Alternatives to Weave logo

Alternatives to Weave

Lighthouse, Knit, Kubernetes, Docker Compose, and Helm are the most popular alternatives and competitors to Weave.
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What is Weave and what are its top alternatives?

Weave can traverse firewalls and operate in partially connected networks. Traffic can be encrypted, allowing hosts to be connected across an untrusted network. With weave you can easily construct applications consisting of multiple containers, running anywhere.
Weave is a tool in the Container Tools category of a tech stack.
Weave is an open source tool with GitHub stars and GitHub forks. Here’s a link to Weave's open source repository on GitHub

Top Alternatives to Weave

  • Lighthouse
    Lighthouse

    Collaborate effortlessly on projects. Whether you’re a team of 5 or studio of 50, Lighthouse will help you keep track of your project development with ease. We give you all the tools you need to organize your tickets – custom states, a powerful tagging system, an advanced search, saved searches (we call them ticket bins), and a mass editing tool. ...

  • Knit
    Knit

    Today, the way remote meetings are run is inefficient. Everyone is crammed into one call and discussion is either stale or everyone is interrupting. It is a group video call reimagined. ...

  • 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. ...

  • Helm
    Helm

    Helm is the best way to find, share, and use software built for Kubernetes.

  • 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. ...

  • Spring Cloud
    Spring Cloud

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

  • 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. ...

Weave alternatives & related posts

Lighthouse logo

Lighthouse

182
163
0
Beautifully Simple Issue Tracking
182
163
+ 1
0
PROS OF LIGHTHOUSE
    Be the first to leave a pro
    CONS OF LIGHTHOUSE
      Be the first to leave a con

      related Lighthouse posts

      Knit logo

      Knit

      0
      5
      0
      The group video call reimagined
      0
      5
      + 1
      0
      PROS OF KNIT
        Be the first to leave a pro
        CONS OF KNIT
          Be the first to leave a con

          related Knit posts

          Kubernetes logo

          Kubernetes

          47K
          40.7K
          635
          Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
          47K
          40.7K
          + 1
          635
          PROS OF KUBERNETES
          • 161
            Leading docker container management solution
          • 126
            Simple and powerful
          • 103
            Open source
          • 75
            Backed by google
          • 56
            The right abstractions
          • 24
            Scale services
          • 19
            Replication controller
          • 9
            Permission managment
          • 7
            Simple
          • 7
            Supports autoscaling
          • 6
            Cheap
          • 4
            Self-healing
          • 4
            No cloud platform lock-in
          • 4
            Reliable
          • 3
            Open, powerful, stable
          • 3
            Scalable
          • 3
            Quick cloud setup
          • 3
            Promotes modern/good infrascture practice
          • 2
            Backed by Red Hat
          • 2
            Cloud Agnostic
          • 2
            Runs on azure
          • 2
            Custom and extensibility
          • 2
            Captain of Container Ship
          • 2
            A self healing environment with rich metadata
          • 1
            Golang
          • 1
            Easy setup
          • 1
            Everything of CaaS
          • 1
            Sfg
          • 1
            Expandable
          • 1
            Gke
          CONS OF KUBERNETES
          • 15
            Poor workflow for development
          • 14
            Steep learning curve
          • 7
            Orchestrates only infrastructure
          • 4
            High resource requirements for on-prem clusters
          • 2
            Too heavy for simple systems
          • 1
            Additional Technology Overhead
          • 1
            More moving parts to secure
          • 1
            Additional vendor lock-in (Docker)

          related Kubernetes posts

          Conor Myhrvold
          Tech Brand Mgr, Office of CTO at Uber · | 41 upvotes · 5.2M 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

          17.5K
          13.2K
          481
          Define and run multi-container applications with Docker
          17.5K
          13.2K
          + 1
          481
          PROS OF DOCKER COMPOSE
          • 121
            Multi-container descriptor
          • 109
            Fast development environment setup
          • 77
            Easy linking of containers
          • 66
            Simple yaml configuration
          • 58
            Easy setup
          • 15
            Yml or yaml format
          • 11
            Use Standard Docker API
          • 7
            Open source
          • 4
            Can choose Discovery Backend
          • 4
            Go from template to application in minutes
          • 3
            Kubernetes integration
          • 2
            Scalable
          • 2
            Easy configuration
          • 2
            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 · 4.6M 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
          Helm logo

          Helm

          1.1K
          760
          18
          The Kubernetes Package Manager
          1.1K
          760
          + 1
          18
          PROS OF HELM
          • 8
            Infrastructure as code
          • 6
            Open source
          • 2
            Easy setup
          • 1
            Support
          • 1
            Testa­bil­i­ty and re­pro­ducibil­i­ty
          CONS OF HELM
            Be the first to leave a con

            related Helm posts

            Emanuel Evans
            Senior Architect at Rainforest QA · | 18 upvotes · 1M 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
            Ido Shamun
            at The Elegant Monkeys · | 7 upvotes · 330.7K views

            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

            See more
            Rancher logo

            Rancher

            860
            1.4K
            644
            Open Source Platform for Running a Private Container Service
            860
            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

            Spring Cloud logo

            Spring Cloud

            744
            681
            0
            Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
            744
            681
            + 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
                Docker Swarm logo

                Docker Swarm

                740
                902
                268
                Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
                740
                902
                + 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
                • 8
                  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 · 4.6M 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