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शुरू होता है 5 June 2026 20:48

समाप्त होता है 5 June 2026

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The Explorer's Guide to Cloud Native GenAI Platform Engineering

Immerse yourself in the world of cloud native generative AI platform engineering with this comprehensive guide. Discover step-by-step methodologies for setting up AI infrastructure on Kubernetes, starting from minimal viable configurations and advancing to sophisticated features. Learn about integrating LLM gateways and vector databases to enh.
CNCF [Cloud Native Computing Foundation] via YouTube

CNCF [Cloud Native Computing Foundation]

6076 कोर्स


31 minutes

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वैकल्पिक अपग्रेड उपलब्ध है

अवलोकन

Immerse yourself in the world of cloud native generative AI platform engineering with this comprehensive guide. Discover step-by-step methodologies for setting up AI infrastructure on Kubernetes, starting from minimal viable configurations and advancing to sophisticated features.

Learn about integrating LLM gateways and vector databases to enhance your AI capabilities. Gain insights into implementing load balancing strategies and optimizing performance, ensuring your AI solutions operate efficiently and effectively.

Available to stream on YouTube, this course bridges the gap between theoretical concepts and practical execution in the realm of artificial intelligence and computer science.

पाठ्यक्रम

  • Introduction to Cloud Native GenAI
  • Overview of Cloud Native and Generative AI
    The role of Kubernetes in AI Infrastructure
  • Setting Up a Minimal Viable GenAI Platform
  • Installing and Configuring Kubernetes
    Deployment of Basic AI Services
  • Exploring Kubernetes for GenAI
  • Kubernetes Concepts: Pods, Nodes, and Services
    Orchestration of AI Workloads
  • Building and Integrating LLM Gateways
  • Understanding LLM (Large Language Models) Architecture
    Deploying and Configuring LLM Gateways on Kubernetes
  • Implementing Vector Databases
  • Introduction to Vector Databases
    Setting Up and Using Vector Store for AI Applications
  • Load Balancing in GenAI Platforms
  • Load Balancing Techniques and Tools
    Best Practices for Traffic Management in AI Services
  • Performance Optimization Techniques
  • Monitoring and Profiling AI Workloads
    Techniques for Improving AI Application Performance
  • Advanced Features and Enhancements
  • Utilizing Auto-scaling and Self-healing Capabilities
    Security Best Practices for GenAI Platforms
  • Case Studies and Real-World Applications
  • Examples of Successful Cloud Native GenAI Implementations
    Lessons Learned and Best Practices
  • Future Trends in Cloud Native GenAI
  • Emerging Technologies and Innovations
    Preparing for the Future of AI Infrastructure
  • Conclusion and Roadmap Beyond the Course
  • Recap of Key Learnings
    Resources for Further Study and Community Involvement

विषय

Computer Science