[TL;DR: In the second part of the series, I fine-tune the original recommendations engine, add a secondary data source, and write an Angular client to consume the data.]

In the “Building a Recommendations Engine Using Spring Boot and Slash GraphQL” article, the recently released Slash GraphQL hosted GraphQL backend by Dgraph was utilized as a system of record for a Java-based recommendations engine. …

Improve your GraphQL skills by building something practical that can also help your career

A silhoutte of a man looking up at the stars.
Photo by Greg Rakozy on Unsplash

In this article, I’m going to explore graph databases/GraphQL by building a proof-of-concept blog powered by the recently launched Slash GraphQL — a hosted-GraphQL back end.

Graphs are a fascinating way to model the information in a system where the relationships (edges) between pieces of data (nodes) are first-class entities of the system. This is a different approach to the more common relational database (RDBMS) model, where the relationships between records are implied. For example, “this user owns this post because user.id == post.user_id.”

Graphs are most useful when the relationships among the data are as important as the data itself. …


Over the past decade, continuous integration (CI) and continuous delivery (CD) have become staples of the software development lifecycle. CI automates the process of merging code and checking for basic regressions and code quality issues, relieving some of the code review burden on your dev team. CD and automated deployments eliminate the overhead involved each time a new feature or a hotfix needs to get deployed.

Imagine if there were no more nights and weekends spent packaging builds and manually deploying across servers! …


Michael Bogan

25 years of startups, products, and software architecture. Currently run DevSpotlight — tech content for tech companies. michael@devspotlight.com.

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