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World Congress 2024 • Aug 20, 2024 • Session details

Building the platform for providing ML predictions based on real-time player activity

Artem Volk , Fabian Zillgens

How do you process millions of telemetry events to personalize gameplay in under 500 milliseconds? Explore Phoenix Games' decoupled, fault-tolerant machine learning architecture on AWS.

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#1 about 2 min

Overview of Phoenix Games and real-time customization goals

The challenge of adapting player experiences in real-time requires fast data iterations and automated process pipelines.

#2 about 2 min

Customizing player experiences in the Emergency HQ title

Machine learning models apply dynamic gameplay modifications to surface relevant store purchases alongside tailored mission difficulties.

#3 about 2 min

Microservice architecture requirements for unobtrusive event collection

Delivering dynamic game features demands simple cross-studio integration without heavy client SDK dependencies.

#4 about 2 min

AWS infrastructure stack and data flow pipeline overview

A simplified architecture highlights the event collection, offline data processing, and machine learning customization mechanisms.

#5 about 3 min

Managing raw game event execution and payload structures

Handling millions of out-of-order game stream instances requires distinct tracking of real event occurrence timestamps versus upload times.

#6 about 3 min

Comparing offline data analytics with online stream processing

Utilizing Apache Spark extracts long-term insights while real-time user activity is handled via unbound Apache Flink queries.

#7 about 2 min

Managing fast real-time player states using profile APIs

Storing live active user snapshot profiles enables rapid integration of both historical offline data and instant inferences.

#8 about 2 min

Demonstrating pipeline latency thresholds during player purchases

Tracking a native player transaction through Flink visualizes how the profile snapshot API updates within hundreds of milliseconds.

#9 about 2 min

Delivering dynamic game packages using external decision models

Decoupled AWS lambda functions empower independent machine learning calculations and simple rule-based feature testing configurations.

#10 about 2 min

Analyzing customization payloads alongside model inference decisions

Displaying specific package deals relies on observing distinct machine learning delays and debugging underlying player delay logic.

#11 about 2 min

Enabling autonomous deployments and independent monitoring controls

Empowering data scientists with Terraform dashboards minimizes blockages while securing the pipeline against flawed algorithm updates.

#12 about 1 min

Measuring API infrastructure limits and platform pipeline latency

Analyzing sub-second turnaround constraints uncovers operational bottlenecks when calling endpoints and executing live updates simultaneously.

#13 about 5 min

Evaluating deployment pipeline compromises and infrastructure scaling costs

Balancing the advantages of resilient decoupled microservices highlights fundamental trade-offs surrounding duplicate data and high storage costs.

#14 about 2 min

Processing extreme event volumes and validating machine operations

Operating at massive scale emphasizes the importance of data verification to prevent custom features from hurting core business revenue.

#15 about 3 min

Executing automated model generation and dynamic user packaging

Empowering data analysts to build localized cloud containers directly enables specific item delivery configurations tailored to individual gamers.

#16 about 4 min

Implementing Lambda request load balancing and player privacy controls

Handling high volume interactions requires strict AWS container load provisioning and limited personal asset storage tracking parameters.

Matching moments

4:29 min

Shifting data analytics from monetization to player experience design

Johanna Pirker Johanna Pirker · World Congress 2021

2:21 min

Building real-time AI coaching and identity applications

Brendan Ittelson Brendan Ittelson +1 · World Congress 2026 North America

2:13 min

Modernizing legacy applications for real-time streaming data consumption

Farooq Sheikh Farooq Sheikh +3 · World Congress 2025

4:31 min

Optimizing system scalability and real-time push capabilities

David Leitner · World Congress 2022

1:47 min

Deploying real-time media workloads on cloud infrastructure

Brendan Ittelson Brendan Ittelson +1 · World Congress 2026 North America

2:59 min

Integrating data analytics and machine learning as interactive elements

Johanna Pirker Johanna Pirker · World Congress 2021

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