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Upstream @ AKS

Podcast af Azure Kubernetes Service

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Videnskab & teknologi

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Upstream@AKS is a conversation series focused on Azure's upstream contributions to Kubernetes and other open source projects. The show explores how Azure team members are building the future of open source projects foundational to Azure Kubernetes Service (AKS).

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10 episoder

episode Transforming Observability with AI: with Qasim Sarfaraz: Upstream@AKS: Azure Kubernetes Service cover

Transforming Observability with AI: with Qasim Sarfaraz: Upstream@AKS: Azure Kubernetes Service

Lachie Evenson and Qasim Sarfraz discuss how AI is transforming observability with Inspektor Gadget and MCP servers for Kubernetes observability. Don’t forget to like, subscribe, and share your thoughts or questions in the comments! Related Links CNCF: https://www.cncf.io/ Inspektor Gadget GitHub repository : https://github.com/inspektor-gadget/inspektor-gadget Inspektor Gadget Headlamp plugin: https://github.com/inspektor-gadget/headlamp-plugin Gadgets on Artifact Hub: https://artifacthub.io/packages/search?kind=22 Inspektor Gadget MCP Server (Discover, Configure, and Analyze output using Inspektor Gadget): https://github.com/inspektor-gadget/ig-mcp-server AKS Model Context Protocol server (A bridge between AI tools & AKS): https://github.com/Azure/aks-mcp Blog: Leveraging Real-Time insights via the AKS-MCP Server: https://blog.aks.azure.com/2025/08/20/real-time-observability-in-aks-mcp-server VS Code Agent Mode: https://code.visualstudio.com/docs/copilot/chat/chat-agent-mode Cagent K8s Debugger: https://github.com/docker/cagent/blob/main/examples/k8s_debugger.yaml Kubernetes slack: https://github.com/inspektor-gadget/inspektor-gadget?tab=readme-ov-file#slack Hello world gadget: https://inspektor-gadget.io/docs/latest/gadget-devel/hello-world-gadget #kubernetes #ai #inspektorgadget

20. okt. 2025 - 21 min
episode Istio & Upstream Networking: with Keith Mattix: Upstream@AKS: Azure Kubernetes Service cover

Istio & Upstream Networking: with Keith Mattix: Upstream@AKS: Azure Kubernetes Service

Lachie Evenson and Keith Mattix talk about Istio and Service Meshes in the cloud native world. Discover how Istio's ambient mode simplifies onboarding, reduces costs, and enables organizations to scale securely and efficiently. Learn about the latest innovations in application-layer networking, including AI-driven routing, Gateway API advancements, and token-based rate limiting for LLM workloads. Whether you're new to Kubernetes or managing complex microservices, this discussion offers practical insights and community resources to help you succeed on your cloud native journey. Don’t forget to like, subscribe, and share your thoughts or questions in the comments! Related LinksCNCF: https://www.cncf.io/Istio: https://github.com/istio/istio/Istio Mutual TLS: https://istio.io/latest/docs/concepts/security/#mutual-tls-authenticationIstio Ambient Mode: https://istio.io/latest/docs/ambient/overview/Gateway API: https://github.com/kubernetes-sigs/gateway-apiGateway API Inference Extension: https://github.com/kubernetes-sigs/gateway-api-inference-extensionWorking Group AI Gateway: https://github.com/kubernetes-sigs/wg-ai-gateway

6. okt. 2025 - 23 min
episode Kaito: AI/ML inference & tuning in Kubernetes: with Ernest Wong: Upstream@AKS: Azure Kubernetes Svc cover

Kaito: AI/ML inference & tuning in Kubernetes: with Ernest Wong: Upstream@AKS: Azure Kubernetes Svc

Lachie Evenson and Ernest Wong discuss Kaito. KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster. The target models are popular open-sourced large models such as phi-4 and llama.Related LinksCNCF: https://www.cncf.io/KAITO: https://github.com/kaito-project/kaitoGet involved with KAITO: https://github.com/kaito-project/kaito?tab=readme-ov-file#get-involvedPackaging models as a container image: https://kaito-project.github.io/kaito/docs/model-as-oci-artifactsKAITO preset models: https://kaito-project.github.io/kaito/docs/presetsGPU Operator: https://github.com/NVIDIA/gpu-operatorRetrieval-Augmented Generation (RAG): https://kaito-project.github.io/kaito/docs/rag/

29. sept. 2025 - 19 min
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