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A Pragmatic Journey from Monolith to Microservices Powered by AI/GenAI
Originally aired:
About the Session
Migrating from a monolithic architecture to microservices is a complex process that involves managing dependencies, ensuring data consistency, and minimizing operational overhead. However, the emergence of AI and GenAI-powered tools is revolutionizing this transformation, making it more efficient, scalable, and intelligent.
This session explores how AI accelerates the microservices transition by automating code transformation, optimizing service boundaries, enhancing observability, and fortifying security. We’ll dive into real-world strategies where AI-powered insights help decompose monoliths into well-structured microservices while ensuring performance, security, and cost-efficiency.
Key Takeaways
- AI-powered code analysis for identifying service boundaries and optimizing decomposition.
- Automated code transformation using GenAI for refactoring and API boundary definition.
- Observability & monitoring enhanced by AI-driven anomaly detection and log analysis.
- Security & compliance with AI-powered vulnerability detection and enforcement of best practices.
- Continuous optimization using predictive scaling, auto-healing, and cost efficiency mechanisms.
- Future outlook: How AI-driven architectures will make microservices more autonomous and self-optimizing.
Target Audience
This session is designed for software architects, engineering leaders, DevOps professionals, and developers who are working on modernizing legacy systems or adopting microservices. It is also valuable for AI/ML practitioners interested in leveraging AI-powered automation for software architecture transformation.
A Pragmatic Journey from Monolith to Microservices Powered by AI/GenAI
Originally aired:
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