Case Study
A leading automotive aftermarket parts provider needed to modernize a large Java Spring Boot application estate that supports professional installers and do-it-yourself customers. The client faced an urgent remediation challenge, with over 100,000 vulnerabilities across 100+ microservices. Infosys led a structured modernization program covering Java and Spring Boot upgrades, Kafka updates, configuration remediation, migration from Jenkins to GitHub Actions, and observability modernization from New Relic to OpenTelemetry. To accelerate delivery, Infosys combined GitHub Copilot, Visual Studio Code plugins, custom agents, and automation scripts to standardize repetitive upgrade and remediation activities across repositories. Custom agents generated unit test cases, helping teams sustain 85%+ code coverage. This AI-assisted approach accelerated remediation, reduced manual effort, and improved code quality at enterprise scale.
150+
automated Databricks workflows deployed as code, enabling scalable and standardized data operations.
12+
plant sites connected through active data pipelines, supporting enterprise-wide data integration.
5+
source system types integrated, including SAP, IP21, GOS, SPF, and document repositories, into a unified data platform.
2+
environments (DEV and PROD) managed from a single codebase, ensuring consistent and streamlined deployments.
Key Challenges
- Lack of a standardized Java Spring Boot remediation process.
- 100,000+ vulnerabilities across 100+ microservices.
- Tight remediation timelines and high delivery expectations.
- Manual upgrades were repetitive, time intensive, and error prone.
- Dependency variations complicated bulk upgrade execution.
- Maintaining code coverage during remediation was challenging.
Accelerate Java Spring Boot vulnerability remediation with structured automation and AI-assisted engineering.
Talk To Experts
Infosys Approach
Assessed the application landscape, remediation process, and SME ownership across service areas.
Grouped services by dependency to prioritize remediation and streamline execution planning.
Enabled GitHub Copilot for developers to accelerate coding, reviews, and unit test generation.
Partnered with internal CoE teams to identify reusable automation for common upgrade steps.
Implemented Java upgrade plugins and custom agents for Kafka, OpenTelemetry, vulnerability, and code-smell remediation.
Developed automation scripts to execute common changes across multiple services and repositories.
Tracked progress, risks, blockers, and quality checkpoints through daily standups and weekly client governance reviews.
The Solution
AI-assisted Java Spring Boot upgrades and vulnerability remediation using GitHub Copilot, VS Code plugins, and custom agents.
- Used GitHub Copilot to accelerate coding, code reviews, unit test generation, and developer-led remediation.
- Identified Java upgrade plugins in Visual Studio Code to speed version uplift activities.
- Implemented pipeline-based automation to apply bulk repository changes and prepare codebases for remediation.
- Created custom agents for Java, Spring Boot, and Kafka upgrades using structured instruction files.
- Built a dedicated agent to generate unit tests and improve automated test coverage.
- Developed batch automation scripts to execute selected upgrade and remediation tasks across repositories.
Business Outcomes
Accelerated vulnerability remediation across Java Spring Boot merchandising applications.
Achieved 55% effort savings through automated unit test generation.
Delivered 29% effort savings using upgrade plugins, custom agents, and automation scripts.
Improved remediation consistency and scalability across multiple repositories.
Strengthened code quality through automated test generation and higher coverage.
Reduced manual dependency with repeatable, pipeline-driven remediation execution.
Benefits
AI-assisted remediation improved productivity, quality, and scalability across Java Spring Boot modernization.
Delivered 55% effort savings through automated unit test generation.
Achieved 29% savings using plugins, agents, and automation scripts.
Accelerated remediation across large-scale Java microservices repositories.
Improved code quality through consistent test coverage gains.
Reduced manual remediation effort with repeatable pipeline execution.
Enabled scalable modernization with reusable automation and custom agents.
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