Executive Summary

Zonevoice, a leading telecommunications provider, partnered with Zero&One to modernize its legacy Java applications and unlock scalability, performance, and maintainability. Facing the limitations of outdated Java frameworks and unsupported libraries, Zonevoice sought a modernization approach that went beyond mere migration, focusing on improving developer productivity, operational efficiency, and future-proofing its platform. Zero&One leveraged its Java Modernization expertise, combined with AI-Powered SDLC (iCODE) accelerators using AWS generative AI services to deliver an automated AI-assisted modernization solution. The project included assessment, refactoring, testing, and secure deployment, resulting in faster release cycles, improved system reliability, and reduced operational overhead.

Customer Challenge

Zonevoice was experiencing several challenges due to its legacy Java applications. The applications were built on outdated Java versions, creating performance bottlenecks and exposing the system to security risks. Many third-party libraries were no longer supported, which increased maintenance complexity and added significant technical debt. Development cycles slowed because of manual refactoring, inconsistent coding patterns, and the absence of automation. As a result, the platform struggled to scale efficiently to meet the growing customer demand for voice, messaging, and cloud communication services.

Key Modernization Need

Zonevoice required a structured modernization strategy to address its evolving needs. The plan had to progressively upgrade applications from Java 8 through Java 17 and ultimately to Java 21, ensuring compatibility at each stage. It also needed to include automated code refactoring and optimization to minimize manual effort, the replacement of unsupported libraries to strengthen security, and the implementation of processes that would enable faster development and deployment cycles while reducing risk.

Why Zero&One and AWS

Zero&One, an AWS Premier Consulting Partner with deep expertise in Java modernization and recognized GenAI Competency, delivers a proven modernization approach that blends automation, AI-driven refactoring, and cloud-native deployment. By leveraging AWS generative AI services such as Amazon Q Developer, Zero&One ensures secure, scalable, and resilient operations. Through the Assess, Transform, and Modernize (ATM) framework, the team automates code assessment, refactoring, and testing significantly reducing manual effort while enhancing code quality, maintainability, and long-term performance.

The Solution

Zero&One implemented a structured Java modernization approach using the Assess, Transform, and Modernize (ATM) framework. The process began with an automated assessment in which ATM scanned the legacy Java applications to identify deprecated APIs, unsupported libraries, and performance bottlenecks, while mapping technical debt and upgrade risks for each module. Refactoring followed, with automated updates that transformed Java 8 code to Java 21, replaced unsupported libraries and APIs, and introduced CI/CD pipelines to support continuous integration, automated testing, and deployment. Testing and validation ensured functional parity through automated unit, integration, and regression tests, accompanied by performance benchmarks that confirmed faster execution and reduced resource usage. Finally, the applications were deployed to AWS with role-based access control, encryption, and monitoring through CloudWatch, along with comprehensive logging for auditability and operational dashboards that provided real-time visibility into application performance and cost optimization.

Solution Architecture

The existing architecture required no major redesign. The only addition was a GitHub Action pipeline integrated with ArgoCD to automate builds and deployments for the Java modernization. To accelerate every phase of the project, Zero&One drew on the AWS AI-Powered SDLC reference architecture from AWS Samples.

Sample AI-Powered SDLC Patterns with AWS.

By adapting these proven patterns into our own internal accelerators, the team streamlined requirements gathering, architecture validation, automated coding, development, and deployment. This approach significantly reduced manual effort and enabled the modernization to be completed in roughly one week, compared with the typical multi-month timeline.

Key KPI's

Key performance indicators highlighted the impact of the modernization initiative.

Upgrade efficiency improved dramatically, with the time to upgrade a single service from Spring Boot 2.0.7 to 3.4.2 reduced to under six hours including code analysis, refactoring, build, and validation compared to about a full week required by traditional manual processes that involve extensive research and dependency resolution.

Modernization speed also increased, as AWS patterns and accelerators enabled a full solution to be modernized in just one week, a task that would typically take around two months if done manually.

Documentation, once lengthy and error-prone with legacy methods, was generated instantly as part of the modernization workflow.

Developer productivity rose as automated refactoring cut manual effort by roughly forty percent, while deployment automation and CI/CD pipelines reduced the time-to-market for new features by half.

Operational excellence improved as well, with enhanced monitoring, scalability, and security posture across the platform.

Results and Benefits

The modernization of Zonevoice’s legacy Java applications—from Java 8 through 17 to 21—combined with AI-powered accelerators and AWS-native tooling, delivered significant results. The initiative enabled faster delivery of new features with a 50% reduction in time-to-market, established a future-proof architecture that supports easier scaling and integration with emerging services, and improved developer productivity while reducing technical debt. Moreover, the entire modernization was completed in a fraction of the traditional timelines and included instant documentation support.