Graph vs graph: GraphQL as the API for your Graph Database (GraphQL Days, Bodensee, September 2019)

Most stories of GraphQL implementations focus on retrofitting a GraphQL layer on top of existing APIs to surface the data’s graphiness. But what if you’re starting from scratch and you know you’ll need a graph from day 1 - what role is there for GraphQL when it’s not the only graph representation in your stack. I’ll tell you how, at the FT, we’ve combined a graph database with GraphQL to expose operational information about our business like never before.

A field guide to the Financial Times (neo4j graph tour, London, March 2019)

The FT was a microservices pioneer, and our teams had a lot of freedom to pick the tools & processes they wanted. 5 years on, many people have moved on and those innovative projects are now legacy code. I’ll tell you about our journey, using neo4j & graphQL, towards keeping track of it all.

Speeding up without slowing down (DeltaV Conf, London, May 2018)

At FT we built one of the world’s fastest media websites, and release to production dozens of times a day. But the architectural and organisational decisions aimed at allowing us to deliver reliable features quickly and consistently don’t always fit neatly with the desire to optimise performance.

In this warts-and-all talk, you’ll learn

  • how we build FT.com
  • how a highly componentised, microservices stack with a rapid release cycle can sometimes get in the way of performance
  • some ideas for working around these obstacles

  • that web performance is hard, and no-one’s perfect

  • Slides
  • Video

Speeding up without slowing down (LDNWebPerf, London, November 2017)

At FT we built one of the world’s fastest media websites, and release to production dozens of times a day. But the architectural and organisational decisions aimed at allowing us to deliver reliable features quickly and consistently don’t always fit neatly with our desire to optimise performance.

In this warts-and-all talk, you’ll learn

  • how we build FT.com
  • how a highly componentised, microservices stack with a rapid release cycle can sometimes get in the way of performance
  • some ideas for working around these obstacles

  • that web performance is hard, and no-one’s perfect

  • Slides
  • Video

Where are the comments? (LDNWebPerf, London, December 2016)

Data and performance tradeoffs on FT.com