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
Hosting & Servers
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
CI/CD, Docker, Kubernetes, automation
Monitoring
Logging, alerting, metrics, observability
Most viewed
Install and configure CockroachDB cluster with high availability and distributed SQL
databasesConfigure network interface monitoring with ICMP ping and connectivity testing
networkingInstall and configure ArgoCD for GitOps continuous deployment with RBAC and SSL
devopsInstall and configure PostgreSQL 17 with performance tuning and security hardening
databasesInstall and configure Loki for centralized log aggregation with Grafana integration
monitoringRecently published
Implement Kubernetes cluster autoscaler for automatic node scaling
devopsConfigure SSH port forwarding and tunneling for secure connections
securityIntegrate MinIO with Prometheus monitoring for performance metrics and observability
monitoringImplement ScyllaDB disaster recovery with cross-region replication
databasesConfigure OpenVPN LDAP authentication for enterprise users with Active Directory integration
securityImplement Kubernetes cluster autoscaler for automatic node scaling
Configure Kubernetes cluster autoscaler to automatically add and remove worker nodes based on pod resource demands. This tutorial covers cloud provider integration, scaling policies, and monitoring for production-grade horizontal scaling.
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.
Implement Kubernetes cluster autoscaling with Helm charts and KEDA for dynamic workload scaling
Configure comprehensive Kubernetes autoscaling with cluster autoscaler for node management, KEDA for event-driven pod scaling, and vertical pod autoscaler for resource optimization. This tutorial covers production-grade deployment using Helm charts with monitoring and optimization strategies.
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