Alternatives to Lumen

I use Laravel because it's the most advances PHP framework out there, easy to maintain, easy to upgrade and most of all : easy to get a handle on, and to follow every new technology ! PhpStorm is our main software to code, as of simplicity and full range of tools for a modern application.

Google Analytics Analytics of course for a tailored analytics, Bulma as an innovative CSS framework, coupled with our Sass (Scss) pre-processor.

As of more basic stuff, we use HTML5, JavaScript (but with Vue.js too) and Webpack to handle the generation of all this.

To deploy, we set up Buddy to easily send the updates on our nginx / Ubuntu server, where it will connect to our GitHub Git private repository, pull and do all the operations needed with Deployer .

CloudFlare ensure the rapidity of distribution of our content, and Let's Encrypt the https certificate that is more than necessary when we'll want to sell some products with our Stripe api calls.

Asana is here to let us list all the functionalities, possibilities and ideas we want to implement.

Back at the start of 2017, we decided to create a web-based tool for the SEO OnPage analysis of our clients' websites. We had over 2.000 websites to analyze, so we had to perform thousands of requests to get every single page from those websites, process the information and save the big amounts of data somewhere.

Very soon we realized that the initial chosen script language and database, PHP, Laravel and MySQL, was not going to be able to cope efficiently with such a task.

By that time, we were doing some experiments for other projects with a language we had recently get to know, Go , so we decided to get a try and code the crawler using it. It was fantastic, we could process much more data with way less CPU power and in less time. By using the concurrency abilites that the language has to offers, we could also do more Http requests in less time.

Unfortunately, I have no comparison numbers to show about the performance differences between Go and PHP since the difference was so clear from the beginning and that we didn't feel the need to do further comparison tests nor document it. We just switched fully to Go.

There was still a problem: despite the big amount of Data we were generating, MySQL was performing very well, but as we were adding more and more features to the software and with those features more and more different type of data to save, it was a nightmare for the database architects to structure everything correctly on the database, so it was clear what we had to do next: switch to a NoSQL database. So we switched to MongoDB, and it was also fantastic: we were expending almost zero time in thinking how to structure the Database and the performance also seemed to be better, but again, I have no comparison numbers to show due to the lack of time.

We also decided to switch the website from PHP and Laravel to JavaScript and Node.js and ExpressJS since working with the JSON Data that we were saving now in the Database would be easier.

As of now, we don't only use the tool intern but we also opened it for everyone to use for free: https://tool-seo.com

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.

I'm building most projects using: Server: either Fastify (all projects going forward) or ExpressJS on Node.js (existing, previously) on the server side, and Client app: either Vuetify (currently) or Quasar Framework (going forward) on Vue.js with vuex on Electron for the UI to deliver both web-based and desktop applications for multiple platforms.

The direct support for Android and iOS in Quasar Framework will make it my go-to client UI platform for any new client-side or web work. On the server, I'll probably use Fastly for all my server work, unless I get into Go more in the future.

Update: The mobile support in Quasar is not a sufficiently compelling reason to move me from Vuetify. I have decided to stick with Vuetify for a UI for Vue, as it is richer in components and enables a really great-looking professional result. For mobile platforms, I will just use Cordova to wrap the Vue+Vuetify app for mobile, and Electron to wrap it for desktop platforms.

One of our top priorities at Pinterest is fostering a safe and trustworthy experience for all Pinners. As Pinterest’s user base and ads business grow, the review volume has been increasing exponentially, and more content types require moderation support. To solve greater engineering and operational challenges at scale, we needed a highly-reliable and performant system to detect, report, evaluate, and act on abusive content and users and so we created Pinqueue.

Pinqueue-3.0 serves as a generic platform for content moderation and human labeling. Under the hood, Pinqueue3.0 is a Flask + React app powered by Pinterest’s very own Gestalt UI framework. On the backend, Pinqueue3.0 heavily relies on PinLater, a Pinterest-built reliable asynchronous job execution system, to handle the requests for enqueueing and action-taking. Using PinLater has significantly strengthened Pinqueue3.0’s overall infra with its capability of processing a massive load of events with configurable retry policies.

Hundreds of millions of people around the world use Pinterest to discover and do what they love, and our job is to protect them from abusive and harmful content. We’re committed to providing an inspirational yet safe experience to all Pinners. Solving trust & safety problems is a joint effort requiring expertise across multiple domains. Pinqueue3.0 not only plays a critical role in responsively taking down unsafe content, it also has become an enabler for future ML/automation initiatives by providing high-quality human labels. Going forward, we will continue to improve the review experience, measure review quality and collaborate with our machine learning teams to solve content moderation beyond manual reviews at an even larger scale.

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

Zulip has been powered by Django since the very early days of its development with Django 1.4, back in 2012. As a reasonably mature web application with significant scale, we're at the stage in many companies' development where one starts to rip out more and more of the web framework to optimize things or just make them work the way we want. (E.g. while I was at Dropbox in early 2016, we discovered we only had about 600 lines of code left from the original Pylons framework that actually ran).

One of the things that has been really fantastic about Django is that we're still happily using it for the vast majority of code in the project, and every time Django comes out with a new release, I read the changelog and get excited about several improvements that actually make my life better. While Django has made some design decisions that I don't agree with (e.g. I'm not a fan of Django REST framework, and think it makes life more difficult), Django also makes it easy to do your own thing, which we've done to great effect (see the linked article for details on our has_request_variables framework).

Overall I think we've gotten a ton of value out of Python and Django and would recommend it to anyone starting a new full-featured web application project today.

What is the best way to increase your income as a freelancer in 2019? What frameworks should be the best to learn? React Node.js Docker Kubernetes Sequelize Mongoose MongoDB ExpressJS hapi Based on trends I've picked up a JS full stack. If you need to work under startups you may replace React with Vue.js . If you want to work in outsourcing Angular 2+ may be better.

What is your opinion?

We are using Node.js and ExpressJS to build a REST services that is middleware of a legacy system. MongoDB as database. Vue.js helps us to make rapid UI to test use cases. Frontend is build for mobile with Ionic . We like using JavaScript and ES6 .

I think next step could be to use Koa but I am not sure.

Will base most server-side APIs on Fastify . Smaller, faster, easier. Faster than Koa; and twice as fast as ExpressJS.

I'm about to start a new project to build a REST API, and I got to this point: Yii2 Vs Lumen Vs Slim, I used Yii 1.1 a while a go and it was awesome, really easy to work with, as a developer you don't have to worry about almost anything, just setup the framework, get your php extensions, and start coding your app.

But, I was told about performance and someone recomended Lumen or Slim to work with a micro framework and a less bloated framework, what worries me is the lack of advantages that Yii2 offers, ACF and RBAC as a native tool on the framework, gii, the model validations and all the security props already in it.

Is it worth it? Is the performance so great on those frameworks to leave aside the advantages of a framework like Yii2?

How do you suggest to make the test to prove wich one is better?

PHP Lumen Yii Slim

I use LoopBack because it is: * It is truly and Unbelievably Extensible * it is default integrated with OpenAPI (Swagger) Spec Driven REST API * I write lesser codes, because most of the user stories have been covered using the code generation * It's documentation is more compact and well detailed than ExpressJS * It is very easy to learn, hence you can build a basic Rest API App in minutes * It has built in NPM packages required to build my Rest API which saves me time on installation and configuration * The Datasource/Service/Controller concept is just Brilliant (that's mostly all you need to get your app speaking with an External API services) * The support for SOAP and Rest API services is amazing!

React LoopBack Node.js ExpressJS Elasticsearch Kibana Logstash Sequelize Mocha Chai Visual Studio Code are the combo of technologies being used by me to build BestPrice Extension with all its micro-services & Web-based fragments