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This tutorial walks through Kubernetes initContainers, demonstrates how to create and manage static Pods, and explains pod scheduling strategies—including node labeling and nodeSelector—using step‑by‑step YAML examples and kubectl commands to illustrate each concept in practice.
This article answers ten common Kubernetes questions, covering pod scheduling strategies, OOM behavior, dynamic ConfigMap updates, pod stability, ClusterIP service load balancing, log collection, liveness probes, scaling mechanisms, exec access, and troubleshooting container restarts, providing concise explanations for each scenario.
The session detailed how Tencent’s container experts boost Kubernetes cluster utilization by correcting pod resource requests, employing two‑level auto‑scaling, dynamic over‑commit, adaptive scheduling and eviction, and using HPA/EHPA/VPA, achieving up to 38.7% node usage and roughly 60% cost savings in real‑world workloads.
The Kubernetes scheduler continuously watches for unscheduled Pods, places them in a priority queue, filters feasible Nodes, scores and selects the best Node using built‑in and custom plugins—adjusting the node‑sampling rate for large clusters, and allowing extensibility through extenders, multiple schedulers, and the scheduler framework configuration.
This article explains the evolution and core principles of the Kubernetes scheduler, outlines its fairness, efficiency, performance, and flexibility goals, describes the scheduling cycle and filtering‑scoring process, and introduces configuration methods for custom scheduling policies.
Learn how to use Kubernetes Descheduler to rebalance uneven pod distribution across nodes by configuring various built‑in strategies, custom policies, filtering options, and deployment methods such as Jobs and CronJobs, with detailed examples and best‑practice guidelines for production clusters.