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...

I use Kong because it reliably proxies traffic quickly with an assortment of pluggable features. The engineers behind the product are of the highest quality. The Company has cultivated the largest active open source community of any API gateway. They generally squash bugs in hours or days not weeks/months. Company engineers help community members through social avenues as well as supporting large enterprise. They heavily value their product and individuals as opposed to just solely growing enterprise license fees.

We needed a lightweight and completely customizable #microservices #gateway to be able to generate #JWT and introspect #OAuth2 tokens as well. The #gateway was going to front all #APIs for our single page web app as well as externalized #APIs for our partners.

We looked at Tyk Cloud and Kong. Kong's plugins are all Lua based and its core is NGINX and OpenResty. Although it's open source, it's not the greatest platform to be able to customize. On top of that enterprise features are paid and expensive. Tyk is Go and the nomenclature used within Tyk like "sessions" was bizarre, and again enterprise features were paid.

We ultimately decided to roll our own using ExpressJS into Express Gateway because the use case for using ExpressJS as an #API #gateway was tried and true, in fact - all the enterprise features that the other two charge for #OAuth2 introspection etc were freely available within ExpressJS middleware.

We opened source Express Gateway with a core set of plugins and the community started writing their own and could quickly do so by rolling lots of ExpressJS middleware into Express Gateway

Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

Read the blog post to go more in depth.