Hewlett Packard Enterprise & HCL Tech Exploring Integration of Edge with Cloud and Hybrid Solutions & Harnessing GenAI Workloads
Abstract: The convergence of edge computing with cloud and hybrid solutions presents an opportunity to achieve scalable, efficient processing with the flexibility and resilience needed in diverse business environments. Leveraging edge computing for real-time data processing, combined with cloud storage and analytics, can optimize performance and cost-effectiveness. However, this integration poses challenges, such as ensuring data privacy, maintaining reliability in remote deployments, and managing scalability to meet growing data volumes and user demands.
Simultaneously, the potential of GenAI workloads to enhance productivity, personalize customer experiences, and streamline operations through advanced analytics and automation is immense. Yet, businesses must address data ownership, compliance, and the integration of AI solutions into existing infrastructures and corporate cultures.
This exclusive event, held at Restaurant Käfer-Schänke, Munich, will highlight the promise and power of integrating edge computing with cloud and hybrid solutions and harnessing GenAI workloads. Join us to gain insights and strategies to unlock the full potential of these technologies.
Discussion Points:
- Security Concerns: How does your company address security concerns when integrating edge devices with cloud infrastructure, especially regarding data privacy and protection?
- Reliability Strategies: Elaborate on the strategies your company employs to ensure the reliability of edge and cloud components in hybrid solutions, particularly in remote or challenging environments.
- Scalability Management: What measures do you take to manage scalability to accommodate increasing data volumes and user demands?
- Data Privacy in GenAI: How have you navigated concerns regarding data privacy and ownership when deploying GenAI solutions?
- Integration Challenges: What challenges have you encountered in integrating and adopting GenAI solutions into existing workflows, infrastructure, and corporate culture? How do you address them?