AI and OpenStack for Resilient Infrastructure by Avani Rampersad
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The document discusses the integration of AI with OpenStack projects to support resilient infrastructure, highlighting key components like Nova, Neutron, Cinder, and Swift for managing AI workloads. It also mentions additional resources such as TensorFlow, PyTorch, Jupyter, and Apache Spark, along with the benefits of containerized workloads and Ceph storage for AI applications. Notable users of OpenStack for AI workloads include NVIDIA, Red Hat, and Pypestream, showcasing the platform's scalability, flexibility, and cost-effectiveness.
AI and OpenStack for Resilient Infrastructure by Avani Rampersad
- 1. Embracing AI Transformation: OpenStack Projects and Open Source Tools for Resilient Infrastructure OpenMetal.io Avani Rampersad Cloud & FinOps Product Manager
- 2. User friendly AI that everyone can use such as Gemini and Chat GPT has AI on the tip of everyone’s tongue. OpenStack x AI
- 3. ● Compute Resources ● Memory ● Storage ● Networking ● Software Framework and Libraries Resource Needed For AI Workloads
- 4. How do OpenStack projects meet the needs of AI workloads? OpenStack & AI Scalability & Flexibility
- 5. What OpenStack projects are key for cloud computing infrastructure designed to host AI workloads? OpenStack & AI ❖ Nova ❖ Neutron ❖ Cinder ❖ Swift ❖ Heat
- 6. OpenMetal.io Nova for AI ● Compute ● Memory
- 7. OpenMetal.io Neutron for AI ● Networking
- 8. OpenMetal.io Swift for AI ● Object Storage
- 9. OpenMetal.io Cinder for AI ● Block Storage
- 10. OpenMetal.io Heat for AI ● Automation
- 11. Additional Resources for AI …. ● TensorFlow ● PyTorch ● Jupyter ● Apache Spark
- 12. Additional Resources for AI …. TensorFlow is an open source software library developed by Google for building and training machine learning models.
- 13. Additional Resources for AI …. PyTorch is another open source machine learning library that’s becoming increasingly popular in AI applications,
- 14. Additional Resources for AI …. Jupyter is an open source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.
- 15. Additional Resources for AI …. Apache Spark is an open source distributed computing system.
- 16. Containerized Workloads Key Benefits of K8s for AI: ● Isolation & Portability ● Scalability ● Resource Utilization ● High Availability and Fault Tolerance ● Service Discover and Load Balancing ● Infrastructure Flexibility
- 17. Ceph Storage Key Benefits of Ceph for AI: ● Scalability ● Redundancy & Reliability ● Flexibility ● Performance ● Integration with AI frameworks
- 18. Who is using OpenStack for AI workloads? Nvidia uses OpenStack Swift Storage as part of their cutting edge AI and ML data management.
- 19. Who is using OpenStack for AI workloads? RedHat uses OpenStack to support the training of their ML programs. ● Spark allows for scalable data processing, ● Sahara streamlines data access and cluster management.
- 20. Who is using OpenStack for AI workloads? Pypestream a self-service automation platform that transforms how businesses engage and empower their customers uses OpenMetal’s OpenStack deployment
- 21. Pypestream open source infrastructure Pypestream had OpenMetal build and deploy a cloud for their DevOps infrastructure that included: ● A private Cloud Core ● A Ceph network distributed storage cluster. ● OpenStack API integrations
- 22. Key Open Source Advantages: ● Scalability ● Flexibility ● Cost Effectiveness ● Storage Options
- 23. Test OpenStack with OpenMetal https://openmetal.io/free-trial/
- 24. Contact Me Social: Avani Rampersad Email: [email protected] Website: OpenMetal.io