Comidoc Analysis
A Comprehensive and Practical Course: Containers, K8s, Networking, Security, Scaling, Storage, Monitoring, HA and others
Azure Kubernetes Service (AKS) Made Easy
Duration19h 46m
Students17.1K
Rating4.6 (1,418)
A Comprehensive and Practical Course: Containers, K8s, Networking, Security, Scaling, Storage, Monitoring, HA and others
FreeEditorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This introductory slide outlines the starting point for learning Azure Kubernetes Service by displaying key architectural components and tools such as kubelet, containerd, and k-proxy.
This course introduction slide outlines key topics including working with node pools and nodes, illustrated with server and OS icons, alongside networking concepts in Azure Kubernetes Service.
This course introduction slide outlines the curriculum starting with understanding containers using Docker visuals before moving to an overview of Kubernetes.
This course introduction slide highlights the topic of monitoring and troubleshooting Azure Kubernetes Service (AKS), illustrated by a sequence of icons for logs, tools, analytics, gauges, alerts, and system health.
Covers essential AKS components including coredns, kube-proxy, and metrics-server, alongside diverse networking options like Azure CNI and Overlay plugins.
Provides instruction on Microsoft Entra integration, Azure RBAC, and Kubernetes RBAC for cluster management.
Learners have noted the absence of shared Kubernetes YAML files used during demonstrations, which can hinder independent practice. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
One signal suggests specific container images used in lectures may be outdated, requiring manual adjustments to newer versions. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
The curriculum aligns well with the target audience of cluster administrators and developers, provided they have prior K8s knowledge.