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 ArgoCD for GitOps continuous deployment with RBAC and SSL
devopsInstall and configure CockroachDB cluster with high availability and distributed SQL
databasesInstall and configure PostgreSQL 17 with performance tuning and security hardening
databasesInstall and configure Loki for centralized log aggregation with Grafana integration
monitoringInstall and configure WireGuard VPN server with client management
networkingRecently published
Configure Nagios SNMP monitoring for network devices with automated discovery and templates
monitoringIntegrate Elasticsearch 8 with Prometheus monitoring and Grafana dashboards
monitoringSet up NGINX web application firewall with ModSecurity 3 and OWASP Core Rule Set
securityConfigure NGINX reverse proxy with advanced caching and load balancing
hostingConfigure Netdata alerts with Slack and Microsoft Teams for real-time monitoring notifications
monitoringSet up ClickHouse and Kafka real-time data pipeline with streaming analytics
Build a production-ready real-time data pipeline using ClickHouse for high-performance analytics and Apache Kafka for streaming data ingestion. Configure clustering, replication, and automated data processing workflows.
Install and configure DuckDB for analytical workloads with Python integration
Set up DuckDB, the high-performance analytical database, with CLI tools and Python integration for fast OLAP queries and data analytics workloads.
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