Relational databases are the default, but they aren't the only way to store data. NoSQL databases trade some of the structure and guarantees of tables for flexibility and scale, and knowing when that trade is worth making is part of designing a backend. Once your system is running, you also need a way to see what it is doing, which is where observability comes in.
You'll start by comparing SQL and NoSQL and looking at MongoDB, the best-known document database. Then the focus shifts to watching a live system through its logs, metrics, and traces, and to tools like Prometheus and Grafana that collect that data and turn it into dashboards and alerts.
This is the last module in the course. Once you've finished it, head to the Projects section to put everything you've learned into practice.
What MongoDB is, how a document database differs from a relational one, and how to think about SQL versus NoSQL when choosing where to store your data.
A quick look at MongoDB, the popular document database, and features like full-text search, geospatial queries, and data aggregation.
What observability is, how it differs from basic monitoring, and how logs, metrics, and traces each help you understand what a running system is doing.
An overview of what Prometheus is and how to use it, including installing it and connecting its metrics to Grafana dashboards.