Vishal Anarase
Mirantis Inc | Cloud Native | Kubernetes Enthusiast | Docker Captain | Kubestronaut | Open Source Advocate
Pune, India
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Vishal Anarase is a Sr. Software Engineer at Mirantis (OSPO), Docker Captain and Kubestronaut passionate about Kubernetes, Docker, Golang and Cloud Native technologies.
He actively contributes to the CNCF ecosystem and regularly speaks at community events and meetups on cloud-native infrastructure, DevOps, observability, AI and platform engineering.
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Sharing GPUs Without Sharing Blast Radius: Multi-Tenant DRA on Kubernetes
Multi-tenant GPU clusters force platform teams into ugly trade-offs. Static partitioning wastes hardware; looser sharing pushes risk onto operators. A node can look healthy while part of its GPU inventory is no longer safe to assign. The question is not whether GPUs can be shared, but whether they can be shared safely.
This session examines Dynamic Resource Allocation through a multi-tenancy lens. Speakers show how DRA improves shared accelerator infrastructure, why device taints, binding conditions, admin access, and finer authorization matter, and what still requires policy above Kubernetes.
Using upstream Kubernetes and the open source NVIDIA DRA driver as references, attendees learn how to evaluate access boundaries, degraded-device handling, and the difference between schedulable and safe-to-reuse. They leave with a framework for multi-tenant GPU platforms and the controls still needed around DRA.
Beyond GPU Counts: Device-Aware Scheduling With Kubernetes DRA
GPU scheduling in Kubernetes is mostly count-based: request one device, land on a node, and let driver logic handle the rest. That fails when partitioning, topology, memory, and capability differences decide whether a job runs well, poorly, or not at all.
This session explains how Dynamic Resource Allocation changes scheduling. Speakers show how DRA gives Kubernetes a richer picture of devices and workload needs, and why partial-device capacity, preferred fallbacks, and partitioned hardware matter for placement.
Using upstream Kubernetes and the open source NVIDIA DRA driver, the talk traces workload request to scheduler decision to kubelet preparation, and what remains hard. Attendees leave knowing when device-aware scheduling is worth the complexity and what Kubernetes can decide today that count-based scheduling could not.
Where Did My GPU Claim Go? Observability for DRA Drivers
Dynamic Resource Allocation gives Kubernetes a structured model for GPUs and other accelerators. But after a ResourceClaim is scheduled and handed to a kubelet plugin, most drivers go quiet. When a pod is stuck in ContainerCreating, engineers can't tell whether the driver, the scheduler, or the API server is at fault, and they have no baseline for how long device preparation should take.
This talk walks through the observability layer merged into the upstream dra-example-driver. We'll cover where to instrument (callback boundaries, not the gRPC server), which signals matter (prepare and unprepare counters, latency histograms, fatal background errors), and how to get API client metrics almost for free from component-base. Then we'll use those metrics to trace a failing claim end to end, go over the deployment gotchas, and be clear about what is still missing. You'll leave with a pattern you can reuse for any DRA driver.
Multicluster Mastery: Managing Multi-Cloud Multi-Cluster Kubernetes with k0rdent and Istio
Managing multiple Kubernetes clusters across different cloud providers (GCP, Azure, AWS) is one of the most challenging aspects of modern cloud-native operations. In this session, we'll explore how k0rdent provides a declarative approach to multi-cloud multicluster management, and how Istio service mesh enables seamless application deployment and communication across clusters spanning multiple cloud providers.
We'll dive into real-world scenarios where we've deployed applications across multi-cloud clusters (GCP, Azure, AWS) using k0rdent's declarative approach for multi-cluster orchestration. You'll learn how to:
- Set up and configure k0rdent for multi-cloud multicluster orchestration
- Manage Kubernetes clusters across GCP, Azure, and AWS declaratively
- Deploy applications with Istio service mesh for cross-cloud, cross-cluster communication
- Handle traffic management, security policies, and observability across multi-cloud clusters
This talk includes live demos showing the complete workflow from multi-cloud cluster registration to application deployment, with practical insights on what worked, what didn't, and lessons learned from production multi-cloud multicluster deployments.
Multi-Cloud Kubernetes Made Simple: k0rdent (CAPI) and Istio for Cross-Cloud Cluster Management
Managing multiple Kubernetes clusters across different cloud providers (GCP, Azure, AWS) is complex. In this lightning talk, we'll show how k0rdent and Istio work together to simplify multi-cloud multicluster management and application deployment.
We'll cover:
- Quick setup of k0rdent for multi-cloud multi-cluster orchestration
- Deploying applications across clusters spanning GCP, Azure, and AWS with Istio
- Cross-cloud, cross-cluster traffic management and observability
This fast-paced session includes a live demo of deploying a microservices application across multi-cloud clusters, with practical tips from production multi-cloud multicluster deployments.
Building Managed Services on Top of Kubernetes
Learn how to leverage Kubernetes to build managed services efficiently. This session covers API design, architectural best practices, and automation techniques, empowering attendees to streamline operations, scale applications, and drive innovation in their organizations.
Vishal Anarase
Mirantis Inc | Cloud Native | Kubernetes Enthusiast | Docker Captain | Kubestronaut | Open Source Advocate
Pune, India
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