Over 10,000 physical typewritten documents from 1932 to 1941 had to be digitised, structured, and connected in order to create a single, centralised source of knowledge, for enabling the analysis of historical processes.
To improve the performance of your microservice architecture, you may consider using graph analysis techniques. By using tools like jQAssistant and Neo4j, you can identify potential issues, better understand the relationships between different services, and even analyze the potential impact of changes on your system. With these tools, you can answer questions like:
Are there any antipatterns present in my microservice architecture? How will certain database refactoring efforts affect the other services in my system? Is my API documentation and specification accurate and up to date? Can I get a clear and current visualization of my entire system?
By implementing graph analysis techniques, you can work towards optimizing the design and functionality of your microservice architecture.
Watch a talk by Eric Wespi from Boston Scientific and GraphAware’s Eric Spiegelberg given at GraphConnect NY 2018.
The Dataportal is a data resource search engine which connects users with visualizations, tools, curated data, and metrics to do their job more effectively. It aids with data discovery, trust, and empowers Airbnb employees to be “data informed” in their decision making, and encourages a culture of self-service.