How We Built Our AI Lab: A Practical Walkthrough
About the webinar
When it comes to AI and GenAI, the quality and performance of your models are only as good as the infrastructure they’re built on. Unlike traditional software applications, AI models are incredibly resource-intensive.
While cloud resources provide easy access to powerful computing tools and promise scalability, they often come with hidden costs, performance variability, and latency issues. With a physical setup, you gain complete control over your hardware and software environment, allowing consistent, high-performance computing. At InfraCloud, we recognized these benefits early on, which is why we invested in building our own AI lab.
For AI experimentation, prototyping, and innovation, an AI lab is a no-brainer, but setting it up could be a mess. You may face challenges around hardware/software environments, compatibility, and data management. We used Kubernetes to simplify the management of multiple AI models and workloads running simultaneously across different environments. We also leveraged other cloud native technologies to enhance the observability, scalability, and reliability of the AI lab.
In this webinar, Sanket, Vishal, and Atul will give you a practical walkthrough of building an AI lab, drawing from their hands-on experience in setting one up.
What to expect
- Importance of infrastructure for AI apps: Learn the importance of infrastructure in making any AI application.
- Hardware and software: Learn about the specialized hardware and software environments required to develop infrastructure to make AI apps.
- Kubernetes & cloud native technologies: Discover how various tools and technologies help develop, run, and manage AI software.
- Tools & technologies: We’ll reveal the specific AI frameworks, libraries, and tools we used, including Kubernetes, Docker, and observability-related technologies.
- Live demonstration: Watch a live demo where our experts showcase the system configuration, infrastructure deployment using IaC, Kubernetes setup, and how to deploy GPU-intensive applications.
- Challenges & solutions: We will share the challenges we face and how we found their solutions so you can have valuable insights for your AI Lab journey.
- Plans: Get a sneak peek into our upcoming plans for the AI Lab.
Meet the Speakers
Manual tester turned developer advocate. He talks about Cloud Native, Kubernetes, AI & MLOps to help other developers and organizations adopt cloud native. He is also a CNCF Ambassador and the organizer of CNCF Hyderabad.
Sanket Sudake specializes in AI Cloud initiatives and building cloud-native platforms. He is a Fission Serverless platform maintainer with deep expertise in distributed systems, containers, and cloud environments.
Vishal is an engineer and loves helping companies transform their business by using technology and coaching people. He is a contributor to Fission, Fast and Simple Serverless Functions for Kubernetes and is organizer of “Pune Kubernetes & CNCF Meetup”.
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