Cloud Native Now’s Post

Kubernetes isn’t just a tool, it’s a spectrum.   I mapped 8 cluster types, from local dev to air-gapped HA to global federation. If you’ve only used EKS/AKS/GKE, this post will expand your mental model. #Kubernetes #SystemDesign #SystemArchitecture #DevOps #Infrastructure #Kubeadm #RKE2 #CloudNative #K3s #HAClusters #EdgeComputing

Good idea — doing a POC (proof of concept) first is a smart way to learn and validate before a full OpenShift rollout. Below are some real-world–style scenarios + principles (from Red Hat) + a roadmap + useful guides for building this “zero → hero” POC     +-----------------------+     |   OpenShift SNO  |     | Control Plane & Node |     +-----------------------+     | kube-apiserver    |     | etcd         |     | kube-controller    |     | kube-scheduler    |     | kubelet        |     | CRI-O / Pod runtime  |     | Network (OVN-K8s)  |     +-----------------------+     | Workloads (Pods)   |     | Operators       |     +-----------------------+ Notes: Control plane and worker workloads are on the same node. Network: OVN-Kubernetes (default). Storage: Local PVs for POC; can test NFS/Gluster/Ceph later.

Resharing this gem: The recent AWS and Azure outages were a brutal reminder: even the biggest clouds have bad days. If you're running production workloads on Kubernetes, high availability isn't just a checkbox. This post lays out 10 rock-solid practices for building resilient Kubernetes platforms. A few that really resonate with me: Multi-region clusters - because one region is never enough. Readiness/liveness probes - small configs, massive impact. Chaos engineering - test your system before the real chaos hits. Resilience isn’t built during an outage, it’s engineered long before. If you’re in platform, SRE or DevOps this is your playbook. #Kubernetes #CloudNative #DevOps #SRE #HighAvailability #PlatformEngineering

🎉 Successfully deployed a cost-optimized Kubernetes cluster for development environments! Just set up a K8s cluster on AWS EC2 with a focus on cost efficiency without compromising functionality. Architecture highlights: ✅ 2-node cluster (1 control plane + 1 worker node) ✅ Single public subnet design (eliminated NAT Gateway costs) ✅ Strict security group rules for node isolation and communication ✅ Containerd runtime with Flannel CNI ✅ Production-grade setup principles adapted for dev workloads Cost optimization strategy: 💰 Replaced traditional private subnet + NAT Gateway architecture with public subnet approach 💰 Implemented tight security group controls to maintain security posture 💰 Significant monthly savings on NAT Gateway charges (~$32-45/month saved) 💰 Perfect balance for development and testing environments Key takeaways: Not all environments need production-level networking complexity Strategic architecture decisions can reduce cloud costs substantially Security can be maintained through proper security group configuration Understanding trade-offs between cost and architecture is crucial This setup is ideal for dev/test workloads where cost control is essential while maintaining a fully functional Kubernetes environment. Ready to deploy and test applications! 🚀 #Kubernetes #K8s #AWS #CloudComputing #DevOps #CostOptimization #CloudArchitecture #ContainerOrchestration #Development #EC2 #FinOps #CloudNative #InfrastructureDesign

Access Mode RWX (ReadWriteMany): Access Mode RWX (ReadWriteMany) is a Kubernetes persistent volume access mode that allows a volume to be mounted with both read and write permissions by multiple nodes simultaneously. This capability enables true multi-writer shared storage, making it essential for applications that need concurrent data access and updates from multiple pods across different nodes, such as content management systems, collaborative tools, shared caches, or distributed logging platforms. RWX depends heavily on the underlying storage system’s ability to support concurrent read/write operations safely, ensuring data consistency, conflict resolution, and performance across distributed environments. Because of this, it typically relies on networked file systems like NFS, GlusterFS, or managed cloud storage solutions. RWX is a powerful enabler for stateful, horizontally scaled workloads, but it also introduces challenges around synchronization, locking, and data integrity, meaning application design must consider concurrency control. In Kubernetes, workloads that depend on RWX are usually those requiring both scalability and shared data persistence across multiple compute resources. #AccessModes #SharedStorage #MultiWriter #Kubernetes #K8s #DevOps

💥 The Real Power of Kubernetes — Beyond Deploying Pods After managing Kubernetes clusters across AWS & Azure environments for several enterprise projects, I’ve learned that true expertise isn’t about YAML — it’s about how well you handle reliability, scale, and chaos in production. Here are 10 real-world lessons I never skip when working with Kubernetes 👇 ⚙️ 1. Cluster hygiene matters more than uptime A “Running” cluster doesn’t always mean it’s healthy. Regularly clean up unused PVCs, Jobs, and ReplicaSets — they silently drain performance. 🧩 2. Namespace strategy = Security architecture Namespaces aren’t folders — they’re isolation layers. Apply quotas, network policies, and RBAC per namespace. 🔄 3. Rolling updates ≠ with zero downtime Understand pod disruption budgets, readiness probes, and rollout parameters. Downtime prevention is an engineered design, not a deployment flag. 🔐 4. Secrets management is your real perimeter Never commit secrets in YAML. Use Vault, AWS Secrets Manager, or External Secrets Operator with KMS encryption. 📊 5. Observability beats troubleshooting Expose Prometheus metrics and set liveness/readiness/startup probes. If you can’t measure it, you can’t improve it. 🧱 6. Control plane health = cluster health Monitor etcd size, API latency, and scheduler queue depth. If your control plane lags, so will every deployment. 🌐 7. Networking separates pros from beginners Understand your CNI plugin (Calico, Cilium), CoreDNS, and Ingress Controllers. Most “pod unreachable” issues are network misconfigurations, not application bugs. 💰 8. Resource tuning = cost tuning Balance performance and budget. Use VPA, Karpenter, or Goldilocks to optimize requests and limits. 🧰 9. Policy as code keeps teams disciplined Use OPA Gatekeeper or Kyverno to block privileged pods and enforce best practices. 🧾 10. Backups and DR are your real insurance Automate Velero or Kasten K10, and test restores regularly. A backup untested is just a theory. 💡 Kubernetes mastery isn’t about running pods — it’s about building resilient, secure, and self-healing systems that survive the unexpected. #Kubernetes #DevOps #SRE #AWS #Azure #ArgoCD #Helm #Terraform #Observability #Prometheus #Grafana #Automation #Security #CloudEngineering #Resilience

Day - 02 Kubernetes - architecture The k8s architecture is divided into two main parts: 1) Control Plane 2) and the Worker Plane, Each playing a vital role in maintaining cluster operations. The Control Plane acts as the central management layer and is responsible for controlling, monitoring, and making decisions about the cluster’s overall state. It ensures that the desired state of applications matches the actual running state. Key components of the Control Plane include: i) API server, ii) etcd, iii) scheduler, iv) controller manager v) cloud controller manager The Worker Plane is where the actual workloads applications and services run. Each node in the worker plane is equipped with essential components that allow it to execute workloads, communicate with the Control Plane, and maintain networking between containers. The main components of the Worker Plane include: i) kubelet ii) kube-proxy iii) container runtime #100DaysOfK8s #Kubernetes #DevOps

Kubernetes Cluster Autoscaler : How to Make Kubernetes Scale Automatically Ever wondered how top tech companies handle sudden traffic spikes without going bankrupt on cloud bills? Let me explain with a example: The Kubernetes Cluster Autoscaler. Imagine you run "QuickFood," a food delivery app. Every day at 12 PM, lunch orders flood in. Your backend API pods need to scale up fast to handle the load, but you don't want to pay for extra servers 24/7. 11:55 AM - Normal Traffic: ➜ 5 worker nodes running ➜ 80% CPU utilization ➜ Everything running smoothly 12:00 PM - Lunch Rush Begins: ➜ Orders increase by 500% ➜ New API pods are created but get stuck in "Pending" state ➜ No existing node has enough CPU/RAM 12:01 PM - Cluster Autoscaler Detects Crisis: ✔ Notices pending pods ✔ Checks node templates (EC2 instance types) ✔ Spins up 3 new worker nodes 12:03 PM - Crisis Averted: ➜ New nodes join cluster ➜ Pending pods get scheduled ➜ Orders process successfully ( Customers stay happy! ) 1:30 PM - Rush Ends: ➜ Traffic returns to normal ➜ Some nodes are now underutilized (15% CPU) ➜ Autoscaler safely drains and removes extra nodes ✔ The Magic Behind the Scenes:----------------- # Your cluster-autoscaler deployment just needs: - --scale-down-utilization-threshold=0.5 - --scale-down-unneeded-time=10m - --max-node-provision-time=15m ------------------------------------------------------- #Kubernetes #DevOps #CloudComputing #AWS #CostOptimization #InfrastructureAsCode #SRE #PlatformEngineering

Understanding How Virtual Machines Run Inside OpenShift 💡 Connect with Red Hat Experts - https://lnkd.in/g7QSNA7V Ever wondered what happens behind the scenes when you spin up a Virtual Machine (VM) on OpenShift using OpenShift Virtualization (KubeVirt)? Here’s the simplified breakdown 👇 1️⃣ virt-controller operator - constantly watches for new VMI (VirtualMachineInstance) objects created via the API server. 2️⃣ virt-handler - runs as a DaemonSet on every node and ensures each VM reaches its desired state. It also detects when a VM needs to be launched and triggers the virt-launcher container. 3️⃣ virt-launcher - runs inside the VM’s pod and starts a local libvirtd instance, which handles the actual virtualization layer and manages the VM lifecycle (start, stop, reboot, migrate, etc.). 4️⃣ Once the VMI is provisioned, the virt-launcher pod routes IPv4 traffic to the VM’s DHCP address - enabling easy port-forwarded connections for remote access. 5️⃣ The libvirtd instance also provides the virsh utility, allowing admins to manage VMs directly: ✅virsh list → View running VMs ✅virsh start → Start a VM ✅virsh shutdown → Gracefully stop a VM ✅virsh dumpxml → View or export VM configuration ✅virsh reset → Reset a VM instantly ✅virsh restore → Restore from a saved state ✅virsh migrate → Migrate a VM to another host To manage your VM interactively, you can even access the virt-launcher pod terminal directly from the OpenShift Web Console → Workloads → Pods → Terminal tab. In short: KubeVirt tightly integrates virtualization into Kubernetes, giving you the power to manage VMs and containers side by side - all through the same OpenShift platform. Connect with Red Hat Experts - https://lnkd.in/g7QSNA7V #OpenShift #KubeVirt #Virtualization #RedHat #CloudNative #HawkStack #DevOps #RHCA #Kubernetes #OpenShiftVirtualization