Cloud Native Mastery
IntermediateMaster containers, Kubernetes, and Infrastructure as Code from first principles, then deploy production agentic AI workloads to AWS, Azure, and GCP. Covers Docker, K8s primitives, Terraform, EKS/AKS/GKE, and the patterns for shipping LLM agents at scale.
Videos
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Learn what a container actually is, how Docker builds images from a Dockerfile, how layers and caching work, and how registries (Docker Hub, ECR, GHCR) distribute images. Covers multi-stage builds, slim base images, and OCI runtime fundamentals.
Master the K8s building blocks: Pods, ReplicaSets, Deployments, Services, ConfigMaps, Secrets, and Ingress. Understand the control plane (API server, scheduler, controller manager, etcd) and how reconciliation loops keep desired state.
Provision cloud resources declaratively with Terraform: providers, resources, state files, remote backends (S3, Terraform Cloud), modules, workspaces, and CI/CD integration. Compare with Pulumi and the broader IaC landscape.
Stand up managed K8s clusters on AWS (EKS), Azure (AKS), and Google Cloud (GKE). Compare networking (VPC CNI, Azure CNI, GKE VPC-native), node pools, autoscaling (Cluster Autoscaler vs Karpenter), and IAM integration per cloud.
Deploy production agentic AI workloads: GPU node pools, model-serving (vLLM, TGI), KEDA autoscaling on queue depth, observability with Prometheus and OpenTelemetry. Patterns for Bedrock, Azure OpenAI, and Vertex AI integration.
Certification Exam
Certification Exam
Cloud Native Mastery
All tracks ยท No time pressure to start
Certification Exam
Cloud Native Mastery
40 Questions
All difficulty levels
120 Minutes
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75% to Pass
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Tips
See allObservability for LLMs: track tokens
Latency and errors are not enough
Call Bedrock Claude via IRSA, no keys
Pod identity > long-lived API tokens
Prompt cache sidecar in front of the model
Hash the prompt, skip the GPU
Warm models before flipping ready
Cold-start latency is a real outage