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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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 Django Redis caching and session storage for high-performance web applications
Set up Redis as both cache backend and session storage for Django applications. Improve page load times and user experience with proper Redis configuration and Django integration.
Configure Apache Airflow DAG performance optimization best practices
Optimize Apache Airflow DAGs for production with parallelism tuning, resource allocation strategies, and performance monitoring. Learn executor configuration, task dependency optimization, and troubleshooting techniques for high-throughput workflows.
Set up Apache Airflow performance monitoring with DataDog agent integration and custom dashboards
Configure comprehensive Apache Airflow monitoring using DataDog agent to track DAG performance, task execution metrics, and resource utilization with custom dashboards and automated alerting for production workflow management.
Implement Airflow load balancing with Celery executor for high availability workflows
Set up Apache Airflow with Celery executor, Redis cluster backend, HAProxy load balancing, and auto-scaling workers for production-grade workflow orchestration with high availability.
Configure Apache Airflow high availability with CeleryExecutor and Redis clustering for production deployments
Set up Apache Airflow with CeleryExecutor and Redis clustering for high availability production deployments. Configure multiple workers, load balancing, monitoring, and automated failover to handle enterprise-scale workflow orchestration with zero downtime.
Configure Apache Airflow with SSL certificates and NGINX reverse proxy for secure production deployment
Set up Apache Airflow behind NGINX with SSL certificates, security headers, and reverse proxy configuration for production-grade deployments with HTTPS termination.
Configure Airflow DAG security and isolation with RBAC policies
Set up comprehensive security for Apache Airflow with role-based access control, DAG-level permissions, and resource isolation. Configure user authentication, implement fine-grained security policies, and establish monitoring for production-grade workflow orchestration.
Configure Apache Airflow performance optimization with connection pooling and resource tuning
Optimize Apache Airflow performance through advanced connection pooling, resource tuning, and Celery executor configuration. Learn to scale workers, configure database pools, and implement comprehensive monitoring for production workflows.
Implement custom Prometheus exporters for application metrics collection and monitoring
Build production-grade custom Prometheus exporters in Python and Go to collect application-specific metrics. Learn exporter architecture, metric types, systemd deployment, and Prometheus integration for comprehensive application monitoring.
Set up Apache Airflow high availability with CeleryExecutor and Redis clustering
Deploy Apache Airflow in high availability mode using CeleryExecutor with Redis clustering for task distribution, PostgreSQL connection pooling, and load-balanced webservers for production-grade workflow orchestration.
Implement comprehensive Apache Airflow DAG testing and validation strategies with pytest and best practices
Learn to implement production-grade testing for Apache Airflow DAGs using pytest, including unit tests for DAG structure validation, integration testing with test databases, and automated validation pipelines with CI/CD integration.
Configure Apache Airflow monitoring with Prometheus alerts and Grafana dashboards
Set up comprehensive monitoring for Apache Airflow with Prometheus metrics collection, StatsD integration, and custom Grafana dashboards. Configure automated alerting for DAG failures, task timeouts, and system health issues.
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