Automating CI/CD for a European E-Commerce Platform, Reducing Deployment Time by 40%

Client Profile

A Netherlands-based e-commerce company with over 200 employees, operating an online retail platform serving customers across Europe.

Industry E-commerce
Location Amsterdam, Netherlands
Company Size 200+ employees
Duration 8 months

Technologies Used

GitLab CI Jenkins Docker

Business Challenge

The client’s development team was shipping product updates multiple times per week, but manual deployment processes were slowing delivery and introducing bugs into production. Monolithic build scripts and inconsistent environments meant that builds took too long, tests were unreliable, and pre-deployment validation was minimal. Unplanned rollbacks were frequent, consuming engineering time and eroding confidence in the release process.

Solution

The client’s existing pipelines were a mix of manual scripts and legacy Jenkins jobs. We consolidated everything into GitLab CI as the single pipeline platform, since the team was already using GitLab for version control. Legacy Jenkins jobs were migrated and decommissioned. All application services were containerised with Docker to eliminate environment inconsistency. We introduced automated unit, integration, and end-to-end tests as mandatory quality gates before any deployment could proceed. Test suites were parallelised across multiple GitLab CI runners to reduce pipeline duration. Dependency and build layer caching was implemented to eliminate redundant work between pipeline runs.

Outcome

Build and test times were reduced by 40%. Unplanned rollbacks dropped by 60% due to comprehensive pre-deployment testing. The engineering team shifted from reactive bug-fixing to proactive feature development, with significantly faster feedback loops on every commit.

Process

1

Pipeline Analysis

Audited the existing CI/CD process, identifying monolithic build scripts and inconsistent environments as the primary causes of slow builds and unreliable test results.

2

Testing Gap Assessment

Identified the absence of systematic pre-deployment testing. Bugs were reaching production because there were no automated quality gates between code commit and deployment.

3

Containerisation

Introduced Docker to standardise build and runtime environments. Every service now builds and runs in an identical container, eliminating environment-related failures.

4

Automated Test Suite

Implemented automated unit, integration, and end-to-end tests as mandatory pipeline stages. No deployment proceeds without passing all quality gates.

5

Parallel Test Execution

Distributed test execution across multiple parallel runners, reducing the critical path of the pipeline and delivering faster feedback to developers.

6

Build Caching

Implemented dependency and Docker layer caching strategies, cutting redundant build work and further reducing pipeline execution time.

Conclusion

Automated CI/CD with enforced quality gates transformed the client’s release process from a source of risk into a reliable, predictable delivery pipeline — enabling faster iteration without sacrificing stability.

Ready to Transform Your Infrastructure?

Book a free consultation with our team to discuss your DevOps and cloud engineering needs.