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
CI/CD, Docker, Kubernetes, automation
Monitoring
Logging, alerting, metrics, observability
Most viewed
Install and configure Deno for web development with systemd and reverse proxy
hostingInstall and configure Uptime Kuma for website monitoring with SSL and email alerts
monitoringInstall and configure Caddy web server with automatic HTTPS and reverse proxy
hostingInstall and configure TimescaleDB with PostgreSQL for high-performance time-series data
databasesInstall and configure Ollama for local AI models on Linux servers
devopsRecently published
Configure PostgreSQL 17 SSL encryption and certificate-based authentication
databasesSet up HAProxy SSL termination with Let's Encrypt certificates
networkingConfigure HAProxy with Consul for dynamic service discovery
networkingConfigure PostgreSQL 17 connection pooling with PgBouncer for high availability
databasesConfigure Kubernetes secrets management with External Secrets Operator and HashiCorp Vault
devopsConfigure DuckDB cluster setup for distributed analytics and high performance workloads
Set up a DuckDB cluster with distributed query processing, network security, and performance optimization for high-throughput analytical workloads across multiple nodes.
Setup DuckDB with Apache Airflow for automated data pipelines
Configure DuckDB as a high-performance analytical database backend for Apache Airflow workflows. Build automated data pipelines that process files, APIs, and databases using DuckDB's columnar engine.
Set 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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