Presentation by Scott Logic's Frances Bromley and Ciara Gardiner at the South West Test meetup on 9 July 2019, summarising their learnings from a project to develop a tool which performance tests DataHelix. DataHelix is an open source product to automate the creation of usable and representative sample data for testing and development purposes. Find out more and contribute to its development at https://github.com/finos/datahelix

1. Performance testing DataHelix
Ciara Gardiner and Frances Bromley

2. “To investigate the use of Docker,
continuous integration and cloud
technology to performance test the
Scott Logic DataHelix”
Goals

3. A data generation tool that creates representative test and
simulation data based on a profile.
It allows the generation of data that both conforms to and
violates the profile, with the goal of aiding testing and
validation.
What is the DataHelix?

4. What’s in a profile?

5. Technical decisions
What should
we test in the
DataHelix?
Where did
we want our
tool to live?
How should
we trigger
our CI?

6. Open source tool to help you package, deploy and run your application.
It uses images that at runtime are containers.
A container contains everything you need to run your application.
What is Docker?

7. Portable
Open source
Shareable
Isolated
Dependable
Small footprint
Microservice architecture
Why Docker?

8. How did we use Docker ?

9. Continuous Integration

10. YML

11. Artifacts

12. “Cloud computing is the on-demand availability of
computer system resources”
Allows us to dictate specifics about the type of
computer the experiment was being run in
Cloud

13. Metrics
Variation in time baselines for a commit.
Input remains the same.
Output is not verified.

14. What did our app look like?

15. What did we learn?
Docker
Circle CI
How to approach performance testing

16. Going forward
● Remove Docker building from within app.
● Deployment onto Cloud to improve cloud knowledge and define the size of the
computers on which it’s being run.
● Set CI up so it updates any time there’s a change to the DataHelix repo.

17. Questions?