What is Dart?
What is Go?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Go?
Sign up to add, upvote and see more consMake informed product decisions
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
Stitch is run entirely on AWS. All of our transactional databases are run with Amazon RDS, and we rely on Amazon S3 for data persistence in various stages of our pipeline. Our product integrates with Amazon Redshift as a data destination, and we also use Redshift as an internal data warehouse (powered by Stitch, of course).
The majority of our services run on stateless Amazon EC2 instances that are managed by AWS OpsWorks. We recently introduced Kubernetes into our infrastructure to run the scheduled jobs that execute Singer code to extract data from various sources. Although we tend to be wary of shiny new toys, Kubernetes has proven to be a good fit for this problem, and its stability, strong community and helpful tooling have made it easy for us to incorporate into our operations.
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...
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.
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
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
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:
Go is a high performance language with simple syntax / semantics. Although it is not as expressive as some other languages, it's still a great language for backend development.
Python is expressive and battery-included, and pre-installed in most linux distros, making it a great language for scripting.
PostgreSQL: Rock-solid RDBMS with NoSQL support.
NATS: fast message queue and easy to deploy / maintain.
Docker makes deployment painless.
Git essential tool for collaboration and source management.
For the backend of https://www.rsvpkeeper.com I went with Go.
My past few project have been built with Go and I'm really loving it. It was my first statically typed language after many years with PHP and Node.js - and honestly I couldn't be happier to have made the switch.
The biggest thing for me, is that with the forced declaration of types - it's made me feel like I've made a more solid backend. Sometimes with PHP I felt like a stiff breeze could knock the whole thing down. I know that's an exaggeration - but it's kinda how it feels.
Anyways, everyone knows that it almost doesn't even matter what an app is actually made with - what really matters are the design decisions you make a long the way.
At FlowStack we write most of our backend in Go. Go is a well thought out language, with all the right compromises for speedy development of speedy and robust software. It's tooling is part of what makes Go such a great language. Testing and benchmarking is built into the language, in a way that makes it easy to ensure correctness and high performance. In most cases you can get more performance out of Rust and C or C++, but getting everything right is more cumbersome.
I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.
We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.
Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis for cache and other time sensitive operations.
We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.
In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.
Go has been a joy to work with. Performance is often 30x of what we used to see with Python. It's a performant and productive programming language: https://getstream.io/blog/switched-python-go/
- Most server-side scripts, all unit tests, all build tools, etc. were driven by NodeJS.
- ExpressJS served as the 'backend' server framework.
- MongoDB (which stores essential JSON) was the main database.
- MongooseJS was used as the main ORM for communicating with the database, with KnexJS used for certain edge cases.
- MochaJS, ChaiJS, and ExpectJS were used for unit testing.
- Frontend builds were done with Gulp and Webpack.
- Package management was done primarily with npm - with a few exceptions that required the use of Bower (also configured with JSON).
- The frontend was build primarily with ReactJS (as the View) and Redux (as the Controller / Store / frontend model).
- Configuration was done with json files.
The only notable exceptions were the use of SCSS (augmented by Compass) for styling, Bash for a few basic 'system chores' and CLI utilities required for development of the app (most notably git and heroku's CLI interface), and a bit of custom SQL for locations where the ORM extractions leaked (the app is DB-agnostic, but a bit of SQL was required to fill gaps in the ORMs when interfacing with Postgres).
The first time I actually started using Go was for software on our devices. So on our hotspots we have some custom software running in the firmware. For the first device, that was actually completely built by our manufacturer. But for the second generation most of the parts are built by us in-house and we needed a way to quickly develop software for the device. But we don't have any C programmers in-house, so we were actually looking for something that basically sits in between the friendliness of Ruby, but the performance and the ability to be deployed on an embedded system which you get with C. That's basically what led us to Go and it's been awesome for that. It works so well and so great. Since it works so great, it pushed us into looking into whether we should start using this for some backend services as well.
The following basic API endpoints are implemented on the server written in Go:
- Authorization (Sign Up, Sign In)
- Update user profile
- Community: add post, like post, add comment, delete post, add reply to comment
- Self-diagnosis: send data from the app to the server
- Journal: send user data from the app to the server
- Add groups of community
- Report post, report comment, report reply
- Block user
We are now re-considering TypeScript because 1) the tooling has improved significantly, and 2) and the root cause of the majority of our front-end bugs are related to typing (despite having PropTypes).
We wrote our own image processing, resizing, and snapshotting service in Go to allow our clients to send photos and GIFs to each other. Files are stored in S3, resized on the fly using OpenCV, and then cached in GroupCache before being served to clients.
Go allows it all to be quite fast and efficient, and entirely non-blocking on uploads!
Our main web scraping engine is built usign Golang because of the way how efficiently and fast this language is. Also out compilation facility let people who dont know Golang build fast as flash scrapers to run ourside of our platform without any knowledge in programming in Golang.
For some of our more taxing parts of our applications, something able to handle high I/O load quickly and with fast processing is needed. Go has completely filled that gap, allowing us to break down walls that would've been completely impossible with other languages.