • 4
        No cloud platform lock-in
      • 4
        Self-healing
      • 4
        Reliable
      • 3
        Quick cloud setup
      • 3
        Open, powerful, stable
      • 3
        Scalable
      • 3
        Promotes modern/good infrascture practice
      • 2
        Custom and extensibility
      • 2
        Cloud Agnostic
      • 2
        Captain of Container Ship
      • 2
        A self healing environment with rich metadata
      • 2
        Runs on azure
      • 2
        Backed by Red Hat
      • 1
        Golang
      • 1
        Expandable
      • 1
        Sfg
      • 1
        Everything of CaaS
      • 1
        Easy setup
      • 1
        Gke
      CONS OF KUBERNETES
      • 15
        Poor workflow for development
      • 15
        Steep learning curve
      • 8
        Orchestrates only infrastructure
      • 4
        High resource requirements for on-prem clusters
      • 2
        Too heavy for simple systems
      • 1
        Additional vendor lock-in (Docker)
      • 1
        More moving parts to secure
      • 1
        Additional Technology Overhead

      related Kubernetes posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 41 upvotes · 5.7M 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
      Docker Compose logo

      Docker Compose

      18.8K
      14.3K
      501
      Define and run multi-container applications with Docker
      18.8K
      14.3K
      + 1
      501
      PROS OF DOCKER COMPOSE
      • 123
        Multi-container descriptor
      • 110
        Fast development environment setup
      • 79
        Easy linking of containers
      • 68
        Simple yaml configuration
      • 60
        Easy setup
      • 16
        Yml or yaml format
      • 12
        Use Standard Docker API
      • 8
        Open source
      • 5
        Go from template to application in minutes
      • 5
        Can choose Discovery Backend
      • 4
        Scalable
      • 4
        Easy configuration
      • 4
        Kubernetes integration
      • 3
        Quick and easy
      CONS OF DOCKER COMPOSE
      • 9
        Tied to single machine
      • 5
        Still very volatile, changing syntax often

      related Docker Compose posts

      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 29 upvotes · 5.3M views

      Our whole DevOps stack consists of the following tools:

      • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
      • Respectively Git as revision control system
      • SourceTree as Git GUI
      • Visual Studio Code as IDE
      • CircleCI for continuous integration (automatize development process)
      • Prettier / TSLint / ESLint as code linter
      • SonarQube as quality gate
      • Docker as container management (incl. Docker Compose for multi-container application management)
      • VirtualBox for operating system simulation tests
      • Kubernetes as cluster management for docker containers
      • Heroku for deploying in test environments
      • nginx as web server (preferably used as facade server in production environment)
      • SSLMate (using OpenSSL) for certificate management
      • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
      • PostgreSQL as preferred database system
      • Redis as preferred in-memory database/store (great for caching)

      The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

      • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
      • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
      • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
      • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
      • Scalability: All-in-one framework for distributed systems.
      • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
      See more

      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.

      See more
      Rancher logo

      Rancher

      889
      1.4K
      644
      Open Source Platform for Running a Private Container Service
      889
      1.4K
      + 1
      644
      PROS OF RANCHER
      • 103
        Easy to use
      • 79
        Open source and totally free
      • 63
        Multi-host docker-compose support
      • 58
        Load balancing and health check included
      • 58
        Simple
      • 44
        Rolling upgrades, green/blue upgrades feature
      • 42
        Dns and service discovery out-of-the-box
      • 37
        Only requires docker
      • 34
        Multitenant and permission management
      • 29
        Easy to use and feature rich
      • 11
        Cross cloud compatible
      • 11
        Does everything needed for a docker infrastructure
      • 8
        Simple and powerful
      • 8
        Next-gen platform
      • 7
        Very Docker-friendly
      • 6
        Support Kubernetes and Swarm
      • 6
        Application catalogs with stack templates (wizards)
      • 6
        Supports Apache Mesos, Docker Swarm, and Kubernetes
      • 6
        Rolling and blue/green upgrades deployments
      • 6
        High Availability service: keeps your app up 24/7
      • 5
        Easy to use service catalog
      • 4
        Very intuitive UI
      • 4
        IaaS-vendor independent, supports hybrid/multi-cloud
      • 4
        Awesome support
      • 3
        Scalable
      • 2
        Requires less infrastructure requirements
      CONS OF RANCHER
      • 10
        Hosting Rancher can be complicated

      related Rancher posts

      Docker Swarm logo

      Docker Swarm

      754
      929
      268
      Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
      754
      929
      + 1
      268
      PROS OF DOCKER SWARM
      • 54
        Docker friendly
      • 45
        Easy to setup
      • 39
        Standard Docker API
      • 37
        Easy to use
      • 22
        Native
      • 21
        Free
      • 12
        Clustering made easy
      • 11
        Simple usage
      • 10
        Integral part of docker
      • 5
        Cross Platform
      • 4
        Labels and annotations
      • 4
        Performance
      • 2
        Shallow learning curve
      • 2
        Easy Networking
      CONS OF DOCKER SWARM
      • 9
        Low adoption

      related Docker Swarm posts

      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
      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 29 upvotes · 5.3M views

      Our whole DevOps stack consists of the following tools:

      • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
      • Respectively Git as revision control system
      • SourceTree as Git GUI
      • Visual Studio Code as IDE
      • CircleCI for continuous integration (automatize development process)
      • Prettier / TSLint / ESLint as code linter
      • SonarQube as quality gate
      • Docker as container management (incl. Docker Compose for multi-container application management)
      • VirtualBox for operating system simulation tests
      • Kubernetes as cluster management for docker containers
      • Heroku for deploying in test environments
      • nginx as web server (preferably used as facade server in production environment)
      • SSLMate (using OpenSSL) for certificate management
      • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
      • PostgreSQL as preferred database system
      • Redis as preferred in-memory database/store (great for caching)

      The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

      • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
      • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
      • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
      • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
      • Scalability: All-in-one framework for distributed systems.
      • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
      See more
      Spring Cloud logo

      Spring Cloud

      747
      701
      0
      Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
      747
      701
      + 1
      0
      PROS OF SPRING CLOUD
        Be the first to leave a pro
        CONS OF SPRING CLOUD
          Be the first to leave a con

          related Spring Cloud posts

          Spring-Boot Spring Cloud Elasticsearch MySQL Redis RabbitMQ Kafka MongoDB GitHub Linux IntelliJ IDEA

          See more
          Argo logo

          Argo

          438
          373
          5
          Container-native workflows for Kubernetes
          438
          373
          + 1
          5
          PROS OF ARGO
          • 2
            Open Source
          • 2
            Autosinchronize the changes to deploy
          • 1
            Online service, no need to install anything
          CONS OF ARGO
            Be the first to leave a con

            related Argo posts