A year ago, Harry Bagdi wrote an amazingly helpful blog post on observability for microservices. And by comparing titles, it becomes obvious that my blog post draws inspiration from his work. To be honest, that statement on drawing inspiration from Harry extends well beyond this one blog post – but enough about that magnificent man and more on why I chose to revisit his blog. When he published it, our company was doing an amazing job at one thing: API gateways.

The differences between microservices and web services deal with different concepts in modern application design. A microservice is a small, independent, application that performs a highly focused service as well as possible. A web service is an internet-based interface that makes the “services” of one application available to applications running on different platforms.

You did it. You have machine learning capabilities up and running in your organization. Success! What started as a few nascent experiments (and maybe a few failures) are now carefully constructed models racing along in full production—with the ability to scale into the hundreds or thousands of productional models in sight. Assembling your expert team of data scientists and custodians seems like a distant memory. Now you’re looking ahead to the future—growth, innovation, revenue!

It’s hard to believe that we are now over 30 years into data warehousing. In that time, we have seen major changes in tools to help user report on and analyse data. In the last twenty years, we have seen the evolution from reporting, ad hoc analysis and advanced analytics. Today, BI/Analytics is a mature market with self-service BI and visual analysis standards in most organisations with self-service data preparation also widely deployed.

This post describes an architecture, and associated controls for privacy, to build a data platform for a nationwide proactive contact tracing solution.