Mirantis

🛑 Important:
Please register here to join the webinar! We will host this webinar in BrightTalk.

🗒 Overview:
Scaling AI across edge, core, and cloud environments is now a top priority but also a top challenge. How do you deliver high-performance inference, maintain control over your data, and keep costs predictable across a hybrid or multi-cloud setup?

In this session, you'll learn how to design and operationalize GPU-powered infrastructure that meets enterprise-grade AI demands. Whether you're leading platform architecture or responsible for AI/ML infrastructure strategy, you'll walk away with:

• Proven patterns for building hybrid GPU clouds that support both training and inference
• A framework for balancing performance, cost, and data sovereignty
• Strategies to enable inference-as-a-service across teams and regions
• Insights into how Kubernetes-native orchestration and NVIDIA technologies can accelerate deployment at scale

Led by Senior DevOps Engineer Prashant Ramhit, this session offers actionable guidance based on real-world deployments. If you're building or scaling intelligent applications, this is a can't-miss discussion on how to do it right.

🔗 Register here
🏡 Location: Online (you’ll get the link once you register)
⏰ Date/Time: July 30th (Wed) @ 9:00 ET / 15:00 BST / 18:00 MUT
👉🏻 Speaker: Prashant Ramhit, Senior DevOps Engineer

🛑 Important:
Please register here to join the webinar! We will host this webinar in BrightTalk.

🗒 Overview:
Sovereign cloud providers and regional telcos face mounting pressure to deliver scalable, profitable AI infrastructure without the complexity or cost of hyperscaler stacks. Traditional IaaS models were not designed for the elasticity, scale, or GPU efficiency that modern AI workloads demand. As a result, many providers experience sluggish customer onboarding, idle GPU capacity, and missed monetization opportunities.

In this webinar, you will learn how to turn your GPU infrastructure into a high-margin AI service platform. Discover how providers are using k0rdent AI’s turnkey deployment templates to launch GPU-backed services in days, reduce time to market, optimize GPU usage, and eliminate infrastructure waste.

To bring the ROI story to life, we will showcase live OpenCost-Grafana dashboards and forecasting metrics that highlight cost efficiency, revenue impact, and long-term profitability. You will walk away with practical insights to help you build a scalable and sovereign AI cloud strategy.

What you’ll learn:

• Why traditional cloud infrastructure falls short for AI workloads and what to do about it
• How to accelerate customer onboarding with k0rdent AI’s GPU service templates
• How to maximize GPU utilization and forecast ROI with OpenCost-Grafana dashboards

This session is ideal for Heads of Cloud Services, Product VPs, and CTOs, and also valuable for anyone involved in building AI infrastructure or launching GPU-backed services in sovereign, regulated, or regional markets.

🔗 Register here
🏡 Location: Online (you’ll get the link once you register)
⏰ Date/Time: August 4th (Mon) @ 9 am ET / 3 pm CEST / 6:30 pm IST
👉🏻 Speaker: Satyam Bhardwaj, Software Engineer

🛑 Important:
Please register here to join the webinar! We will host this webinar in BrightTalk.

🗒 Overview:
AI initiatives often start with promise, but scaling them into production is where most organizations struggle. The result is fragmented teams, underutilized GPU clusters, rising costs, and ad hoc AI projects that cannot be repeated or sustained.

In this webinar, we will explore how forward-thinking enterprises are transforming GPU sprawl into highly efficient AI Factories by building repeatable, scalable AI and ML pipelines.

You will learn how to:

• Streamline GPU provisioning and orchestration across hybrid and multi-cloud environments
• Establish standardized, reusable workflows for training, inference, and deployment
• Optimize infrastructure utilization to eliminate bottlenecks and control costs
• Enable platform teams to deliver self-service AI environments for data scientists and developers

This session will provide a blueprint for taking your AI strategy from disorganized experimentation to an industrialized factory model that accelerates innovation and delivers measurable ROI at enterprise scale.

Who should attend: Platform engineers, AI and ML architects, DevOps leaders, and technology decision-makers responsible for enterprise AI adoption.

🔗 Register here
🏡 Location: Online (you’ll get the link once you register)
⏰ Date/Time: August 20th (Wed) @ 9:00 PT / 12:00 ET / 17:00 BST
👉🏻 Speaker: Edward Ionel, Director of Growth Marketing