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Using ScyllaDB for
Distribution of Game
Assets in Unreal Engine
Joakim Lindqvist, Senior Tools Programmer
Joakim Lindqvist
■ Senior Tools Developer within the Foundation team of
Unreal Engine
■ 15 years experience working in games
■ Based out of Stockholm, Sweden
■ The complexity of building games
■ Overview of Unreal Cloud DDC
■ Future work
Agenda
The Complexity of
Building Games
Games are Complicated to Make
■ 2 major types of content, source code and game assets
■ Large assets
■ Large teams work on them
■ Specialized skill - spread out across the world
The Process of Cooking Data
■ Cooking is data transformation
■ Historically cached on network file systems within a office
■ Geo distribution
■ Work From Home
■ Headache to scale storage
■ Can take hours to start up the editor without caching
Unreal Cloud DDC
Cached Objects
■ Custom self describing binary
format called Compact Binary
■ Structured object with
attachments that are content
addressed
■ Content addressing
■ Deduplication
■ Avoids replicating the same
content
{
“name”: “largeFile”,
“size” : 2480,
“attachment”: 9fffabc5e0a…1f084f8c5e
}
■ Kubernetes
■ 5 regions
■ 7 TB local nvme cache
■ ~50 TB S3 storage
■ 10-500 users per region
■ Last access tracking
Unreal Cloud DDC
Architecture
ScyllaDB
(Metadata)
Web api
Local NVME
AWS S3
(Blob
Storage)
ScyllaDB
(Metadata) Web api
AWS S3
(Blob
Storage)
Why ScyllaDB
■ Performance sensitive workload
■ Geo replicated database
■ Eventual consistency works well with our workload
■ Small deployment (2-3 nodes of i4i.xlarge/i4i.2xlarge) in 5 DCs
■ ~3000 req/s per node
Future Work
Future Work
■ Small blob storage in ScyllaDB
■ ScyllaDB on Azure
■ Performance improvements on the API
■ Extending to more workloads
■ Source Code: https://github.com/EpicGames
Unreal Engine
Thank You
Stay in Touch
Joakim Lindqvist
joakim.lindqvist@epicgames.com
twitter.com/J0CC0
github.com/jocco
www.linkedin.com/in/jocco/

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Using ScyllaDB for Distribution of Game Assets in Unreal Engine

  • 1. Using ScyllaDB for Distribution of Game Assets in Unreal Engine Joakim Lindqvist, Senior Tools Programmer
  • 2. Joakim Lindqvist ■ Senior Tools Developer within the Foundation team of Unreal Engine ■ 15 years experience working in games ■ Based out of Stockholm, Sweden
  • 3. ■ The complexity of building games ■ Overview of Unreal Cloud DDC ■ Future work Agenda
  • 5. Games are Complicated to Make ■ 2 major types of content, source code and game assets ■ Large assets ■ Large teams work on them ■ Specialized skill - spread out across the world
  • 6.
  • 7. The Process of Cooking Data ■ Cooking is data transformation ■ Historically cached on network file systems within a office ■ Geo distribution ■ Work From Home ■ Headache to scale storage ■ Can take hours to start up the editor without caching
  • 9. Cached Objects ■ Custom self describing binary format called Compact Binary ■ Structured object with attachments that are content addressed ■ Content addressing ■ Deduplication ■ Avoids replicating the same content { “name”: “largeFile”, “size” : 2480, “attachment”: 9fffabc5e0a…1f084f8c5e }
  • 10. ■ Kubernetes ■ 5 regions ■ 7 TB local nvme cache ■ ~50 TB S3 storage ■ 10-500 users per region ■ Last access tracking Unreal Cloud DDC
  • 11. Architecture ScyllaDB (Metadata) Web api Local NVME AWS S3 (Blob Storage) ScyllaDB (Metadata) Web api AWS S3 (Blob Storage)
  • 12. Why ScyllaDB ■ Performance sensitive workload ■ Geo replicated database ■ Eventual consistency works well with our workload ■ Small deployment (2-3 nodes of i4i.xlarge/i4i.2xlarge) in 5 DCs ■ ~3000 req/s per node
  • 14. Future Work ■ Small blob storage in ScyllaDB ■ ScyllaDB on Azure ■ Performance improvements on the API ■ Extending to more workloads
  • 15. ■ Source Code: https://github.com/EpicGames Unreal Engine
  • 16. Thank You Stay in Touch Joakim Lindqvist joakim.lindqvist@epicgames.com twitter.com/J0CC0 github.com/jocco www.linkedin.com/in/jocco/