Alternatives to Helios logo

Alternatives to Helios

Apollo, Kubernetes, Docker Compose, Spring Cloud, 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 254 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. ...

  • 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. ...

  • 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). ...

Helios alternatives & related posts

Apollo logo

Apollo

2K
1.7K
22
GraphQL server for Express, Connect, Hapi, Koa and more
2K
1.7K
+ 1
22
PROS OF APOLLO
  • 12
    From the creators of Meteor
  • 5
    Great documentation
  • 3
    Open source
  • 2
    Real time if use subscription
CONS OF APOLLO
  • 1
    File upload is not supported
  • 1
    Increase in complexity of implementing (subscription)

related Apollo posts

Nick Rockwell
SVP, Engineering at Fastly · | 44 upvotes · 2.2M 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

49.5K
43.2K
639
Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
49.5K
43.2K
+ 1
639
PROS OF KUBERNETES
  • 162
    Leading docker container management solution
  • 126
    Simple and powerful
  • 104
    Open source
  • 75
    Backed by google
  • 56
    The right abstractions
  • 24
    Scale services
  • 19
    Replication controller
  • 10
    Permission managment
  • 7
    Simple
  • 7
    Cheap
  • 7
    Supports autoscaling
  • 4
    Reliable
  • 4
    Self-healing
  • 4
    No cloud platform lock-in
  • 3
    Quick cloud setup
  • 3
    Open, powerful, stable
  • 3
    Scalable
  • 3
    Promotes modern/good infrascture practice
  • 2
    Captain of Container Ship
  • 2
    A self healing environment with rich metadata
  • 2
    Cloud Agnostic
  • 2
    Runs on azure
  • 2
    Backed by Red Hat
  • 2
    Custom and extensibility
  • 1
    Golang
  • 1
    Expandable
  • 1
    Gke
  • 1
    Easy setup
  • 1
    Sfg
  • 1
    Everything of CaaS
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 · 5.5M 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

18.3K
13.9K
501
Define and run multi-container applications with Docker
18.3K
13.9K
+ 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 · 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
Rancher logo

Rancher

877
1.4K
644
Open Source Platform for Running a Private Container Service
877
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

746
920
268
Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
746
920
+ 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 · 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

744
694
0
Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
744
694
+ 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 Machine logo

      Docker Machine

      430
      506
      12
      Machine management for a container-centric world
      430
      506
      + 1
      12
      PROS OF DOCKER MACHINE
      • 12
        Easy docker hosts management
      CONS OF DOCKER MACHINE
        Be the first to leave a con

        related Docker Machine posts

        Argo logo

        Argo

        419
        357
        5
        Container-native workflows for Kubernetes
        419
        357
        + 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