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
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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 Uvicorn ASGI server with systemd and reverse proxy for FastAPI applications
hostingInstall and configure Ollama for local AI models on Linux servers
devopsConfigure Linux system time synchronization with chrony and NTP hardening
linuxRecently published
Configure Kubernetes network policies for enhanced cluster security
securitySet up Kubernetes persistent volume snapshots and backup automation
devopsImplement Kafka Streams exactly-once processing semantics with Java applications
devopsImplement ClickHouse backup automation with compression and S3 integration
databasesInstall and configure Filebeat 8.15 for efficient log shipping to ELK stack
monitoringImplement Kafka Streams exactly-once processing semantics with Java applications
Configure Kafka cluster and Java applications for exactly-once processing semantics with transaction state management, idempotent producers, and EOS isolation levels for reliable stream processing.
Configure Kafka Streams state stores and RocksDB optimization for high-performance streaming applications
Configure Kafka Streams state stores with RocksDB optimization for high-performance streaming applications. Learn custom state store configurations, RocksDB tuning parameters, and monitoring techniques for production-grade stream processing.
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.
Implement Kafka Streams processing applications with Java and Scala for real-time data analytics
Build production-ready Kafka Streams applications using Java and Scala for real-time data processing, including stateless transformations, stateful aggregations, windowing, and stream joins with exactly-once semantics.
Implement Kafka Streams applications for real-time data processing with Java and Scala
Build production-grade Kafka Streams applications for real-time data processing using Java and Scala. Configure stream processing topologies, implement windowing operations, and deploy scalable streaming applications with monitoring.
Implement Spark streaming with Kafka and MinIO for real-time analytics and big data processing
Build a production-ready real-time analytics pipeline using Apache Spark 3.5 streaming, Kafka for data ingestion, and MinIO for distributed object storage. This tutorial covers fault-tolerant streaming configurations and end-to-end pipeline implementation.
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