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 Deno for web development with systemd and reverse proxy
hostingInstall and configure Caddy web server with automatic HTTPS and reverse proxy
hostingInstall and configure Ollama for local AI models on Linux servers
devopsInstall and configure Uvicorn ASGI server with systemd and reverse proxy for FastAPI applications
hostingInstall and configure Uptime Kuma for website monitoring with SSL and email alerts
monitoringRecently published
Setup Node.js error tracking with Sentry for production monitoring and debugging
monitoringImplement Node.js application monitoring with Prometheus metrics and Grafana dashboards
monitoringImplement OSPF multi-area design with FRRouting and advanced routing policies
networkingConfigure Istio security policies with external authorization services integration
securityImplement Docker network security with custom bridge networks and container isolation
securityConfigure Spark on Kubernetes with cluster autoscaling for dynamic workloads
Deploy Apache Spark 3.5 on Kubernetes with automatic cluster scaling, dynamic resource allocation, and comprehensive monitoring for production data processing workloads.
Set up Spark Streaming with Kafka and Delta Lake for real-time analytics
Configure Apache Spark 3.5 with Kafka integration and Delta Lake support for building production-grade real-time analytics pipelines with ACID transactions and streaming capabilities.
Implement Spark SQL performance optimization with Catalyst optimizer and advanced tuning
Optimize Apache Spark 3.5 SQL performance using Catalyst optimizer with advanced query tuning, adaptive query execution, and production-grade configuration for high-throughput analytics workloads.
Configure Kafka Streams for real-time data processing and analytics
Set up Kafka Streams applications with Java development environment to build real-time data processing pipelines for analytics and monitoring workloads.
Configure Spark Kubernetes Operator with MinIO for cloud-native analytics
Deploy Apache Spark on Kubernetes with the Spark Operator and MinIO object storage for scalable big data processing. Configure RBAC, SSL certificates, and persistent storage for production-ready analytics workloads.
Optimize ClickHouse performance for high-throughput workloads with advanced tuning and memory management
Learn how to optimize ClickHouse for high-throughput analytics workloads through advanced memory configuration, query performance tuning, storage engine optimization, and connection pooling strategies.
Set up TimescaleDB high availability with streaming replication and automatic failover
Configure TimescaleDB with PostgreSQL streaming replication for high availability. Set up primary and standby servers with hot standby mode, implement automatic failover with pg_auto_failover, and monitor replication status for production-ready time-series database clustering.
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.
Configure TimescaleDB automated data retention policies for efficient storage management
Set up automated data retention and compression policies in TimescaleDB to optimize storage usage and maintain database performance. Learn to configure drop_chunks and compression policies with monitoring.
Configure ClickHouse materialized views for real-time analytics with performance optimization
Set up ClickHouse materialized views to transform raw data into real-time aggregations. Configure performance optimization with memory tuning and monitoring for high-throughput analytics workloads.
Set up Spark 3.5 Delta Lake with MinIO for ACID transactions and big data analytics
Configure Apache Spark 3.5 with Delta Lake and MinIO object storage for ACID transactions, data versioning, and distributed analytics processing. Includes complete setup for production-grade data lake architecture.
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.
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