ASML: self-service CI in Stage Position Measurement, 300+ engineering hours a year back

Self-service CI, one view of release readiness, and the same CI flow for multiple teams

Client
ASML, semiconductor engineering, lithography systems
Team
Stage Position Measurement
Stack
Jenkins pipelines in Groovy, Python, Bash, SQL, Git, ClearCase, Linux, Google Cloud Platform
Role
Engineer building the CI pipelines
Duration
1 year

The situation

ASML builds lithography systems where integration speed and test reliability decide delivery. In Stage Position Measurement, engineers ran repeatable integration steps by hand, and there was no single place to judge release readiness.

Before and after

Before After
Integration steps run by hand one self-service CI pipeline
Release readiness no single place to judge it one Python and SQL reporting view of production machine test results
CI across teams and test environments not standardized standardized CI flows for multiple teams
Production machine tests on ASML's own test environments offload of selected tests to Google Cloud Platform started
Engineering time on this work 300+ hours a year back
Before and after diagram of integration in ASML Stage Position Measurement. Before: integration steps run by hand, and no single place to judge release readiness. After: one self-service CI pipeline and one release-readiness view. Before Integration steps run by hand ? No single place to judge release readiness After One self-service CI pipeline One release-readiness view

The decision they faced

Keep running integration steps by hand and judging release readiness from scattered test results, or build one self-service CI flow with one readiness view.

What was built

A self-service CI pipeline for the Stage Position Measurement domain.
One Python and SQL reporting view of production machine test results, for faster release-readiness decisions.
CI automation tested and rolled out across proprietary ASML test environments, standardizing the flows of multiple teams.
The first offload of selected production machine tests to Google Cloud Platform, to raise throughput and shorten feedback.

What it took from their team

Reviews and approval from the team's other DevOps engineers: about 2 to 3 hours a week in meetings and reviews.

“It was a pleasure for the team and me to work with Mateusz and I wouldn’t hesitate to hire him again.”

ASML Maikel Jansen Group leader SW Stage Position and Measurement

“Mateusz created designs for automation of work processes, managed external dependencies and solved tooling prerequisites needed to implement the designs, build automations from the designs in Groovy (Jenkins pipeline scripts), Python and Shell script (Bash), tested the automations at different proprietary ASML test environments and worked at Linux systems in Git and ClearCase based development environments.

He gained experience about integration procedures and configuration management as applied in a large scale company. It was a pleasure for the team and me to work with Mateusz and I wouldn’t hesitate to hire him again.”

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Talk to the engineer

"As an engineer, I know the challenges in software delivery from both business and technical views. I built Expeditious Software to remove bottlenecks and manual work, and to deliver measurable improvements in speed and reliability."

Mateusz Ulas, founder of Expeditious Software

Mateusz Ulas

Founder and platform engineer