Engineering
How production infrastructure is designed — topology, platforms, observability, security, and recovery patterns.
A production-grade infrastructure architecture built on a 4-node Proxmox virtualization cluster, featuring functional workload isolation, container orchestration, centralized observability, and automated recovery pipelines.
Architecture
A production environment built on a 4-node Proxmox virtualization cluster, with workloads separated by function to improve isolation, operational control, and maintainability. The environment is organized into dedicated virtual machines for gateway and container management, production applications, databases, and monitoring/security services.
Architecture
The production environment uses layered network and traffic controls to separate public-facing access from internal application, database, and monitoring services. Public traffic is filtered at the edge, routed securely through a central gateway, and passed only to required internal services while keeping databases and management workloads isolated from direct public access.
Architecture
Production applications and supporting services are containerized using Docker and managed primarily through Docker Compose. This provides consistent service configuration, isolated application environments, and a repeatable operational workflow for deploying and operating multiple production workloads.
Architecture
The production environment uses a self-hosted observability stack to provide visibility into infrastructure health, service performance, resource utilization, and application logs.
Architecture
Security is implemented as multiple defensive layers across the edge, network, application, host, and access-management levels to reduce unnecessary exposure, control access, detect suspicious activity, and protect production workloads.
Architecture
Backups are integrated into the production operations workflow to protect application data, database data, configuration, and deployment-related information against accidental deletion, failed changes, service failures, and infrastructure incidents.
Architecture
Structured disaster recovery procedures designed to ensure rapid service restoration and minimal data loss across all production workloads.
Decisions
Documented choices - context, rationale, and accepted trade-offs.
Context
Needed reliable, multi-tier production hosting for applications, databases, and monitoring without resource contention or cloud compute costs.
Rationale
Proxmox VE provides bare-metal hypervisor efficiency, robust VM isolation (Gateway, App, DB, Observability), snapshotting, and cluster management.
Trade-offs
Requires active hypervisor maintenance, host patching, and storage capacity management compared to fully managed cloud instances.
Context
Needed lightweight, declarative container management for 15+ production services with predictable startup and minimal operational overhead.
Rationale
Docker Compose provides version-controlled YAML stack definitions, isolated bridge networking, and reproducible deployments without Kubernetes complexity.
Trade-offs
Lacks native multi-host auto-scaling, requiring manual vertical scaling and host placement decisions.
Context
Needed unified metrics and log visibility across virtual machines and container workloads without prohibitive SaaS observability costs.
Rationale
Prometheus, Grafana, and Loki offer deep telemetry correlation, powerful PromQL/LogQL querying, and full data retention control.
Trade-offs
Requires monitoring and tuning TSDB storage retention, scrape intervals, and indexing performance.
Diagrams
Visual references for topology, platforms, and operational layers. Replace placeholders with your own diagrams.
