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Scalability and Load in Online Games


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The huge growth in online games over the last few years presents unique challenges in terms of scalability and backend infrastructure. Launch day can mean an immediate increase in load from a few hundred to millions of users, each of whom may be conducting dozens of transactions per minute as they purchase extra weapons or gear. Games often process many more writes than reads, some of which are low-latency and compute-intensive while others are high-latency but must be shared among hundreds of global servers. Multiplayer games require enough global player state to allow for matchmaking, while not allowing for a single point of failure. Games require both centralized servers to allow for frequent updates and decentralized ones to allow for low-latency play worldwide. And to prevent cheating, authoritative logic needs to stay server-side. With $24 billion in revenue in 2014 (and projected to grow 4x that by 2020), the online game industry is in need of all the creative solutions that researchers can offer. This talk will outline specific high-performance computing challenges faced by games and the pros and cons of the current solutions being used.

Published in: Technology
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Scalability and Load in Online Games

  1. 1. Scalability and Load in Online Games 1 James Gwertzman @gwertz
  2. 2. Promise & peril of live game operations • Launched 3/2/12 • Shot to top 10 • Servers crashed • Offline for 168 days • $27M lost revenue • Re-launched 8/17/12 • Top-grossing game for nearly 3 years LTD revenue: $150M+ Source: AppAnnie, NPD, ThinkGaming 2 Updated more than 45 times Rank history for top grossing games, iOS in United States
  3. 3. Build game Launch The old days…
  4. 4. Build game Build backend Launch Build tools for ops team Segment & target customers Deploy servers Business intelligence Offers & Promotions Update content Host in-game events Customer service Nowadays… Business intelligence User Acquisition
  5. 5. Characteristics of live games • Many more writes than reads (primarily driven by analytics) • Authoritative server-side game logic (to prevent cheating) • Millions of users (often with transient relationships) • Peak load often hits on day one of release • Must be scalable, global, and reliable all at once • Game studios often inexperienced at large-scale system design • Testing w/ real user “stories” at scale is hard but critical 5
  6. 6. + Live ops tools and dashboards (mission control for the whole team) Back-end services (cross-platform, one-stop shop) + Integration with other partners (building out a full ecosystem) and many more coming... 6
  7. 7. Typical backend services • Player Accounts – Authentication – Profile Management – Account Linking • Data Storage – Per player – Per title – Per character (under one player) – Files / CDN delivery • Commerce – Catalog Management – Virtual Currencies – Player Inventory – In-game Purchasing – Receipt validation (Apple/Google/Amazon) – Marketing and Promotion • In-game Marketing – Push Notifications – In-game Messaging • Product Management – Analytics and Reporting – Customer Segmentation – Customer Support Tools – Abuse Reporting and Banning • Social – Friends Lists – Player Chat – Leaderboards – Game forum integration – Trading / gifting • Multiplayer – Photon integration (real-time / turn-based) – Matchmaking – Custom game server hosting – Server monitoring • Game logic – Server-hosted JavaScript 7
  8. 8. Availability Zone B Oregon AWS cloud: PlayFab Web Services Amazon Route 53 ( Amazon EC2 (API handling) Matchmaker Instance Instance Game Server Monitor DynamoDB Amazon RDS Amazon S3 Amazon RedshiftReports service Instance Logs Architecture Overview Matchmaker (Secondary) Instance Virginia Availability Zone A Amazon EC2 (API handling) Elastic Load Balancing Cross-zone storage Game Client Game Manager (Dashboards) Amazon EC2 (Virtual game servers) Tokyo Amazon EC2 (Virtual game servers) Sydney Physical game servers Physical game servers Amazon EC2 (Virtual game servers) Local disk Local disk Local disk Physical game servers
  9. 9. Dealing with elastic load • Peak load is often launch day – Hard to predict actual load • We solve using elastic compute & storage solutions • No transaction support in DB, so must solve at logic level 9
  10. 10. Applying actions to user segments • Users are grouped into segments based on behavior • Games apply actions to segments – Send a push notification – Grant an item • Need both batch and real-time processing • We use a hybrid model, with duplicate storage – Redshift for bulk actions – DynamoDB for individual triggers 10
  11. 11. Global state for matchmaking • Matching users for a game is harder than it sounds – Millions of players – Must be atomic – Lots of state and complex rules • We use a single server, w/ fallover – State is written though to DB – If primary fails, secondary reads in state from DB and takes over – This happens very quickly… 11
  12. 12. Thank you James Gwertzman ( @gwertz or @playfabnetwork Create a free account today at 12