This article details replacing sidecar log collectors with node-level DaemonSets in Kubernetes, covering resource cost analysis, declarative LogPipeline CRD design, controller implementation, backpressure handling, capacity planning, and production verification steps for enterprise-scale log collection.
A rigorous benchmark of nine Kubernetes log collectors under a 1‑core, 1 GiB limit shows VictoriaMetrics' vlagent achieving 143,000 lines per second—4.5× faster than Fluent Bit and 28× faster than Fluentd—while using the least CPU and memory, and exposing hidden correctness bugs in several competitors.
The article details Duodian DMALL’s migration from a traditional Hadoop stack to a cloud‑native Spark‑on‑Kubernetes architecture, explaining the motivations, design choices, component selections, operational challenges, and lessons learned through concrete examples and performance observations.
This article explains Kubernetes container runtimes, the CRI and OCI standards, compares Docker, containerd, CRI‑O and runc, outlines the challenges of log collection in K8s, and shows how open‑source collectors like Filebeat and Fluent Bit as well as iLogtail's daemonset and sidecar modes provide flexible, enriched logging solutions.
This article walks through a complete, reproducible setup for collecting, storing, querying, and visualizing Kubernetes logs with ClickHouse and Grafana, covering architecture choices, agent configurations (OpenTelemetry Collector, Vector, Fluent Bit), schema design, compression results, query examples, performance tuning, and dashboard integration.
This article compares four popular open‑source log collection tools—Logstash, Fluentd, Fluent Bit, and Vector—examining their key features, performance, resource usage, scalability, security, and ecosystem to help enterprises select the most suitable solution for their specific logging needs.
This article explains why Stone Docs switched from SLS/ES to ClickHouse for Kubernetes log storage, outlines the four‑stage architecture (collection, transmission, storage, management), compares DaemonSet, network, and SideCar collection methods, and provides concrete ClickHouse table definitions and Fluent‑Bit configurations for a production‑grade logging pipeline.
This guide shows how to configure Fluent Bit to collect Kubernetes container logs, develop a Go‑based ClickHouse output plugin, deploy the pipeline with ConfigMap, RBAC and DaemonSet resources, define the ClickHouse table schema, and evaluate performance across different log rates.
