
Explore PowerShell's versatility with Jeffrey Snover and Jason Helmick as they showcase favorite solutions, leveraging 15 years of success and new innovations for cross-platform management and automation.

Explore hardware options for deep learning, from NVIDIA GPUs to cloud providers. Learn to choose the right setup for solo developers, startups, and large companies.

Learn about testing and deploying ML projects, covering project structure, evaluation, continuous integration, Docker, REST APIs, and various deployment options for efficient and scalable systems.

Explore infrastructure and tooling for deep learning projects, covering GPU machines, experiment tracking, and all-in-one solutions like AWS SageMaker.

Hands-on labs introducing text recognition project, covering setup, data handling, model creation, training, and deployment in a full-stack deep learning context.

Explore efficient AutoML using Ludwig and Ray, leveraging heuristics for model production. Learn how Nodeless Kubernetes optimizes GPU resource management, reducing costs in cloud environments.

Explore eBPF's potential in high-throughput scenarios, focusing on Falco's syscall tracing. Learn about challenges, mitigations, and future enhancements for large-scale tracing tools.

Explore MLExray for efficient debugging of edge-deployed machine learning models, covering benefits, deployment challenges, and practical demonstrations.

Optimize CPU performance in Kubernetes by managing thread scheduling and memory locality with CRI Resource Manager, enhancing database and AI training without workload-specific configurations.

Explore Knative Functions: a platform between CaaS and FaaS for deploying serverless applications. Learn its evolution, capabilities, and how to create, build, and deploy event-driven functions in multiple languages.

Explore efficient deep learning training using Ludwig AutoML and Ray on nodeless Kubernetes, optimizing GPU resource management for cost-effective and scalable model development.

Explore Kamelets as event sources in Knative, learn installation, discovery, deployment, and management. Live demo showcases integration with event-driven applications using Apache Camel connectors.

Explore NUMA-aware scheduling in Kubernetes for HPC workloads, addressing challenges, solutions, and future developments in resource orchestration and performance optimization.

Explore Knative's evolution from Elafros to CNCF incubation, its community growth, upcoming features, and how to get involved in this serverless computing platform.

Explore Knative's serverless application deployment simplification and learn to use 'kn' CLI for efficient developer workflows, from service creation to production rollout.

Explore Kueue, a Kubernetes-native job queueing solution for efficient resource management and fair sharing in batch workloads, addressing limitations in pod-centric scheduling.

Explore Apache YuniKorn's advanced batch scheduling capabilities for Kubernetes, including workload queueing and quota sharing, while seamlessly coexisting with traditional non-batch workloads.

Explore Knative's autoscaling, cold start challenges, and innovative solutions like container pausing to enhance serverless performance and reduce latency in cloud-native systems.

Leveraging Knative for scalable ML inference platforms: simplifying deployment, enabling serverless containers, and optimizing performance for production-ready machine learning applications.

Explore strategies for managing sensitive assets in GitOps, including encryption, integration with secrets engines, and leveraging GitOps tools to enhance security in cloud-native environments.

Explore solutions for monitoring short-lived workloads and serverless jobs using Prometheus, addressing challenges and demonstrating best practices for capturing fleeting metrics in cloud-native environments.