November 14, 2019

167 words 1 min read

The evolution and future of software architecture

The evolution and future of software architecture

Mark Richards discusses the evolution of software architecture and shows how the systems we've built so far wont live up to current social, economic, and technology demands.
Talk Title The evolution and future of software architecture
Speakers Mark Richards (Self-employed)
Conference O’Reilly Software Architecture Conference
Conf Tag Engineering the Future of Software
Location New York, New York
Date April 3-5, 2017
URL Talk Page
Slides
Video Talk Video

Back in the day, large-scale monolithic systems ruled the world. While these systems worked well in their time, we saw them quickly fall apart in the 2000s. But why? Mark Richards discusses the evolution of software architecture and shows how the systems we’ve built so far won’t live up to current social, economic, and technology demands. Mark then outlines the ingredients that go into both evolutionary architecture and competitive advantage, offers a glimpse of what software architecture will look like in the future, and shares the things we software architects need to focus on and think about beyond 2017.

large-scale
comments powered by Disqus
Applying data and machine learning to scale education

Applying data and machine learning to scale education

November 9, 2019

Daphne Koller explains how Coursera is using large-scale data processing and machine learning in online education. Building on Coursera's wealth of online learning data, Daphne discusses the role of automation in scaling access to education that is personalized and efficient at connecting people with skills and knowledge throughout their lives.
Big data for big data: Machine-learning models of Hadoop cluster behavior

Big data for big data: Machine-learning models of Hadoop cluster behavior

November 9, 2019

Sean Suchter and Shekhar Gupta describe the use of very fine-grained performance data from many Hadoop clusters to build a model predicting excessive swapping events.
From rivulets to rivers: Elastic stream processing in Heron

From rivulets to rivers: Elastic stream processing in Heron

November 6, 2019

Twitter processes billions of events per day the instant the data is generated using Heron, an open source streaming engine tailored for large-scale environments. Bill Graham, Avrilia Floratau, and Ashvin Agrawal explore the techniques Heron uses to elastically scale resources in order to handle highly varying loads without sacrificing real-time performance or user experience.
Mistakes were made, but not by us: Lessons from a year of supporting Apache Kafka

Mistakes were made, but not by us: Lessons from a year of supporting Apache Kafka

November 4, 2019

Dustin Cote and Ryan Pridgeon share their experience troubleshooting Apache Kafka in production environments and discuss how to avoid pitfalls like message loss or performance degradation in your environment.
Robot farmers and chefs: In the field and in your kitchen

Robot farmers and chefs: In the field and in your kitchen

November 3, 2019

Food production and preparation have always been labor and capital intensive, but with the internet of things, low-cost sensors, cloud-computing ubiquity, and big data analysis, farmers and chefs are being replaced with connected, big data robotsnot just in the field but also in your kitchen. Tim Gasper explores the tech stack, data science techniques, and use cases driving this revolution.