I've been getting back into building scrappy little web apps for my friends. On top of this, I recently joined a startup and getting away from Enterprise class software has made me make a huge mind-shift. In the recent past when I wanted to build apps I was thinking Kubernetes, Helm Charts, etc. However, in small app, and startup land reducing the barriers to ship is very important.

Here we are, its 2017 dotnet core is out, and finally dotnet has a proper cli. In a previous post we explored the new cli. In short you can use the dotnet cli to build, test, package, and publish projects. However sometimes just using the cli is not enough. Sometimes, you land in a place where you have many projects to compile, test, and package.

Now that dotnet core tools have been released I thought it would be good to look into the dotnet cli. This is a new command line interface to build, manage, compile and run dotnet core based applications

Today marks the release of Visual Studio 2017, and with it the final release of the tools for dotnet core. This means as of today you can build, test, and deploy an application completely supported by microsoft. Not just the runtimes, but the tooling as well. The CLI for dotnet core has been finalized, and its awesome. The csproj system has been revitalized. New csproj's can be created, and are fully compatible with the old. Visual studio 2017 has finally released. This is probably the greatest version of visual studio ever created. Finally VS has gone from a slow, archaic editor, to a fast moving IDE. An IDE with a DevOps-First Cloud-First mentality. An IDE ready to tackle today's modern challenges.

Recently I wanted to make myself a short url host. Really, I made this not to make short urls, but to make memorable urls for myself.

tl;dr click here

When we talk about capturing metrics in applications. One server/service that constantly is in all conversations monitoring, is statsd. Incase you have never heard of it, statsd is a udp/tcp server that you send your in-code metrics to. These metrics get aggregated by statsd, and are forwarded to various backends. Some backends are services like librato or sumologic. Other times you are sending metrics to time series databases such as graphite or god forbid influxdb.

This boils down to in code you can say "log whenever this block of code is hit" or say "measure how long this function takes to execute". These stories come together to form pretty graphs, and rich alerts. All of this enabled by statsd.