Infrastructure tutorials
Production-grade guides for Linux, servers, security and performance. Copy-paste commands, multi-distro support, written by engineers who run this in production.
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Linux
System administration, shell scripting, package management
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Web servers, reverse proxies, SSL, domains
Security
Firewalls, hardening, encryption, access control
Performance
Caching, optimization, profiling, load testing
Databases
MySQL, PostgreSQL, Redis, backups, replication
Networking
DNS, load balancing, VPN, TCP/IP, routing
DevOps
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Monitoring
Logging, alerting, metrics, observability
Most viewed
Configure Linux system time synchronization with chrony and NTP hardening
linuxInstall and configure CockroachDB cluster with high availability and distributed SQL
databasesInstall and configure PostgreSQL 17 with performance tuning and security hardening
databasesConfigure network interface monitoring with ICMP ping and connectivity testing
networkingInstall and configure ArgoCD for GitOps continuous deployment with RBAC and SSL
devopsRecently published
Configure NGINX rate limiting and DDoS protection with advanced security rules
securityConfigure centralized logging with rsyslog and logrotate for system monitoring and log management
linuxConfigure Kubernetes vertical pod autoscaler for resource optimization and cost management
devopsImplement Kubernetes workload rightsizing with VPA recommendations and cost analysis
devopsConfigure Kubernetes cluster autoscaler with mixed instance types for cost optimization
devopsConfigure Kubernetes vertical pod autoscaler for resource optimization and cost management
Set up VPA to automatically adjust CPU and memory requests for your Kubernetes workloads. Reduce resource waste and optimize costs by letting VPA analyze actual usage patterns and rightsizing containers.
Implement Kubernetes workload rightsizing with VPA recommendations and cost analysis
Set up Vertical Pod Autoscaler to automatically optimize resource requests and limits for your Kubernetes workloads. Create cost analysis dashboards to track resource utilization and identify opportunities for rightsizing containers in production clusters.
Configure Kubernetes cluster autoscaler with mixed instance types for cost optimization
Set up Kubernetes cluster autoscaler 1.30 with mixed instance types and spot instances to automatically scale nodes based on demand while minimizing infrastructure costs through intelligent instance selection and workload optimization.
Configure Apache Airflow DAG performance optimization best practices
Optimize Apache Airflow DAGs for production with parallelism tuning, resource allocation strategies, and performance monitoring. Learn executor configuration, task dependency optimization, and troubleshooting techniques for high-throughput workflows.
Set up Kubernetes custom metrics autoscaling with Prometheus adapter for application-specific scaling
Configure Prometheus adapter to expose custom application metrics to Kubernetes Horizontal Pod Autoscaler for intelligent scaling based on business metrics like queue depth, response time, and user load instead of basic CPU/memory usage.
Integrate TimescaleDB with Telegraf for metrics collection and time-series monitoring
Set up TimescaleDB with PostgreSQL and configure Telegraf to collect system and application metrics. Create continuous aggregates and monitoring dashboards for comprehensive time-series analysis and alerting.
Monitor Kubernetes cluster with Prometheus Operator for comprehensive observability
Set up complete cluster monitoring using Prometheus Operator with automated metrics collection, custom dashboards, and intelligent alerting for production Kubernetes environments.
Set up NGINX monitoring with Prometheus and Grafana for web server observability
Monitor your NGINX web server performance and health with Prometheus metrics collection and Grafana dashboards. Set up comprehensive observability including request rates, response times, error tracking, and automated alerting for production web servers.
Integrate OpenTelemetry with ELK stack for unified observability and distributed tracing
Set up a comprehensive observability stack by integrating OpenTelemetry Collector with Elasticsearch, Logstash, and Kibana for distributed tracing, metrics collection, and unified monitoring across microservices and applications.
Configure Kubernetes horizontal pod autoscaler for dynamic scaling based on resource metrics
Set up HPA with CPU and memory targets for automatic pod scaling. Configure metrics server and Prometheus adapter for custom metrics monitoring. Enable dynamic workload scaling based on resource utilization.
Configure OpenTelemetry sampling strategies for high-traffic applications
Learn how to implement probabilistic, deterministic, and adaptive sampling strategies in OpenTelemetry to optimize distributed tracing performance and reduce storage costs in high-traffic production environments.
Monitor container performance with Prometheus and cAdvisor for comprehensive metrics collection
Set up comprehensive container monitoring with cAdvisor, Prometheus, and Grafana to collect detailed metrics on CPU, memory, network, and disk usage. This tutorial covers installation, configuration, and alerting for production-ready container performance monitoring.
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