As businesses evolve to keep pace with technological advancements, they are increasingly adopting cloud-native and open-source technologies to enhance scalability, agility, and innovation. With IT ecosystems growing more complex, ensuring seamless workload management, security, and compliance has become a top priority.
In a knowledge exchange session, curated by CORE Media in association with Oracle, CIOs, and digital leaders explored how enterprises can optimize their hybrid and multi-cloud strategies using OpenShift and Oracle Cloud VMware Solution (OCVS) to ensure seamless workload management, enhanced security, and regulatory compliance.
Anoop Mathur, Founder, CORE Media, Premal Munshi, Senior Sales Director – Tech Cloud, Oracle, and Unnikrishna Panicker, Director - Cloud Engineering, Oracle, shared their perspectives on the role of open-source AI frameworks in accelerating innovation, improving automation, and enabling real-time data-driven decision-making.
Some of the key points highlighted by CIOs and digital leaders who attended the discussion were:
- Optimizing Hybrid & Multi-Cloud Strategies With hybrid cloud deployments becoming the norm, CIOs examined how OpenShift and Oracle Cloud VMware Solution (OCVS) facilitate seamless workload management while ensuring agility, security, and compliance. They also shared best practices for integrating legacy systems with modern cloud platforms to enhance operational efficiency.
- Harnessing Open-Source AI for Innovation The discussion highlighted how open-source AI frameworks and containerized platforms are accelerating innovation, improving automation, and enabling real-time data-driven decision-making. Leaders emphasized the need for open collaboration and interoperability to drive continuous advancements in AI capabilities.
- Striking the Right Balance Between Performance, Cost, and Scalability
Finding cost-effective ways to maintain high performance and scalability was a major focus, with experts sharing strategies to optimize infrastructure expenses while meeting evolving data and AI demands. They also explored how predictive analytics and automation can maximize resource utilization without compromising efficiency.
