Alternatives to LiteSpeed

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.

Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

We've been happy with nginx as part of our stack. As an open source web application that folks install on-premise, the configuration system for the webserver is pretty important to us. I have a few complaints (e.g. the configuration syntax for conditionals is a pain), but overall we've found it pretty easy to build a configurable set of options (see link) for how to run Zulip on nginx, both directly and with a remote reverse proxy in front of it, with a minimum of code duplication.

Certainly I've been a lot happier with it than I was working with Apache HTTP Server in past projects.

nginx or Apache HTTP Server that's the question. The best choice depends on what it needs to serve. In general, Nginx performs better with static content, where Apache and Nginx score roughly the same when it comes to dynamic content. Since most webpages and web-applications use both static and dynamic content, a combination of both platforms may be the best solution.

Since both webservers are easy to deploy and free to use, setting up a performance or feature comparison test is no big deal. This way you can see what solutions suits your application or content best. Don't forget to look at other aspects, like security, back-end compatibility (easy of integration) and manageability, as well.

A reasonably good comparison between the two can be found in the link below.

I need some advice to choose an engine for generation web pages from the Spring Boot app. Which technology is the best solution today? 1) JSP + JSTL 2) Apache FreeMarker 3) Thymeleaf Or you can suggest even other perspective tools. I am using Spring Boot, Spring Web, Spring Data, Spring Security, PostgreSQL, Apache Tomcat in my project. I have already tried to generate pages using jsp, jstl, and it went well. However, I had huge problems via carrying already created static pages, to jsp format, because of syntax. Thanks.

Java Spring JUnit

Apache HTTP Server Apache Tomcat

MySQL

I am currently in school for computer science and am doing a class project about web servers. Our assignment is to research and select one of these web servers. Could you please let me know which one you would choose among NGINX, Microsoft IIS, and Apache HTTP Server and why?

We use nginx and OpenResty as our API proxy running on EC2 for auth, caching, and some rate limiting for our dozens of microservices. Since OpenResty support embedded Lua we were able to write a custom access module that calls out to our authentication service with the resource, method, and access token. If that succeeds then critical account info is passed down to the underlying microservice. This proxy approach keeps all authentication and authorization in one place and provides a unified CX for our API users. Nginx is fast and cheap to run though we are always exploring alternatives that are also economical. What do you use?

At Kong while building an internal tool, we struggled to route metrics to Prometheus and logs to Logstash without incurring too much latency in our metrics collection.

We replaced nginx with OpenResty on the edge of our tool which allowed us to use the lua-nginx-module to run Lua code that captures metrics and records telemetry data during every request’s log phase. Our code then pushes the metrics to a local aggregator process (written in Go) which in turn exposes them in Prometheus Exposition Format for consumption by Prometheus. This solution reduced the number of components we needed to maintain and is fast thanks to NGINX and LuaJIT.

Unlike our frontend, we chose Flask, a microframework, for our backend. We use it with Python 3 and Gunicorn.

One of the reasons was that I have significant experience with this framework. However, it also was a rather straightforward choice given that our backend almost only serves REST APIs, and that most of the work is talking to the database with SQLAlchemy .

We could have gone with something like Hug but it is kind of early. We might revisit that decision for new services later on.

I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.

We switched from Unicorn (process model) to Puma (threaded model) to decrease the memory footprint of our Rails production web server. Memory indeed dropped from 6GB to only 1GB!

We just had to decrease our worker count and increase our thread count instead. Performance (response time and throughput) remained the same, if not slightly better. We had no thread-safety errors, which was good.

Free bonus points are:

• Requests are blazing fast on our dev and staging environments!
• Puma has first-class support for WebSockets, so we know for sure that Rails ActionCable or GraphQL subscriptions will work great.
• Being on Puma makes us even more "default Rails"-compliant since it is the default Rails web server these days.

I have an integration service that pulls data from third party systems saves it and returns it to the user of the service. We can pull large data sets with the service and response JSON can go up to 5MB with gzip compression. I currently use Rails 6 and Ruby 2.7.2 and Puma web server. Slow clients tend to prevent other users from accessing the system. Am considering a switch to Unicorn.