Advanced Edge Computing

• Familiarity with cloud computing and networking

Audience

• Business Analysts
• Product managers
• Developers

Edge computing is a form of distributed computing that brings data storage and processing closer to the end user. It reduces latency and conserves network resources by utilizing edge servers instead of the traditional centralized cloud.

This instructor-led, live training (online or onsite) explores the next level of edge computing technology, focusing on innovative applications and solutions for modern businesses. This instructor-led, live training dives deep into complex architectures, real-world integration challenges, and emerging trends in edge computing. Participants will gain hands-on experience with advanced tools and techniques to design, deploy, and manage edge computing solutions effectively.

By the end of this training, participants will be able to:

• Design and implement advanced edge computing architectures.
• Integrate edge computing solutions with existing IT infrastructure.
• Address real-world challenges in deploying edge computing in various industry sectors.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

• Overview of Edge Computing
  • Definition and evolution of edge computing
  • Key drivers and industry trends
  • Comparative analysis with traditional cloud computing models
• Edge Computing vs. Cloud Computing
  • Technical differences and operational implications
  • Use case scenarios: Where edge outperforms cloud and vice versa
  • Cost-benefit analysis for businesses
• Real-world Use Cases of Edge Computing
  • Smart cities and IoT
  • Autonomous vehicles
  • Industrial automation and predictive maintenance
• Architecture of Edge Computing Systems
  • Components of edge architecture (devices, gateways, edge servers)
  • Design principles and deployment models
  • Challenges in scalability and interoperability
• Networking for Edge Computing
  • Networking requirements and challenges at the edge
  • Role of 5G and its impact on edge computing solutions
  • Secure and efficient data transfer protocols
• Security and Privacy in Edge Computing
  • Potential vulnerabilities and threat models
  • Encryption, authentication, and authorization mechanisms
  • Compliance with data protection regulations (e.g., GDPR)
• Managing and Monitoring Edge Computing Environments
  • Tools and strategies for remote management
  • Performance monitoring and anomaly detection
  • Update and patch management for edge devices
• Future Trends and Challenges in Edge Computing
  • Emerging technologies influencing edge computing (e.g., AI, blockchain)
  • Overcoming technical and regulatory challenges
  • Future outlook and potential market growth areas