This article walks through a small team’s step‑by‑step journey to low‑cost automated operations, covering monitoring with Prometheus, configuration versioning via Ansible, CI/CD pipelines in Jenkins, and scalable script generation using Cookiecutter.
This guide walks small teams through step‑by‑step implementation of low‑cost automated operations, covering basic monitoring with Prometheus, configuration versioning via Ansible, CI/CD pipelines using Jenkins, and scaling practices, enabling gradual evolution toward enterprise‑grade DevOps architectures.
This article explains how to configure Kubernetes Horizontal Pod Autoscaler (HPA) to scale workloads based on custom business metrics collected by Prometheus, covering installation of Metrics Server, deployment of a demo app, setup of the Prometheus adapter, and practical load‑testing steps.
This article shares practical Go microservice building experiences, covering gRPC-based communication, TLS security, request tracing, and comprehensive monitoring with Prometheus, including metric selection, alerting, and log management using Logrus and Graylog, to help reduce coupling and improve system observability.
This article outlines a large‑scale monitoring solution for distributed microservice environments, comparing traditional ELK logging with a custom GPE stack (Grafana, Prometheus, Exporter, Consul), detailing architecture, components, workflows, and practical considerations for reliable observability.
This guide explains how to choose between push and pull monitoring models, introduces Prometheus architecture and metric syntax, shows Node.js client integration with code examples, and covers Alertmanager features and Grafana visualization for effective application monitoring.
This article shares practical experiences of using Prometheus for monitoring complex services, covering metric types, PromQL query techniques, naming conventions, service discovery with file‑based configs, high‑availability sharding, alerting via Alertmanager, and visualisation with Grafana, providing actionable guidance for reliable observability.
This article examines the unique challenges of monitoring containers, outlines three categories of metrics to collect, compares host‑centric and layered monitoring architectures, provides detailed methods for gathering CPU, memory, I/O and network data via cgroup files and Docker commands, and shares practical insights, tooling recommendations, and a Q&A session for effective container observability.
From early manual deployments to a sophisticated, multi-layered monitoring stack—including ELK, Zabbix, Statsd, Grafana, and Prometheus—Bilibili’s ops team shares the evolution, challenges, and lessons learned in building scalable, automated infrastructure for massive internet traffic.
This article examines the daunting performance‑optimization challenges of a complex PaaS architecture, breaks the system into control, data, and monitoring subsystems, defines concrete metrics, demonstrates testing with Prometheus and other tools, and shares practical automation techniques to accelerate iterative improvements.
This article translates and expands a comparative analysis of Prometheus against Graphite, InfluxDB, OpenTSDB, Nagios, and Sensu, covering their applicability, data models, storage mechanisms, architecture, and strengths to help readers choose the most suitable time‑series database for monitoring needs.
This article explains why monitoring is essential for system reliability, outlines the key components of a comprehensive monitoring framework, compares data collection methods, and presents practical container monitoring solutions—from Docker stats to cAdvisor with InfluxDB and Grafana, as well as Kubernetes and Mesos integrations.
This article explains why Docker services need monitoring, distinguishes black‑box and white‑box approaches, compares self‑hosted and SaaS monitoring stacks, and reviews key components and popular tools such as Prometheus, InfluxDB, Grafana, Datadog, and Sysdig.
