Resources

So, for your brand new project, you decided to throw away your monolith and go for microservices. But after a while, you realize things are not going as smoothly as expected ;-)

Hopefully, a graph can help to detect antipatterns, visualize your whole system, and even do cross-service impact analysis.

In this talk, we’ll analyze a microservice system based on Spring Cloud, with jQAssistant and Neo4j. We will see how it can be helpful to answer questions like:

do I have anti-patterns in my microservice architecture ?

which services / applications are impacted when doing a database refactoring ?

is my API documentation / specification up to date ?

how to get an up to date visualization of my whole system ?

and more !

Visualizing a complex graph is a task of graph simplification and providing well-thought visual cues, the best UI goes unnoticed. This talk will summarize current approaches and present a novel user interaction pattern, which takes advantage of a performant Neo4j graph engine.

Tracking end of line manufacturing issues to their source can be a daunting task. Boston Scientific, in partnership with GraphAware, has used the Neo4j platform to build a manufacturing quality tool that offers dramatic improvements to the time, quality, and quantity of investigations. In this talk we will review a manufacturing value stream in a graph and discuss the analysis methods available, which result in striking increases in business efficiencies, for this unique application. We will also present how the system was implemented within the existing data architecture and then scaled from a laptop investigational tool to an enterprise-grade solution with Neo4j Server.