
023 Is DevOps the Killer of traditional Performance Engineering?
12/05/16 • 32 min
Listen to our conversation where we also discuss how these roles have changed in organizations we recently interacted with.
Listen to our conversation where we also discuss how these roles have changed in organizations we recently interacted with.
Previous Episode

022 Latest trends in Software Feature Development: A/B Tests, Canary Releases, Feedback Loops
In Part II with Finn Lorbeer (@finnlorbeer) from Thoughtworks we discuss some of the new approaches when implementing new software features. How can we build the right thing the right way for our end users?
Feature development should start with UX wireframes to get feedback from end users before writing a single line of code. Feature teams then need to define and implement feedback loops to understand how features operate and are used in production. We also discuss the power of A/B testing and canary releases as it allows teams to “experiment” on new ideas and thanks to close feedback loops will quickly learn on how end users are accepting it.
*****Related Links:******
Process Automation and Continuous Delivery at OTTO.de
https://dev.otto.de/2015/11/24/process-automation-and-continuous-delivery-at-otto-de/
Are we only Test Manager?
http://www.lor.beer/are-we-only-test-manager/
Sind wir wirklich nur Testmanagerinnen?
https://dev.otto.de/2016/06/08/sind-wir-wirklich-nur-testmanagerinnen/
Next Episode

024 What the hell is “Continuous Acceleration of Performance”?
Mark Tomlinson, still a veteran and performance god, is enlightening us on his concept of Continuous Acceleration of Performance. Continuous Delivery is all about getting faster feedback from code changes as code gets deployed faster in smaller increments to the end user. One aspect that is often left out is feedback on performance metrics and behavior. In the “old days” performance feedback was given very late – either in the load testing phase at the end of the project lifecycle or even as late as when it hits production. That could be too late and it makes it hard to fix the root cause.
Listen to our conversation on how to accelerate performance related feedback loops without getting overwhelmed with too much data!
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