Alternatives to Machinable logo

Alternatives to Machinable

Marvel, Docker, Firebase, Socket.IO, and Pusher are the most popular alternatives and competitors to Machinable.
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What is Machinable and what are its top alternatives?

It provides a RESTful interface to your app's Users and Data. Quickly define and spin-up API endpoints that validate user data so you can focus on the Frontend Experience.
Machinable is a tool in the Realtime Backend / API category of a tech stack.
Machinable is an open source tool with 36 GitHub stars and 3 GitHub forks. Here鈥檚 a link to Machinable's open source repository on GitHub

Top Alternatives of Machinable

Machinable alternatives & related posts

Marvel logo

Marvel

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Prototyping for everyone
Marvel logo
Marvel
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Machinable

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Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD | 21 upvotes 1.7M views
Vagrant
Vagrant
VirtualBox
VirtualBox
Ansible
Ansible
Elasticsearch
Elasticsearch
Kibana
Kibana
Logstash
Logstash
TeamCity
TeamCity
Jenkins
Jenkins
Slack
Slack
Apache Maven
Apache Maven
Vault
Vault
Git
Git
Docker
Docker
CircleCI
CircleCI
LXC
LXC
Amazon EC2
Amazon EC2

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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Tim Nolet
Tim Nolet
Founder, Engineer & Dishwasher at Checkly | 20 upvotes 1.1M views
atChecklyHQChecklyHQ
Heroku
Heroku
Docker
Docker
GitHub
GitHub
Node.js
Node.js
hapi
hapi
Vue.js
Vue.js
AWS Lambda
AWS Lambda
Amazon S3
Amazon S3
PostgreSQL
PostgreSQL
Knex.js
Knex.js
vuex
vuex

Heroku Docker GitHub Node.js hapi Vue.js AWS Lambda Amazon S3 PostgreSQL Knex.js Checkly is a fairly young company and we're still working hard to find the correct mix of product features, price and audience.

We are focussed on tech B2B, but I always wanted to serve solo developers too. So I decided to make a $7 plan.

Why $7? Simply put, it seems to be a sweet spot for tech companies: Heroku, Docker, Github, Appoptics (Librato) all offer $7 plans. They must have done a ton of research into this, so why not piggy back that and try it out.

Enough biz talk, onto tech. The challenges were:

  • Slice of a portion of the functionality so a $7 plan is still profitable. We call this the "plan limits"
  • Update API and back end services to handle and enforce plan limits.
  • Update the UI to kindly state plan limits are in effect on some part of the UI.
  • Update the pricing page to reflect all changes.
  • Keep the actual processing backend, storage and API's as untouched as possible.

In essence, we went from strictly volume based pricing to value based pricing. Here come the technical steps & decisions we made to get there.

  1. We updated our PostgreSQL schema so plans now have an array of "features". These are string constants that represent feature toggles.
  2. The Vue.js frontend reads these from the vuex store on login.
  3. Based on these values, the UI has simple v-if statements to either just show the feature or show a friendly "please upgrade" button.
  4. The hapi API has a hook on each relevant API endpoint that checks whether a user's plan has the feature enabled, or not.

Side note: We offer 10 SMS messages per month on the developer plan. However, we were not actually counting how many people were sending. We had to update our alerting daemon (that runs on Heroku and triggers SMS messages via AWS SNS) to actually bump a counter.

What we build is basically feature-toggling based on plan features. It is very extensible for future additions. Our scheduling and storage backend that actually runs users' monitoring requests (AWS Lambda) and stores the results (S3 and Postgres) has no knowledge of all of this and remained unchanged.

Hope this helps anyone building out their SaaS and is in a similar situation.

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Firebase logo

Firebase

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The Realtime App Platform
Firebase logo
Firebase
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Tassanai Singprom
Tassanai Singprom
JavaScript
JavaScript
PHP
PHP
HTML5
HTML5
jQuery
jQuery
Redis
Redis
Amazon EC2
Amazon EC2
Ubuntu
Ubuntu
Sass
Sass
Vue.js
Vue.js
Firebase
Firebase
Laravel
Laravel
Lumen
Lumen
Amazon RDS
Amazon RDS
GraphQL
GraphQL
MariaDB
MariaDB
Google Analytics
Google Analytics
Postman
Postman
Elasticsearch
Elasticsearch
Git
Git
GitHub
GitHub
GitLab
GitLab
npm
npm
Visual Studio Code
Visual Studio Code
Kibana
Kibana
Sentry
Sentry
BrowserStack
BrowserStack
Slack
Slack

This is my stack in Application & Data

JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB

My Utilities Tools

Google Analytics Postman Elasticsearch

My Devops Tools

Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack

My Business Tools

Slack

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fontumi
fontumi
Firebase
Firebase
Node.js
Node.js
FeathersJS
FeathersJS
Vue.js
Vue.js
Google Compute Engine
Google Compute Engine
Dialogflow
Dialogflow
Cloud Firestore
Cloud Firestore
Git
Git
GitHub
GitHub
Visual Studio Code
Visual Studio Code

Fontumi focuses on the development of telecommunications solutions. We have opted for technologies that allow agile development and great scalability.

Firebase and Node.js + FeathersJS are technologies that we have used on the server side. Vue.js is our main framework for clients.

Our latest products launched have been focused on the integration of AI systems for enriched conversations. Google Compute Engine , along with Dialogflow and Cloud Firestore have been important tools for this work.

Git + GitHub + Visual Studio Code is a killer stack.

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related Socket.IO posts

across_the_grid
across_the_grid
Full-stack web developer at Capmo GmbH | 10 upvotes 194.4K views
Socket.IO
Socket.IO
Node.js
Node.js
ExpressJS
ExpressJS

I use Socket.IO because the application has 2 frontend clients, which need to communicate in real-time. The backend-server handles the communication between these two clients via websockets. Socket.io is very easy to set up in Node.js and ExpressJS.

In the research project, the 1st client shows panoramic videos in a so called cave system (it is the VR setup of our research lab, which consists of three big screens, which are specially arranged, so the user experience the videos more immersive), the 2nd client controls the videos/locations of the 1st client.

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React
React
Redux
Redux
FeathersJS
FeathersJS
HTML5
HTML5
JavaScript
JavaScript
MongoDB
MongoDB
Redis
Redis
Socket.IO
Socket.IO
ES6
ES6

I have always been interested in building a real-time multiplayer game engine that could be massively scalable, and recently I decided to start working on a MMO version of the classic "snake" game. I wanted the entire #Stack to be based on ES6 JavaScript so for the #Backend I chose to use FeathersJS with MongoDB for game/user data storage, Redis for distributed mutex and pub/sub, and Socket.IO for real-time communication. For the #Frontend I used React with Redux.js, the FeathersJS client as well as HTML5 canvas to render the view.

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Pusher
Pusher
PubNub
PubNub
Google Cloud Pub/Sub
Google Cloud Pub/Sub

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Google Cloud Pub/Sub logo

Google Cloud Pub/Sub

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Global service for real-time and reliable messaging and streaming data
Google Cloud Pub/Sub logo
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SignalR logo

SignalR

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A new library for ASP.NET developers that makes developing real-time web functionality easy.
SignalR logo
SignalR
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Pusher
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PubNub
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