cloud

The roots of the project As many other tech workers in startups, I’ve worked on pretty large scale projects (even if that’s subjective). I’m talking about projects involving machine learning, for example, that are often about showing the right advertisment to the right person at the right moment. Training the machine learning models for that requires a lot of resources (CPU, RAM, GPU, etc.). The same is true with APIs that are in charge of collecting data from the clients (the data will very often be used to train the ML models). [Read More]

I you are, like me, concerned about privacy, you may be the administrator of a few physical servers, either at home or rented to some dedicated server providers. Virtual machine instances (or VPS) bought in public clouds are great, but if you can’t configure yourself the underlying network and the hypervisors, where is the fun ? (just kidding, there is so much to do above a cloud-like infrastructure too). Here I’ll describe a little configuration I made for my own needs. [Read More]

Context If you operate an IaaS infrastructure, either private (OpenStack, OpenNebula, …) or public cloud (AWS, GCP, …), you certainly already wondered how to properly bootstrap your first virtual machines templates. IaaS solutions are often linked to a public repository of basic virtual machines images that can be used to quickly start deploying instances. If this is good for initial tests, it’s not that safe to bootstrap all your instances from a guest operating system someone you don’t has built for you. [Read More]