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A Pragmatic Journey from Monolith to Microservices Powered by AI/GenAI
Wed, 23 April
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.
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About the speaker
Suvankar Chakraborty
Cloud Architect & Head of DevOps Engineering, EPAM Systems
Suvankar Chakraborty is a Cloud Architect and Head of DevOps Engineering with over 18 years of experience in multi-cloud architecture, DevOps, and enterprise technology solutions. He specializes in AWS, GCP, OCI, Kubernetes, Terraform, Jenkins, and container orchestration, driving large-scale digital transformation and AI initiatives.
Currently, he leads cloud strategy and DevOps engineering at a confidential organization, where he has successfully implemented scalable cloud architectures, engineered CI/CD pipelines, and optimized cloud infrastructure across multi-cloud environments. His leadership in Kubernetes deployments, cloud automation, and AI-driven solutions has significantly enhanced system reliability, reduced costs, and accelerated digital innovation.
Previously, as Chief Engineer & Head of Containerization, he led hybrid cloud models with Anthos, Kubernetes-GKE, and automation frameworks, while mentoring and managing 60+ engineers. His tenure at Oracle and other leading firms involved enterprise cloud solutions, IT operations, and large-scale automation projects.
Suvankar holds multiple cloud, DevOps, and enterprise architecture certifications, including AWS Cloud Solution Architect, Azure Certified Professional, Oracle Exadata/Exalogic, and PMP. He is a strategic leader, mentor, and technology advocate, committed to building high-performance cloud ecosystems and scalable enterprise solutions.
