Alternatives to GoLand

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

When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.

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.

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

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

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.

We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

#FrameworksFullStack #Languages

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

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.

We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

#FrameworksFullStack #Languages

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.

I've been in the #frontend game for about 7 years now. I started coding in Sublime Text because all of the tutorials I was doing back then everyone was using it. I found the speed amazing compared to some other tools at the time. I kept using Sublime Text for about 4-5 years.

I find Sublime Text lacks some functionality, after all it is just a text editor rather than a full fledged IDE. I finally converted over to PhpStorm as I was working with Magento and Magento as you know is mainly #PHP based.

This was amazing all the features in PhpStorm I loved, the debugging features, and the control click feature when you click on a dependency or linked file it will take you to that file. It was great.

PhpStorm is kind of slow, I found that Prettier was taking a long time to format my code, and it just was lagging a lot so I was looking for alternatives. After watching some more tutorial videos I noticed that everyone was using Visual Studio Code. So I gave it a go, and its amazing.

It has support for everything I need with the plugins and the integration with Git is amazing. The speed of this IDE is blazing fast, and I wouldn't go back to using PhpStorm anymore. I highly recommend giving Visual Studio Code a try!

UPDATE: Thanks for the great response. I am going to start with VSCode based on the open source and free version that will allow me to grow into other languages, but not cost me a license ..yet.

I have been working with software development for 12 years, but I am just beginning my journey to learn to code. I am starting with Python following the suggestion of some of my coworkers. They are split between Eclipse and IntelliJ IDEA for IDEs that they use and PyCharm is new to me. Which IDE would you suggest for a beginner that will allow expansion to Java, JavaScript, and eventually AngularJS and possibly mobile applications?

I use Visual Studio because it provides me best default configuration for development. Less choice helps me concentrate on the product. In a sense it is iPhone of software development for me. When my laptop broke, I just download latest version of VS and start coding without any configuration. For sure it has best editor in terms of perceived responsiveness. Could not say the same for IntelliJ IDEA unfortunately.

When I switched to Visual Studio Code 12 months ago from PhpStorm I was in love, it was great. However after using VS Code for a year, I see myself switching back and forth between WebStorm and VS Code. The VS Code plugins are great however I notice Prettier, auto importing of components and linking to the definitions often break, and I have to restart VS Code multiple times a week and sometimes a day.

We use Ruby here so I do like that Visual Studio Code highlights that for me out of the box, with WebStorm I'd need to probably also install RubyMine and have 2 IDE's going at the same time.

Should I stick with Visual Studio Code, or switch to something else? #help

We use Prettier because when we rebooted our front-end stack, I decided that it would be an efficient use of our time to not worry about code formatting issues and personal preferences during peer review. Prettier eliminates this concern by auto-formatting our code to a deterministic output. We use it along with ESLint and have 1st-class support in our WebStorm and Visual Studio Code editors.

Secure Membership Web API backed by SQL Server. This is the backing API to store additional profile and complex membership metadata outside of an Azure AD B2C provider. The front-end using the Azure AD B2C to allow 3rd party trusted identity providers to authenticate. This API provides a way to add and manage more complex permission structures than can easily be maintained in Azure AD.

We have .Net developers and an Azure infrastructure environment using server-less functions, logic apps and SaaS where ever possible. For this service I opted to keep it as a classic WebAPI project and deployed to AppService.

• Trusted Authentication Provider: @AzureActiveDirectoryB2C
• Frameworks: .NET Core
• Language: C# , Microsoft SQL Server , JavaScript
• IDEs: Visual Studio Code , Visual Studio
• Libraries: jQuery @EntityFramework, @AutoMapper, @FeatureToggle , @Swashbuckle
• Database: @SqlAzure
• Source Control: Git
• Build and Release Pipelines: Azure DevOps
• Test tools: Postman , Newman
• Test framework: @nUnit, @moq
• Infrastructure: @AzureAppService, @AzureAPIManagement

.NET Core is #free, #cross-platform, and #opensource. A developer platform for building all types of apps ( #web apps #mobile #games #machinelearning #AI and #Desktop ).

Developers have chosen .NET for:

Productive: Combined with the extensive class libraries, common APIs, multi-language support, and the powerful tooling provided by the Visual Studio family ( Visual Studio and Visual Studio Code ), .NET is the most productive platform for developers.

Any app: From mobile applications running on iOS, Android and Windows, to Enterprise server applications running on Windows Server and Linux, or high-scale microservices running in the cloud, .NET provides a solution for you.

Performance: .NET is fast. Really fast! The popular TechEmpower benchmark compares web application frameworks with tasks like JSON serialization, database access, and server side template rendering - .NET performs faster than any other popular framework.