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v2 Continuous performance validation

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Daniel Moll

on 14 June 2017

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Transcript of v2 Continuous performance validation

Continuous performance validation
Daniel Moll
Agenda
Performance testing done by specialists -> specialists are scarce -> dependencies in sprint planning

Continuous performance validation
Continuous performance validation
Maximize feedback, minimize effort.

Automation
Automated benchmarking

Benchmarking
Requirements
Benchmark to previous build
Benchmark to fixed baseline

Automate everything!
Tooling
SUT
check in
check out
traffic
load metrics
resource metrics
metric
data
analyze results
benchmark
results
Integrates well with development tools (Maven, Jenkins, Bamboo, git)
Script all in code, no GUI
Edit script in IDE of choice
Performance tests part of code base
Clean, flexible DSL that developers pick up easily
Template script from Maven archetype
Frequent feedback on performance, starting early in sprint.
Team creates and maintains scripts.
If it hurts, do it more often!
Questions?
https://github.com/dmoll1974/targets-io
dmoll1974@gmail.com
https://www.linkedin.com/in/dmoll1974

Throughput time performance tests
Defects found just before go-live result in no-go
Introduction
Waterfall vs Agile
Continuous performance validation
Tooling
Demo
Challenges
Developer-friendly!
Automated test execution from CI/CD pipeline
Automated test analysis / benchmarking
Automated
reporting
of results
Key benefits for teams
Adds performance to the feedback loop
Based on open source components
Maximizes feedback, minimizes effort
Provides performance test autonomy
logs
logs
Waterfall
Agile

Waterfall vs Agile
Two/three releases per year
Executed at the end of the project, just before go-live
Hand over to ops.
Tests executed by specialists
Continuous integration
Shorter time to market without compromising quality
Autonomous teams
2 week sprints, frequent releases
2 - 3 weeks throughput time
Full transcript