In a previous article, I described an implementation of an RNN from scratch in go. The target is to use the RNN as a processing unit. The ultimate goal is to create a portable tool cross platform and able to grab and process data where they are. I have many applications in mind such as finding the root-cause of an incident or managing the capacity of an infrastructure. Note I stick to the Go language for many reasons: Some of them a personnal and not opposable (I simply like it).

Shakespeare and I, encounter of the third type A couple of months ago, I attended the Google Cloud Next 17 event in London. Among the talks about SRE, and keynotes, I had the chance to listen to Martin Gorner’s excellent introduction: TensorFlow and Deep Learning without a PhD, Part 2. If you don’t want to look at the video, here is a quick summary: a 100 of lines of python are reading all Shakespeare’s plays; it learns his style, and then generates a brand new play from scratch.

In a previous post, I did some experiments with gRPC, protocol buffer and Terraform. The idea was to transform the “Terraform” cli tool into a micro-service thanks to gRPC. This post is the second part of the experiment. I will go deeper in the code and see if it is possible to create a brand new utility, without hacking Terraform. The idea is to import some packages that compose the binary and create my own service based on gRPC.