game-servers
Game server architecture, scalability, matchmaking, and backend systems for online games. Build robust, scalable multiplayer infrastructure.
What this skill does
# Game Servers
## Server Architecture Patterns
```
┌─────────────────────────────────────────────────────────────┐
│ SERVER ARCHITECTURES │
├─────────────────────────────────────────────────────────────┤
│ DEDICATED SERVER: │
│ • Server runs game simulation │
│ • Clients send inputs, receive state │
│ • Best security and consistency │
│ • Higher infrastructure cost │
├─────────────────────────────────────────────────────────────┤
│ LISTEN SERVER: │
│ • One player hosts the game │
│ • Free infrastructure │
│ • Host has advantage (no latency) │
│ • Session ends if host leaves │
├─────────────────────────────────────────────────────────────┤
│ RELAY SERVER: │
│ • Routes packets between peers │
│ • No game logic on server │
│ • Good for P2P with NAT traversal │
│ • Less secure than dedicated │
└─────────────────────────────────────────────────────────────┘
```
## Scalable Architecture
```
SCALABLE GAME BACKEND:
┌─────────────────────────────────────────────────────────────┐
│ GLOBAL LOAD BALANCER │
│ ↓ │
├─────────────────────────────────────────────────────────────┤
│ GATEWAY SERVERS │
│ Authentication, Routing, Rate Limiting │
│ ↓ │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ MATCHMAKING │ │ LOBBY │ │ SOCIAL │ │
│ │ SERVICE │ │ SERVICE │ │ SERVICE │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ ↓ │
├─────────────────────────────────────────────────────────────┤
│ GAME SERVER ORCHESTRATOR │
│ (Spawns/despawns based on demand) │
│ ↓ │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────────────────────────────────────────────┐ │
│ │ GAME SERVERS (Regional, Auto-scaled) │ │
│ │ [US-East] [US-West] [EU-West] [Asia] [Oceania] │ │
│ └─────────────────────────────────────────────────────┘ │
│ ↓ │
├─────────────────────────────────────────────────────────────┤
│ DATABASE CLUSTER │
│ [Player Profiles] [Leaderboards] [Match History] [Items] │
└─────────────────────────────────────────────────────────────┘
```
## Matchmaking System
```
MATCHMAKING FLOW:
┌─────────────────────────────────────────────────────────────┐
│ 1. QUEUE: Player enters matchmaking queue │
│ → Store: skill rating, region, preferences │
│ │
│ 2. SEARCH: Find compatible players │
│ → Same region (or expand after timeout) │
│ → Similar skill (±100 MMR, expand over time) │
│ → Compatible party sizes │
│ │
│ 3. MATCH: Form teams when criteria met │
│ → Balance teams by total MMR │
│ → Check for premade groups │
│ │
│ 4. PROVISION: Request game server │
│ → Orchestrator spawns or assigns server │
│ → Wait for server ready │
│ │
│ 5. CONNECT: Send connection info to all players │
│ → IP:Port or relay token │
│ → Timeout if player doesn't connect │
└─────────────────────────────────────────────────────────────┘
```
## Player Data Management
```csharp
// ✅ Production-Ready: Player Session
public class PlayerSession
{
public string PlayerId { get; }
public string SessionToken { get; }
public DateTime CreatedAt { get; }
public DateTime LastActivity { get; private set; }
private readonly IDatabase _db;
private readonly ICache _cache;
public async Task<PlayerProfile> GetProfile()
{
// Try cache first
var cached = await _cache.GetAsync<PlayerProfile>($"profile:{PlayerId}");
if (cached != null)
{
return cached;
}
// Fall back to database
var profile = await _db.GetPlayerProfile(PlayerId);
// Cache for 5 minutes
await _cache.SetAsync($"profile:{PlayerId}", profile, TimeSpan.FromMinutes(5));
return profile;
}
public async Task UpdateStats(MatchResult result)
{
LastActivity = DateTime.UtcNow;
// Update in database
await _db.UpdatePlayerStats(PlayerId, result);
// Invalidate cache
await _cache.DeleteAsync($"profile:{PlayerId}");
}
}
```
## Auto-Scaling Strategy
```
SCALING TRIGGERS:
┌─────────────────────────────────────────────────────────────┐
│ SCALE UP when: │
│ • Queue time > 60 seconds │
│ • Server utilization > 70% │
│ • Approaching peak hours │
│ │
│ SCALE DOWN when: │
│ • Server utilization < 30% for 15+ minutes │
│ • Off-peak hours │
│ • Allow graceful drain (don't kill active matches) │
├─────────────────────────────────────────────────────────────┤
│ PRE-WARMING: │
│ • Spin up servers before expected peak │
│ • Use historical data to predict demand │
│ • Keep warm pool for instant availability │
└─────────────────────────────────────────────────────────────┘
```
## 🔧 Troubleshooting
```
┌─────────────────────────────────────────────────────────────┐
│ PROBLEM: Long matchmaking times │
├─────────────────────────────────────────────────────────────┤
│ SOLUTIONS: │
│ → Expand skill range over time │
│ → Allow cross-region matching │
│ → Reduce minimum player count │
│ → Add bots to fill partial matches │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ PROBLEM: Server crashes during peak │
├─────────────────────────────────────────────────────────────┤
│ SOLUTIONS: │
│ → Pre-warm servers before peak │
│ → Increase max server instances │
│ → Add circuit breakers │
│ → Implement graceful degradation │
└─────────────────────────────────────────────────────────────┘
┌────────────────────────────────────────────Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.