Disclaimer This is a technical article about a work in progress. The primary goal is to document what I did and to clarify my ideas. A more general and complete article about software 2.0 is in development and should be published on my company’s blog later. This post describes the concept of software 2.0. It evaluates an instance of the Unicode equation parser (as described here) to give a strict separation of the software 1.
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.