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Plan K3s upgrades with release channels, server-first sequencing, System Upgrade Controller, datastore snapshots, v1.37 checks, and rollback.
Design K3s networking with Flannel, Traefik, ServiceLB, Gateway API, private node traffic, and a separate HA control-plane registration endpoint.
Choose K3s storage for production across local-path, Longhorn, node failure, PVC recovery, and backups without confusing persistence, HA, and DR.
Learn K3s default datastore behavior and compare SQLite, embedded etcd, and external PostgreSQL/MySQL/etcd for HA, quorum, backups, and recovery.
Design K3s on cloud VMs across single-server, agent, and HA topologies, including datastore, networking, storage, backups, upgrades, and production operations.
Compare serverless vs containers across architecture, scaling, cost, portability, runtime control, serverless containers, Kubernetes, and common use cases.
A practical Kubernetes security baseline for RBAC, ServiceAccounts, Secrets, Pod Security Standards, securityContext, and recurring access reviews.
Learn Kubernetes monitoring across metrics, logs, Events, and traces, with a practical small-team observability and alerting framework.
Understand Kubernetes autoscaling with HPA, node scaling, resource requests, scale-to-zero, stabilization, scheduling, and worker cost boundaries.
Plan Kubernetes backup and disaster recovery with RPO/RTO, etcd, persistent data, VolumeSnapshots, restore testing, and failure-specific recovery runbooks.
Plan Kubernetes upgrades with supported-version checks, API compatibility, worker drains, PDBs, recovery state, stop criteria, and post-upgrade validation.
Kubernetes cluster management for small teams: capacity, upgrades, recovery, autoscaling, monitoring, security, and cost.
Understand Kubernetes requests vs limits for CPU and memory, including scheduling, throttling, OOM behavior, HPA, QoS, LimitRange, best practices, and worker capacity.
Compare Kubernetes LoadBalancer Services vs Ingress controllers, including routing, TLS, TCP/UDP, public endpoints, Gateway API, and when to use each.
Understand Kubernetes Services, ClusterIP, NodePort, LoadBalancer, Gateway API, and Ingress for production traffic exposure.
Design Kubernetes networking and storage across Services, Gateway API, NetworkPolicy, PVCs, StorageClasses, private networking, and recovery.
Troubleshoot Kubernetes DNS and service discovery across CoreDNS, namespaces, Pod resolver settings, Services, EndpointSlices, NetworkPolicy, and upstream DNS.
Plan a Docker Compose to Kubernetes migration across state, probes, networking, secrets, storage, worker sizing, cutover, and rollback.
Learn when Kubernetes node pools make sense, how labels, affinity, taints, autoscaling, failure capacity, and worker shapes affect workload placement.
Size Kubernetes clusters using Node Allocatable, workload requests, worker shape, rollout overlap, N+1 failure headroom, and autoscaling boundaries.
Understand Kubernetes persistent storage, PVs, PVCs, StorageClasses, access modes, reclaim policies, StatefulSets, snapshots, and backup boundaries.
Learn Kubernetes NetworkPolicy with default-deny, ingress, egress, selectors, DNS rules, examples, rollout checks, and production verification.
Compare managed vs self-managed Kubernetes across control-plane ownership, upgrades, HA, recovery, cost, and team fit—and see when a managed Kubernetes service makes sense.
Choose Docker, Compose, K3s, or managed Kubernetes based on ownership, multi-host needs, scaling, and recovery.
Kubernetes multi-tenancy for MSPs: compare namespace isolation, dedicated worker pools, virtual control planes, and dedicated clusters for security, cost, and operations.
K3s is Kubernetes, not a separate orchestrator. Compare K3s vs K8s on resource footprint, HA, customization, production use, and self-managed vs managed ownership.
Compare shared vs per-client Kubernetes clusters for MSPs across isolation, admin access, blast radius, lifecycle, chargeback, and operations.
Learn when not to use a VPS, the main VPS limitations, and when shared hosting, an app platform, managed database, serverless, Kubernetes, dedicated hardware, or object storage fits better.
Reduce Kubernetes costs by measuring allocation, rightsizing requests, tuning autoscaling, removing idle capacity, and controlling storage and observability.
Docker Compose vs Kubernetes for small teams: compare production fit, migration triggers, operational cost, readiness, and a staged Raff infrastructure path.
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