Pods are ephemeral—they are created, destroyed, and rescheduled dynamically, causing their IP addresses to change constantly. A Kubernetes Service provides a stable, persistent virtual IP (VIP), DNS name, and load balancing frontend across a dynamic set of backend Pods.
While Pods are the basic building blocks of Kubernetes, you should rarely deploy bare Pods directly. Instead, production applications use Deployments, a higher-level abstraction that manages ReplicaSets to guarantee high availability, self-healing, and seamless scaling.
The kubectl command-line interface is the primary tool platform engineers and developers use to interact with Kubernetes clusters. In this episode, we’ll configure kubectl and deploy our first atomic Kubernetes primitive: the Pod.
A Kubernetes cluster consists of two primary logical layers: the Control Plane (the cluster’s brain) and Worker Nodes (the muscle that runs application containers). Understanding how these components communicate is crucial for cluster administration and troubleshooting.
The evolution of modern infrastructure has transitioned from physical bare-metal servers to Virtual Machines (VMs), lightweight OCI Containers, and ultimately automated Container Orchestration platforms like Kubernetes.
Master Kratix to deliver self-service infrastructure and application capabilities to development teams with Promises, Workflows, Pipelines, and GitOps.
Mengalami error OOMKilled (Exit Code 137) saat menjalankan aplikasi di Kubernetes? Masalah ini terjadi ketika penggunaan memori kontainer melebihi batas resources.limits.memory.
1. Penyebab Utama Error # Secara teknis, OOM (Out Of Memory) Killer pada Linux Kernel akan menghentikan proses yang mengonsumsi RAM berlebih.
2. Solusi Cepat # Naikkan batas RAM pada manifest YAML:
