Abishek Tiwari discusses how to use stored procedures to create a fast-track API transformation program on top of legacy systems, migrating business logic into a service tier, one store proc at a time
Justin Wood and Giovanni Vigorrelli compare and contrast RAML and Swagger, do a round up of the other specifications languages, and present some conclusions.
Tom Faulhaber discusses the new container-based toolbox for building systems that are robust in the face of failures, how to recover from failure and how the tools can be used to best effect.
Tom Gianos and Dan Weeks discuss Netflix' overall big data platform architecture, focusing on Storage and Orchestration, and how they use Parquet on AWS S3 as their data warehouse storage layer.
Martina Iglesias Fernández discusses Spotify’s approach to documentation through automatic discovery of existing endpoints, service configuration, and deployment information at runtime.
Adam Wick talks about his team’s experience developing CyberChaff, a novel network defense solution with unikernels built into its core and why unikernels made sense for them.
Steven Cooper discusses using machine learning to understand malformed API requests to not only respond with a best fit response, but capture the user errors for future responses.
Rob Harrop discusses the increasing automated field of operations and what the future might hold when machine learning and AI techniques are brought to bear on the problem of systems operations.
Tod Golding discusses the architecture and design strategies associated with building and delivering SaaS solutions in a serverless model.
Glenn Block discusses the truth and myth beyond some beliefs: the web was built for hypermedia, there is no REST without hypermedia, hypermedia is the magic cure for all API ills, etc.
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
David Julia describes some patterns that Pivotal Labs have employed over the last two years of building Spring Boot based microservices in the context of legacy systems.