Industry

Gaming

Infrastructure for interactive experiences

I build the backend infrastructure for games-real-time multiplayer, matchmaking, leaderboards, and live ops. I understand the unique performance and reliability requirements of gaming.

At a glance
Regulations
5 frameworks
KPIs tracked
6 core metrics
Reference stacks
5 patterns
Services
4 engagements
Case studies
0 published
Perspective

How I think about gaming

The architecture, the trade-offs, and where I push back on conventional wisdom.

Game backends operate under constraints that most web engineers never face. A 50ms increase in latency isn't a slow page - it's a player who blames the netcode and refunds the game. A regional server outage during a tournament is a meme on Reddit by the time the postmortem starts. I architect game backends with the assumption that reliability is the product, and that scale is spiky in ways most cloud providers don't model well.

Real-time multiplayer is the hard problem. Authoritative servers, client-side prediction, server reconciliation, lag compensation, and rollback netcode each have their domain - fighting games and shooters live and die on rollback, MMOs run on tick-based authoritative servers, MOBAs split the difference. I help studios design the netcode primitives, deploy stateful sessions onto Kubernetes via Agones, and place game servers at the edge using providers like Multiplay, GameLift, or Edgegap to keep ping budgets under 60ms for 90% of players.

Matchmaking is a queue theory problem dressed up as machine learning. The naive Elo or TrueSkill 2 implementation gets you to launch; the production system has to balance skill, latency, party size, role preference, fairness, queue time, and content variety simultaneously. I build matchmakers using a mix of skill priors, learned ranking, and constraint solvers, with explicit observability so designers can tune the experience without changing code.

Live ops is where the modern games industry actually lives. Battle passes, seasonal events, in-game stores, A/B tested progression curves - all of it driven by data pipelines that need to update faster than weekly patches. I architect live-ops platforms with feature flagging, server-driven UI, Redis-backed leaderboards, and analytics streams that show producers exactly which event mechanic is moving DAU. Crash analytics, retention cohorts, and monetization funnels all live in this layer.

Anti-cheat and trust are the eternal arms race. Server-authoritative game logic is the foundation; client-side anti-cheat (BattlEye, Easy Anti-Cheat) catches the casual cheaters; behavioral models catch the rest. I help studios build the reporting and review pipelines, with ML-assisted triage so the moderation team can focus on the cases that actually need a human. Account security - credential stuffing defenses, device fingerprinting, regional fraud patterns - gets the same rigor as fintech, because the items in your inventory are increasingly worth real money. See a multiplayer build or start a project.

Challenges

What teams struggle with

The recurring problems I see on gaming engagements.

  • 1Real-time multiplayer at scale
  • 2Low-latency matchmaking
  • 3Anti-cheat and security
  • 4Live ops and event systems
  • 5Global player distribution
How I help

Capabilities I bring

Concrete engineering work that resolves the challenges on the left.

  • Real-time game backend systems
  • Matchmaking and ranking systems
  • Leaderboard and progression systems
  • Live ops infrastructure
  • Global edge deployment
Metrics

What teams measure

The KPIs leadership obsesses over in this sector. Most tie back to performance and architecture decisions made years before the dashboard was built.

01

Concurrent player peak (CCU)

Capacity-planning North Star; live tournaments and launch days are 10-50x steady state.

02

p99 round-trip latency

Sub-60ms is the bar for competitive shooters; 100-150ms is acceptable for most action games.

03

Crash-free session rate

Stability metric tracked per platform; >99.5% is standard for premium titles.

04

Day-1 / Day-7 / Day-30 retention

The classic retention triplet that drives monetization and live-ops investment.

05

ARPDAU / conversion to payer

Free-to-play monetization core metrics; payer conversion typically 2-5%.

06

Cheater report rate / detection time

Trust health for competitive titles; lower is better, faster detection prevents toxicity spirals.

Reference stacks

Stacks I see most often

Patterns I reach for first when scoping a gamingengagement. I don't pick technologies for novelty - read more about how I choose.

1

Unity or Unreal client + dedicated server fleets on Agones/Kubernetes or AWS GameLift

2

Redis Cluster for leaderboards, presence, and matchmaking queues; ScyllaDB for player state

3

WebSockets/UDP via uWebSockets, ENet, or QUIC for low-latency transport

4

PlayFab, Nakama, or a custom Go backend for accounts, inventory, and live ops

5

Snowflake or BigQuery for game analytics, with Tinybird or Materialize for real-time dashboards

Technologies

Tools of the trade

The platforms and frameworks I lean on for gaming work.

Building for Gaming?

Let's discuss your specific challenges and how technology can help you ship safely, sleep well, and keep regulators happy.

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