Alternatives to Helios logo

Alternatives to Helios

Apollo, Kubernetes, Docker Compose, Helm, and Rancher are the most popular alternatives and competitors to Helios.
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What is Helios and what are its top alternatives?

Helios is a Docker orchestration platform for deploying and managing containers across an entire fleet of servers. Helios provides a HTTP API as well as a command-line client to interact with servers running your containers.
Helios is a tool in the Container Tools category of a tech stack.
Helios is an open source tool with 2.1K GitHub stars and 255 GitHub forks. Here’s a link to Helios's open source repository on GitHub

Top Alternatives to Helios

  • Apollo

    Apollo

    Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes. ...

  • 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. ...

  • 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. ...

  • Docker Machine

    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. ...

Helios alternatives & related posts

Apollo logo

Apollo

1.9K
1.5K
18
GraphQL server for Express, Connect, Hapi, Koa and more
1.9K
1.5K
+ 1
18
PROS OF APOLLO
  • 12
    From the creators of Meteor
  • 3
    Great documentation
  • 2
    Real time if use subscription
  • 1
    Open source
CONS OF APOLLO
    Be the first to leave a con

    related Apollo posts

    Nick Rockwell
    SVP, Engineering at Fastly · | 44 upvotes · 1.8M views

    When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

    So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

    React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

    Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

    See more
    Adam Neary

    At Airbnb we use GraphQL Unions for a "Backend-Driven UI." We have built a system where a very dynamic page is constructed based on a query that will return an array of some set of possible “sections.” These sections are responsive and define the UI completely.

    The central file that manages this would be a generated file. Since the list of possible sections is quite large (~50 sections today for Search), it also presumes we have a sane mechanism for lazy-loading components with server rendering, which is a topic for another post. Suffice it to say, we do not need to package all possible sections in a massive bundle to account for everything up front.

    Each section component defines its own query fragment, colocated with the section’s component code. This is the general idea of Backend-Driven UI at Airbnb. It’s used in a number of places, including Search, Trip Planner, Host tools, and various landing pages. We use this as our starting point, and then in the demo show how to (1) make and update to an existing section, and (2) add a new section.

    While building your product, you want to be able to explore your schema, discovering field names and testing out potential queries on live development data. We achieve that today with GraphQL Playground, the work of our friends at #Prisma. The tools come standard with Apollo Server.

    #BackendDrivenUI

    See more
    Kubernetes logo

    Kubernetes

    40.2K
    34.4K
    628
    Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
    40.2K
    34.4K
    + 1
    628
    PROS OF KUBERNETES
    • 159
      Leading docker container management solution
    • 124
      Simple and powerful
    • 101
      Open source
    • 75
      Backed by google
    • 56
      The right abstractions
    • 24
      Scale services
    • 18
      Replication controller
    • 9
      Permission managment
    • 7
      Supports autoscaling
    • 7
      Simple
    • 6
      Cheap
    • 4
      Reliable
    • 4
      No cloud platform lock-in
    • 4
      Self-healing
    • 3
      Quick cloud setup
    • 3
      Open, powerful, stable
    • 3
      Scalable
    • 3
      Promotes modern/good infrascture practice
    • 2
      Cloud Agnostic
    • 2
      Runs on azure
    • 2
      Backed by Red Hat
    • 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
    • 13
      Poor workflow for development
    • 11
      Steep learning curve
    • 5
      Orchestrates only infrastructure
    • 2
      High resource requirements for on-prem clusters

    related Kubernetes posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 39 upvotes · 4.4M 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

    15.3K
    11.3K
    477
    Define and run multi-container applications with Docker
    15.3K
    11.3K
    + 1
    477
    PROS OF DOCKER COMPOSE
    • 121
      Multi-container descriptor
    • 109
      Fast development environment setup
    • 75
      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
      Go from template to application in minutes
    • 4
      Can choose Discovery Backend
    • 2
      Kubernetes integration
    • 2
      Easy configuration
    • 2
      Scalable
    • 1
      Quick and easy
    CONS OF DOCKER COMPOSE
    • 8
      Tied to single machine
    • 5
      Still very volatile, changing syntax often

    related Docker Compose posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.5M 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

    974
    672
    11
    The Kubernetes Package Manager
    974
    672
    + 1
    11
    PROS OF HELM
    • 5
      Infrastructure as code
    • 3
      Open source
    • 2
      Easy setup
    • 1
      Testa­bil­i­ty and re­pro­ducibil­i­ty
    CONS OF HELM
      Be the first to leave a con

      related Helm posts

      Emanuel Evans
      Senior Architect at Rainforest QA · | 17 upvotes · 739.6K 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
      Robert Zuber

      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
      Rancher logo

      Rancher

      815
      1.3K
      644
      Open Source Platform for Running a Private Container Service
      815
      1.3K
      + 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
      • 8
        Hosting Rancher can be complicated

      related Rancher posts

      Docker Swarm logo

      Docker Swarm

      709
      854
      268
      Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
      709
      854
      + 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
        Performance
      • 4
        Labels and annotations
      • 2
        Shallow learning curve
      • 2
        Easy Networking
      CONS OF DOCKER SWARM
      • 7
        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 · | 28 upvotes · 3.5M 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

      698
      637
      0
      Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
      698
      637
      + 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

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          Docker Machine logo

          Docker Machine

          423
          490
          12
          Machine management for a container-centric world
          423
          490
          + 1
          12
          PROS OF DOCKER MACHINE
          • 12
            Easy docker hosts management
          CONS OF DOCKER MACHINE
            Be the first to leave a con

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