
Explore Arm-based image recognition implementation using Kubernetes on edge devices, focusing on practical applications and performance optimization techniques.

Explore KubeEdge for efficient edge computing inference with Adrian Gonzalez-Martin from Seldon. Learn about deploying and managing machine learning models at the network edge.

Explore reactive computing, streaming ML, and deep learning for image recognition. Learn about serverless architecture and real-time data processing with a live demo of software engineering integration.

Explore deep learning packages for IoT devices, focusing on implementation strategies and practical applications for edge computing and resource-constrained environments.

Explore ACUMOS AI, an open-source platform for ML workflow, trusted AI, and federated learning. Learn about cloud migration, edge deployment, and practical use cases in this comprehensive overview.

Explore event-driven autoscaling for serverless Java using KEDA and Knative on Kubernetes, focusing on Apache Kafka metrics for efficient scaling beyond traditional resource-based methods.

Learn about ExecuTorch, a new stack for accelerating PyTorch models on edge devices, addressing on-device ML challenges and enabling efficient, portable execution without compromising user experience.

Explore Intel's strategy for AI integration across platforms, emphasizing open-source contributions, software acceleration, and developer-friendly tools to maximize performance and productivity.

Explore lightweight Kubernetes distributions k0s, k3s, and MicroK8s. Compare features, capabilities, and use cases to choose the best option for your needs. Includes deep dive into k0s and introduction to k0smotron for multi-cluster management.

Explore Kubernetes-native solutions for Edge and IoT using k0s and k0smotron. Learn about key use cases, technical challenges, and how these tools simplify deployment and management of distributed infrastructure.

Learn to train and deploy a custom object detection model on the Google Coral Dev Board Micro, achieving fast inference speeds with low power consumption. Hands-on guide covers data collection, model training, and deployment.

Explore strategies to optimize LLM deployments in Kubernetes clusters, focusing on reducing model size, improving resource utilization, and balancing performance with efficiency for cloud-to-edge scenarios.

Explore AI edge deployment patterns using Kubernetes and Open Data Hub. Learn to manage distributed architectures, handle edge data, and select optimal deployment strategies for various industries and use cases.

Explore deploying WebAssembly applications using Argo CD and wasmCloud, enabling GitOps workflows for cloud-native apps across multiple clusters, clouds, and edge devices.

Explore cutting-edge strategies for securing smart homes in this DefCamp 2023 presentation. Learn about emerging threats and innovative solutions to protect IoT devices and networks at the edge.

Discover a cost-effective 2-node high availability architecture for Kubernetes at the edge, offering resilience and 33% savings compared to traditional 3-node setups. Learn from real-world examples and explore open-source solutions.
![Unleash the Power of etcd - Exploring E[Xtensible]-etcd Capabilities](https://img.youtube.com/vi/VL9111ony2k/mqdefault.jpg)
Explore E[Xtensible]-etcd: an innovative solution for optimizing etcd storage in Kubernetes clusters. Learn about its evolution, limitations, benchmarks, applications, and community implications.

Automated system for composing network function chains into P4 programs for edge gateways, optimizing traffic processing and reducing programmer workload in cloud environments.

Innovative packet loss recovery mechanism for edge-based interactive streaming, reducing bandwidth costs and improving video frame delivery while maintaining low latency requirements.

Vulcan: Automatic system for optimizing live ML query plans. Determines best pipeline, placement, and configuration with low profiling cost and fast online adaptation, outperforming existing systems.

Explore KubeEdge's architecture and real-world applications in IoT and distributed systems. Learn how it extends Kubernetes for efficient edge computing workload management across various industries.