Java remains a widely used programming language, particularly for enterprise backend systems, due to its robust runtime, portability, and extensive ecosystem of libraries. However, developers face challenges when deploying Java applications in cloud environments like Kubernetes, especially with older frameworks, due to Java's higher memory and CPU requirements and slower startup times. To optimize performance, it is crucial to tune Java applications by selecting appropriate JVM versions, frameworks, and server software, configuring Kubernetes deployments, and adjusting memory and CPU limits. Modern solutions such as GraalVM and frameworks like Quarkus can enhance performance and reduce startup times. Additionally, garbage collection tuning and monitoring tools like Datadog can provide insights into application performance, helping to address issues such as GC pauses and OOM kills. By understanding and applying these strategies, developers can improve the efficiency and scalability of Java applications in containerized environments.