10 June 2025
Java™ is one of the most widely used programming languages globally, powering applications across various platforms. It’s estimated that over three billion devices run Java applications, with nearly 70% of organizations reporting that more than half of their applications rely on Java.
While Java remains a cornerstone of enterprise software development, many businesses still rely on older Java versions and monolithic architectures. This gap leads to performance bottlenecks, security vulnerabilities and operational inefficiencies. Open-source library support for Java 8 ends in 2026, which presents an urgent challenge for enterprises with extensive Java-based applications.
Beyond technical constraints, organizations face an overwhelming USD 1.52 trillion technical debt problem, with a significant portion stemming from maintaining legacy applications.
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Despite the urgent need to modernize Java applications to meet evolving business demands, enterprises face multiple challenges that slow down transformation efforts.
− Security and compliance risks: Legacy Java applications often contain outdated dependencies, making them vulnerable to cyberthreats. Unpatched Java vulnerabilities, such as Log4j, can expose enterprises to significant security risks when left unresolved.
− Performance and operational inefficiencies: Older Java applications frequently experience sluggish performance, downtime and scaling issues. The average cost of IT downtime is USD 5,600 per minute, with 59% of Fortune 500 companies experiencing at least 1.6 hours of unplanned downtime per week. Also, for 10% of small and medium-sized businesses (SMBs), downtime costs exceed USD 50,000 per hour.
− Complexity of legacy code and technical debt: Modernizing Java applications requires addressing accumulated technical debt, including outdated libraries, inefficient coding patterns and redundant modules. Refactoring legacy Java code manually is time-intensive and prone to errors, making AI-powered assistance not just beneficial, but essential.
− Limited cloud integration and containerization challenges: Many legacy Java applications were developed in an era before cloud native architectures. Without modern frameworks such as Spring Boot or Quarkus, enterprises struggle to migrate applications to cloud environments.
IBM® watsonx Code Assistant™ accelerates the modernization process by leveraging Gen AI-driven automation to transform legacy Java applications efficiently.
− AI-generated high-quality Java code: IBM watsonx Code Assistant, powered by Java fine-tuned Granite code models, generates optimized Java code, reducing manual effort while ensuring performance and scalability, accelerating development cycles without compromising code integrity.
− Automated code refactoring and upgrade to latest Java versions: IBM watsonx Code Assistant identifies legacy code components that need modernization and provides automated refactoring capabilities. This allows enterprises a smooth transition to the latest Java versions while maintaining compatibility with new platforms and frameworks.
− Streamlined application lifecycle and CI/CD integration: The tool integrates seamlessly with continuous integration and continuous deployment (CI/CD) pipelines, facilitating continuous integration, automated testing and faster deployments. This helps reduce time-to-market for enterprise applications.
− Security enhancement and risk mitigation: IBM watsonx Code Assistant helps enterprises strengthen application security by identifying and eliminating outdated dependencies, integrating encryption protocols and helping to ensure compliance with industry security standards.
− Cloud-native enablement and containerization support: IBM watsonx Code Assistant simplifies migration to microservices architectures. This facilitates containerized deployment on cloud environments and helps ensure that enterprises maximize the benefits of cloud adoption.
The future of enterprise applications lies in agility, security and efficiency. IBM watsonx Code Assistant empowers businesses to modernize their Java applications, while reducing technical debt and operational complexity.