I love Markdown… I mean, who doesn’t? I use it for everything: wiki pages, release notes, API documentation, deployment guides, to do lists for my wife. Ok maybe not that last one, I’m usually the recipient of the to do lists!
I’ve designed a little domain specific language in C# to manage changes to the system clock. The objective was to simulate a sequence of transactions running against my domain model with realistic time intervals between each transaction.
I found out this week that using the LIKE operator in an Entity Framework
query is maddeningly difficult 😳. I reckon there are three options, each with
different trade-offs and levels of difficulty.
Recently I’ve been thinking a lot about manual exploratory testing and performance testing, both of which require large sets of realistic test data.
On most projects we can’t use real user data for testing (due to data security rules) so instead I’ve come up with a few simple techniques to generate large sets of random, but realistic, sample data.
I’m a big fan of using Vagrant for development. I really like the approach of installing the framework, database and development tools on a project-specific virtual machine that can be shared with the other folks on the team.
But Docker is the shiny new toy that promises development / production parity, allowing infrastructure to be scripted alongside the code and run in these light-weight container thingy-me-bobs.
Does Docker live up to its promises? Is it time to evict the Vagrant? I’ve developed a simple web app to find out…
Colin the Geek