A new career step ahead with Google

Since I started my career (late 90s) back in Brazil, I’ve always dreamed about reaching certain milestones. Getting a degree in computer science, then pursue a masters degree with a good university, become a good software engineer with solid fundamentals in computation and programming, build a strong relationships network, so on so forth. At the time, Microsoft, Apple and IBM were huge companies already and were producing most of the technology the market was consuming. Read more…

Diabetes Predictor – Leveraging Recommendations API alongside digital assistant

This is the third post of a series of four covering the process I went through with Americas University’s technical team to create a digital diabetes predictor. The first one introduces the scenario, solution’s rational and ends up with the building of the AI model that will serve as prediction engine in Azure ML. The second guides through the process of creating a digital assistant (Bot) that uses the AI model previously created to predict Read more…

Leveraging Azure Container Registry Tasks to build and push Docker images

Containers provide new levels of virtualization, isolating application and developer dependencies from infrastructure and operational requirements. What remains, however, is the need to address how this application virtualization is managed and patched over the container lifecycle. Most companies and developers rely on Docker Desktop for that purpose, as it is lightweight, works pretty well for both Windows, Linux and Mac, takes care of important configuration details on guest OS, and so on, but mainly because Read more…

Diabetes Predictor – Building a digital assistant

Couple weeks ago I published an article here in the blog outlining the process of creating a new machine learning model that has the ability of predict diabetes for a given person based-upon a set of data provided. That one is the first article of a series of three, and is available in here. Go check it out! In today’s post I’m going to discuss the process we went through to build out the diabetes Read more…

Diabetes Predictor – Building the ML Model

Historically, developers don’t take any serious responsibilities on application’s data. I mean, they used to some point in the past, but certainly not over the past five, ten years. Database’s technologies evolution and ORMs (Object Relational Mapper) efficiency on top of it, ended up creating a whole generation of developers that didn’t need to understand what’s happening under-the-covers. Personally, I see advantages and disadvantages on developers taking that path with the main advantage being how Read more…

Implementing Virtual Machine to Pod communication in Azure Kubernetes Service (AKS)

Network is one of the trickiest parts of a Kubernetes (K8s)’ cluster. That’s because there are multiple layers of abstraction that has to be implemented in different ways (Host, Container Engine, Kubernetes, and so on) to make the communication between objects within the cluster feasible. Today’s post is not about explaining or getting into the details of how networking is handled by Kubernetes. Actually, K8s documentation does a great job on laying this down. If Read more…

Spinning up a Splunk instance on top of Web Apps for Containers in Azure

Logging as much information as possible is something critical for modern applications. You know that. More recently, adding intelligence to generated data towards to identify patterns, prevent future issues, and such, has also become critical. Adding to that, considering the fact that most companies are in the process of moving applications, databases and its underlying infrastructures into the public cloud (Azure, AWS, GCP and others) it is almost certain that some critical portion of the Read more…

Six reasons by why you shouldn’t be doing Kubernetes just yet

First things first. Kubernetes (and its variations) is great and currently, the only logical choice for companies building up microservices in the cloud (no matter what kind). This article has nothing to do with the technology itself. Instead, it’s a combination of insights I have gathered from working with customers embarking on Kubernetes projects over the last three years on an almost daily basis. This article should not dissuade or to discourage you from embarking Read more…

Common Data Models – Bringing CDM to life

The last two posts in this blog were all about discussing concepts related to Common Data Models (CDM) and also, describing an approachable process (writing it with some comprehensive code) on how to project CDM for real case scenarios. With today’s post, I want to discuss possibilities on the tooling currently available out there to bring code-based CDMs (like the one we’ve built) into life. If you didn’t have the chance to take a look Read more…

Common Data Models – Defining an initial structure for Americas University

Couple months ago I started a new series of posts here about Common Data Models (CDM). The idea with that was to starting some exploration around this new technology brought by Microsoft into the market throughout its data services in Azure, and where the benefits of it resides. The first post that introduces the concept of CDM and does suggest a fictitious scenario for us to land down the concepts related to it overtime, can Read more…