Article contents
Decoding Cloud-Native Architecture: Best Practices for Modernizing Legacy Applications
Abstract
Cloud-native architecture represents a transformative paradigm shift in application development and deployment, significantly transforming how organizations conceptualize, build, and operate software systems in the digital era. This comprehensive article explores the multifaceted journey from traditional monolithic architectures to modern cloud-native ecosystems, revealing both the compelling benefits and complex challenges organizations face during this transition. The architectural evolution spans microservices decomposition, containerization, and orchestration platforms that collectively enable unprecedented scalability, resilience, and operational agility. Organizations worldwide are increasingly recognizing that cloud-native transformation extends beyond mere technological adoption, requiring fundamental shifts in organizational culture, operational practices, and strategic thinking. The transition from legacy systems presents significant technical obstacles, including tight coupling, outdated technology stacks, and documentation degradation, while organizational challenges manifest through skill gaps, cultural resistance, and the need for new collaborative models. Strategic modernization demands a balanced, iterative paradigm that prioritizes business value delivery while minimizing disruption to critical operations. Best practices emerging from successful transformations emphasize the integration of DevOps practices, security-first principles, and continuous improvement cultures that align technical capabilities with business objectives. The synthesis of these elements creates a comprehensive framework for organizations navigating the complex path from legacy constraints to cloud-native possibilities, ultimately enabling them to achieve enhanced operational efficiency, accelerated innovation cycles, and improved competitive positioning in an increasingly digital marketplace.
Article information
Journal
Journal of Computer Science and Technology Studies
Volume (Issue)
7 (7)
Pages
486-492
Published
Copyright
Open access

This work is licensed under a Creative Commons Attribution 4.0 International License.