Introduction

If you can’t measure it, you can’t improve it. Every production system needs observability – the ability to understand what’s happening inside your services from the outside. In this post, we’ll walk through the key pieces of a monitoring stack: querying metrics with SQL, collecting them with Python, visualising the architecture, and presenting status dashboards with inline HTML.

Whether you’re running a handful of microservices or a full-blown platform, the fundamentals are the same. Let’s build it up from scratch.

Introduction

Welcome to my first blog post. This is a space where I explore various topics in software engineering, from database queries to data pipelines and system design. Grab a coffee and let’s dive in.

The best way to learn is by doing. Throughout this post, I’ll walk through some real examples that cover SQL analytics, Python scripting, system architecture, and a bit of web styling.

Analyzing User Engagement with SQL

One of the first things you might want to do with a new product is understand how users are interacting with it. Here’s a query that calculates a rolling 7-day active user count, broken down by signup cohort: