Manage Kubernetes configuration with ConfigMaps, Secrets, namespaces, resource quotas, and environment-specific settings.
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Expose pod and container metadata to applications. Access pod name, namespace, labels, annotations, and resource limits from within containers.
Expose pod and container metadata to applications using the Downward API. Access labels, annotations, resource limits, and node information from within pods.
Manage application configuration with environment variables and ConfigMaps. Learn injection methods, mounting as files, and dynamic configuration updates.
Pull container images from private registries using image pull secrets. Configure authentication for Docker Hub, GCR, ECR, ACR, and private registries.
Switch between multiple clusters efficiently. Configure kubeconfig, manage contexts, and set up secure multi-cluster access.
Organize and manage Kubernetes resources with labels and annotations. Implement labeling strategies for selection, filtering, and metadata.
Set CPU and memory requests and limits effectively. Understand QoS classes, resource quotas, and optimize container resource allocation.
Set CPU and memory requests and limits for containers. Understand QoS classes, resource quotas, and best practices for right-sizing workloads.
Master Kubernetes ConfigMaps and Secrets for application configuration. Learn creation methods, mounting strategies, and security best practices.
Master Kubernetes namespace organization for multi-team environments. Learn resource quotas, network policies, and RBAC per namespace.
Master Kubernetes resource management with proper CPU and memory requests and limits. Avoid OOMKills, throttling, and resource contention.
Handle Kubernetes API version changes and deprecations. Migrate resources to stable APIs and ensure cluster upgrade compatibility.
Deploy ArgoCD for GitOps-based continuous delivery. Learn to sync Kubernetes manifests from Git repositories with automated reconciliation.
Reduce cloud costs in Kubernetes clusters. Right-size resources, use spot instances, implement autoscaling, and monitor spending effectively.
Manage Kubernetes configurations with Kustomize overlays. Customize base manifests for different environments without template duplication.
Control pod scheduling with taints and tolerations. Dedicate nodes for specific workloads, handle node conditions, and implement scheduling constraints.
Implement resource quotas to limit CPU, memory, and object counts per namespace. Ensure fair resource allocation across teams and environments.
Limit resource consumption per namespace with ResourceQuotas. Control CPU, memory, storage, and object counts to ensure fair cluster sharing.
Use Crossplane to provision and manage cloud infrastructure resources like databases, storage, and networking using Kubernetes-native APIs and GitOps workflows
Configure ComputeDomains for robust and secure Multi-Node NVLink (MNNVL) workloads on NVIDIA GB200 and similar systems using DRA
Learn to use Kubernetes Dynamic Resource Allocation (DRA) for flexible GPU allocation, sharing, and configuration with the NVIDIA DRA Driver
Dynamically partition NVIDIA A100 and H100 GPUs using Multi-Instance GPU (MIG) technology with Dynamic Resource Allocation for flexible workload isolation
Orchestrate heterogeneous accelerator workloads combining GPUs, TPUs, FPGAs, and custom AI chips using Dynamic Resource Allocation
Configure Google Cloud TPUs in Kubernetes using DRA for flexible allocation, multi-slice workloads, and optimized machine learning training
Extend the Kubernetes API with custom API servers using the aggregation layer to add new resource types and functionality without modifying core components
Perform Kubernetes cluster upgrades with zero downtime. Learn upgrade strategies, pre-flight checks, rollback procedures, and best practices for production clusters.
Customize the Kubernetes scheduler with scheduling profiles, plugins, and advanced placement strategies for optimal pod placement and resource utilization
Extend Kubernetes API with Custom Resource Definitions. Define custom objects, configure validation schemas, and manage CRD lifecycle.
Manage resource cleanup with Kubernetes finalizers. Implement custom cleanup logic and understand how finalizers prevent premature resource deletion.
Implement leader election and distributed coordination with Kubernetes Lease objects. Build highly available controllers and prevent split-brain scenarios.
Automatically inject configurations into pods using admission controllers. Configure environment variables, volumes, and annotations at deployment time.
Our book includes an entire chapter dedicated to configuration with dozens more examples.
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