Private Online Platform
I handled infrastructure, backend systems, deployments, monitoring, and production issues for a large FiveM platform supporting real communities and daily player traffic. Most of the work was making systems reliable, scalable, and easy to operate long-term.
Reliability under real traffic
The platform supported large public communities with hundreds of concurrent players, live events, voice systems, databases, web dashboards, and real-time game services running together.
My work focused on keeping everything stable during updates, debugging production issues quickly, and building systems that were easy to maintain over time instead of relying on temporary fixes.
Most of the infrastructure was self-managed across Linux and Windows hosts using NGINX, Node.js, Redis, MongoDB, PostgreSQL, Cloudflare, and internal tooling.
Production operations
Most production issues came down to debugging networking, server performance, caching problems, database bottlenecks, deployment mistakes, or game resource instability.
I usually approached incidents by reproducing the problem first, narrowing down possible causes, validating fixes in development, and rolling changes out carefully to avoid impacting live players.
We also built internal documentation, deployment procedures, backups, and monitoring tools to reduce repeated issues over time. A lot of the work was making sure updates could be reverted quickly if something broke in production.
Infrastructure stack
The platform was split into edge routing, backend services, game servers, and multiple database systems depending on workload requirements. Different parts of the stack prioritized low latency, persistence, or operational simplicity.
Edge & proxy
NGINX reverse proxies handled routing, SSL termination, caching, static assets, and traffic forwarding across multiple internal services and game endpoints.
Application tier
Node.js services powered APIs, dashboards, automation systems, WebSocket features, and internal tooling used by both players and staff.
Data tier
MongoDB, PostgreSQL, MySQL, and Redis were used depending on the workload. Work included backups, indexing, migrations, replication planning, and performance debugging.
What the numbers looked like
Combined creator audience
Peak concurrent players
Production services managed
What I took from running it
Observability first
Good logs and monitoring save hours during incidents. Being able to quickly trace failures mattered more than adding more infrastructure.
Small deployments
Smaller, reversible updates made production safer and easier to debug compared to large releases.
Documentation matters
Internal docs, deployment notes, and runbooks made onboarding and maintenance significantly easier over time.