Track: Workhorse Languages, Not Called Java


Day of week:

What does Python, Ruby, Go, and R have in common? They are all workhorses languages that modern companies are using to solve problems that just a few years ago they would have reached for Java to use. Come learn how Ruby is powering Infrastructure, Python is driving ML/Automation, and much more. Workhorse Languages Not Called Java is all about the richness in languages today. 

Track Host:
Werner Schuster
InfoQ Lead Editor for Functional Programming
Werner Schuster (@murphee) sometimes writes software, sometimes interviews folks about software. His recent interests are languages, performance optimisation, monitoring, and how to make software suck less using computer science research.
10:35am - 11:25am

by Richard Croucher
VP of High Frequency Engineering @Barclays

Financial Services run arguably the most complex applications, with major institutions each running thousands of different applications. The most challenging and performance critical are the High Frequency Trading systems used in the Equities markets. This session will describe the application environments, design patterns and programming languages commonly deployed across Financial Services including Investment Banks and Hedge Funds.

11:50am - 12:40pm

by Matt Long
Dev-in-test @OpenCredo

With the rise of DevOps, programmable infrastructure is reaching widespread adoption. However, although automated testing of software is becoming ever more common, the same cannot be said with testing the target deployment environment itself. With microservices making our deployments more and more complex, we can no longer afford to ignore this type of testing. This talk will take a tour through some approaches to environment infrastructure testing that we have...

1:40pm - 2:30pm

Open Space
2:55pm - 3:45pm

by Colin Hemmings
CTO and Co-founder @Outlyer

Outlyer is a SaaS infrastructure monitoring tool. We process and store time-series data, which is currently at 100K points per second and growing.

To do the grunt work of processing and storing the growing mass of data, we originally started out with Node.JS—quick to build and time-saving. About a year into using it, we started to reach the limits of Node, so we began to investigate a more appropriate technology. We looked...

4:10pm - 5:00pm

5:25pm - 6:15pm