Published on April 26, 2014
Everything I Learned About Scaling Online Games I Learned at Google and eBay Randy Shoup @randyshoup linkedin.com/in/randyshoup
Background CTO at KIXEYE • Making awesome games awesomer (and scalabler and reliabler) Director of Engineering for Google App Engine • World’s largest Platform-as-a-Service Chief Engineer at eBay • Multiple generations of eBay’s real-time search infrastructure
Engineering “Fun” Whole user / player experience • Think holistically about the full end-to-end experience of the user • UX, functionality, performance, bugs, etc. All useful metrics are *proxies* for fun • Performance: load time, frame rate, lag • Technology: latency, availability • Business: acquisition, retention, monetization
Real-Time Strategy Games are … Real-time Spiky Diverse Constantly evolving Constantly pushing boundaries Technically and operationally demanding
Know Your Requirements Less is more • More wood, fewer arrows • Solve 100% of one problem rather than 50% of two • Release one great feature instead of two iffy ones Understand the requirements • e.g., Battle replay • Ephemeral combat • Immutable recording • Manageable storage footprint
Know Your Bottlenecks Log everything Monitor relentlessly Measure bottlenecks and attack the first • “When you solve problem one, problem two gets a promotion” • Theory of Constraints: attacking *any* other problem yields no improvement Accept that your intuition is WRONG (!)
Know Your Distributions “Normal” distribution is *not* normal • Only works for quantities physically constrained on both sides, clustered around a mean • E.g., adult height or weight Leads to invalid analysis and conclusions • Removing outliers • Ignoring real problems • Your (trained) intuition is WRONG (!)
Know Your Distributions Exponential (“Long Tail”) distribution *much* more common • Income, latency, human connections, etc. • Also easy to reason about – only single parameter Percentiles are your best friends (!) • Reasonably characterize any distribution • Measure 90%ile, 99%ile, 99.9%ile • Focus on the real problems • Mean and Standard Deviation are useless
Layering and Responsibility Multiple layers • Client • Game server • Services • Persistence Clarify roles and responsibilities • Client- vs. server-authoritative • Google service layering (+)
Distribution of Data / Work Load-balancing (for stateless work) • Web servers, proxies • Most services Sharding (for stateful work) • Combat servers • Matchmaking • Leaderboards • Databases
Services Simple, well-defined interface Single-purpose Modular and independent Small team Autonomy and responsibility
Component Isolation Combat server for TOME • Highly “twitchy” real-time MOBA combat • Very latency-sensitive Real-time interactions isolated to a single, ephemeral component • No coordination with any central service Highly dynamic load distribution • Router assigns battle to least-loaded server • Requires latency-fairness between players
Asynchrony: Do Work Up Front Custom asset pipeline • Spriting, compression, etc Pre-render “movies” instead of real-time particle effects Tons of caching
Asynchrony: Client Liveness Client continues seamlessly if disconnected • Gameplay more important than immediate synchronization Event loop for rendering • Keep up with the frame rate (!) Default to background processing • Refresh assets • Save client state
Asynchrony: Reactive Server Minimize request latency • Respond as rapidly as possible to client • Queue events / messages for complex work • Service interactions via reliable events Functional Reactive programming • Heavy use of Scala and Akka • Never block (!) • eBay, Google programming models (-)
Small, Independent Teams Studio System • Full-stack, independent game teams • Near-complete autonomy on technology choices, development processes Vendor-customer discipline • Google service teams (+) Reduces contention and coherence
Hire and Retain Top People Hire „A‟ Players • Difference between top and bottom performers is not 1.5x; it’s 10x (!) • (+) Google hiring process Virtuous Cycle • A players bring A players • B players bring C players • Constantly raise the bar Reduces contention and coherence
Play to People‟s Strengths People are not cogs, not fungible • (-) eBay “Train seats” • Destroyed incentives, personal pride, long-term ownership Align work with skills and passion • Symphony instead of Factory (!) • Skills in Flash, Scala, etc. • Build customizability for target developer, not builder (DSL >> code)
Small Details Matter In the very large, the very small matters a *lot* • Subatomic physics and cosmology • eBay and variable-byte encoding (+) • GAE and memcache slab memory allocation (+) Discipline is *which* details matter • Combat server and memory contention • 40% improvement from six characters … • “const ”
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