Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

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...

We are hardcore Kubernetes users and contributors. We loved the automation it provides. However, as our team grew and added more clusters and microservices, capacity and resources management becomes a massive pain to us. We started suffering from a lot of outages and unexpected behavior as we promote our code from dev to production environments. Luckily we were working on our AI-powered tools to understand different dependencies, predict usage, and calculate the right resources and configurations that should be applied to our infrastructure and microservices. We dogfooded our agent (http://github.com/magalixcorp/magalix-agent) and were able to stabilize as the #autopilot continuously recovered any miscalculations we made or because of unexpected changes in workloads. We are open sourcing our agent in a few days. Check it out and let us know what you think! We run workloads on Microsoft Azure Google Kubernetes Engine and Amazon EC2 and we're all about Go and Python!

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

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.

Following its migration from vanilla instances with autoscaling groups to Kubernetes, Postmates began facing challenges while “migrating workloads that needed to scale up very quickly.”

The built-in Horizontal Pod Autoscaler (HPA) automatically scales the number of pods in a replication controller, deployment or replica set based on observed CPU utilization. But the challenges for Postmates is that there’s no way to configure the scale velocity of one particular cluster with an HPA.

For Postmates, which runs at least three different types of applications with distinct performance and scaling characteristics, this proved problematic.

To overcome these challenges, the team created and open sourced the Configurable Horizontal Pod Autoscaler, which allows for fine-grained tuning on a per-HPA object basis. The result is that “you can configure critical services to scale down very slowly, while every other service could be configured to scale down instantly to reduce costs.”

I use C# because it is incredibly clear and easy to use. The documentation is second to none, being a Microsoft product, and if you just want something that works without exploring a million frameworks and libraries you can pretty much start a C# website and have it running in an hour. C# is basically, in my opinion, a cleaner and easier to use Java. My experience is limited to web design, however. It might come down to personal opinion but I wouldn't even know where to start writing a java back end website but visual studio makes it very easy to write it in C#. If you are new to full stack development I can't recommend Visual Studio enough. It does, however, hide away a lot of abstraction that programmers much more clever than me use to make really interesting websites and server setups. C# will do everything you need to create any website you can imagine, though.

Before I end my rant about how much I love this language I'd like to reiterate how easy it is to figure out problems you encounter. I was stuck on how to store a path string in a database and found the solution by browsing the documentation for 2 minutes, which included examples. Every ASP element is clearly and wonderfully documented.

I adopted Clojure and ClojureScript because:

• it's 1 language, multiple platforms.
• Simple syntax.
• Designed to avoid unwanted side effects and bugs.
• Immutable data-structures.
• Compact code, very expressive.
• Source code is data.
• It has super-flexible macro.
• Has metadata.
• Interoperability with JavaScript, Java and C#.

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.

TypeScript saves you from all nonsense semantics of JavaScript , LOL.

NATS: fast message queue and easy to deploy / maintain.

Docker makes deployment painless.

Git essential tool for collaboration and source management.

I'm #Fullstack here and work with Vue.js, React and Node.js in some projects but also C# for other clients. Also started learning Python. And all this with just one tool!: #Vscode I have used Atom and Sublime Text in the past and they are very good too, but for me now is just vscode. I think the combination of vscode with the free available extensions that the community is creating makes a powerful tool and that's why vscode became the most popular IDE for software development. You can match it to your own needs in a couple of minutes. Did I mention you can style it your way? Amazing tool!

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

Our new backend micro services are primarily written in Node.js and Go and legacy systems are written in Java. For our new stack decision, we aimed to achieve greater developer productivity, low IO latency and good community so we had couple of technologies in hand to choose but finally we concluded to go for Node.js for API layer and Go for CPU/IO intensive tasks. Currently the inter-services communication is happening via REST but soon to be moved to RPC-based communication.

We have added very little to the CoffeeScript Hubot application – just enough to allow it to talk to our Hubot workers. The Hubot workers implement our operational management functionality and expose it to Hubot so we can get chat integration for free. We’ve also tailored the authentication and authorization code of Hubot to meet the needs of roles within our team.

For larger tasks, we’ve got an internal #CLI written in Go that talks to the same #API as Hubot, giving access to the same functionality we have in Slack, with the addition of scripting, piping, and all of our favorite #Unix tools. When the Hubot worker recognizes the CLI is in use, it logs the commands to Slack to maintain visibility of operational changes.

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 use C# because of the ease of designing user interfaces compared to Java. Using Visual Studio makes C# a breeze for prototyping and creating apps and I really appreciate how quickly I can turn an idea into reality. I was first introduced to C# in a special topics course and quickly started preferring it over Java. The similarities between the two made the switch easy while the added benefits C# offers made it very worth it.