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Three Steps to Modern Media Asset
Management with Active Archive
Housekeeping
• Recording
• Available on-demand approximately 5 minutes after
today’s presentation
• Resources
• Questions
• Please rate this webinar
Agenda
• Learn about Moonbot & Taking Flight
• Hear specifics about Moonbot Studios
– Why the cloud?
– Goals
– Details, details, details
– Result Statistics
• Using Google Cloud Platform for Rendering
• Ensuring Accessibility and Performance
Today’s Speakers
Sara Hebert
Director of Marketing
Moonbot Studios
Jeff Kember
Cloud Solutions Architect
Google Cloud Platform
Aaron Wetherold
Systems Engineer
Avere Systems
Brennan Chapman
Pipeline Supervisor
Moonbot Studios
Moonbot Studios
Sara Hebert, Director of Marketing, Moonbot Studios
• FOUNDED: 2009
• LOCATION: Shreveport, Louisiana
• EMPLOYEES: 50+
• AWARDS: 239, including…
– 1 Oscar
– 4 Emmys
– 14 Cannes Lions
– 12 Clios
– 5 Webbys
“Top-shelf creative pedigree” – FAST COMPANY
“Storytelling of the future” – LA TIMES
Taking Flight to the Cloud
Brennan Chapman, Pipeline Supervisor, Moonbot Studios
Why we decided to use the cloud
• 3 overlapping projects with high volume of renders
– 30 second spot
– 5 minute short film
– 11 minute pilot episode
• No space on-site for required equipment
– Additional space, power, networking needed for on-site
• Faster Scaling
Our Current Setup
• Moonbot has about 50 people on staff
• 12 Lighters across the 3 projects
• Software
– Maya 2015
– Arnold
– Nuke
• Qube Render Management
• Shotgun
Our Current Setup
• Isilon Storage NAS – 100TB
• 32 IBM blades
– 2x E5450 @ 3Ghz
– 32GB RAM
• 40 Dell FX2 (Rentals)
– 2x E5-2650 v3 @ 2.3Ghz
– 64GB RAM
Arnold Notes
• We found it more cost effective to use Arnold licenses on fastest
nodes.
• Old IBM blades were 4x slower than the new FX2s
Targets We Set
• Overnight Renders
• Compute power should scale hourly if needed
• Add up to 2,500 additional cores
• Easy to use for both pipeline and artists
• Need forecasting system to predict when we need cloud capacity
• Minimal amount of new tools
• Consistency between setup of on-site render nodes and cloud
Targets We Set
• Use Qube for Render Management
• Only use cloud for Arnold renders, keep Nuke renders on-site
Previous Experiences with Cloud
• Zync for Silent, a project for
Dolby Laboratories
– Rendered a few thousand
frames
– Worked well, but added
complexity for artists
How to Handle Storage
• Projects required transfer of about 12TB
• Limited to a 100Mbps connection
• Need to copy assets to cloud
• Need to copy results back on-site
How to Handle Storage
• Avere solved most of this for us
• Used a vFXT Edge filer
How to Handle Storage
• Presents the Avere storage to render nodes the same way on-site
renders nodes see on-site storage
• Handles all transfers to and from cloud for assets and rendered
images
• Uses clustered system to spread load across multiple nodes
• Simple to setup
• Mounts via NFS
How to Handle Storage
• Faster and easier to setup using Avere to automatically load only
the required files needed to perform each render
Vs.
• Developing scripts that find and copy all dependencies, then start
the render
How to Handle Storage
• We used the cache read and write with 30 second write-back
• Using the write cache allowed the render nodes finish faster,
transfer was then completed by the Avere cluster
• ISSUE: No way to get notification from Avere when the writeback
transfers were finished.
Cloud Render Node Configuration
• Cent OS
• Use fstab to mount nfs storage from Avere just like on-site nodes
mount the nfs storage from the Isilon
• Used Ansible to configure our instance, and then saved it to an
image in Google Cloud
Preemptible vs On-Demand Instances
• On-Demand
– Higher cost
– Availability guaranteed
• Preemptible instances
– Lower Cost, 1/3 of price
– Restarts every 24 hours
– Availability not guaranteed
Instance Groups
• Google Cloud offers a system for managing pools of instances using
Instance Groups and Templates.
• This automatically handles starting and stopping instances.
• When using pre-emptible instances, they are automatically
added/removed based on their availability.
• Using this system we had spin-up times at around 2-3 minutes.
Security
• No public IP’s on render nodes
• All traffic goes through VPN tunnel
Arnold Notes
• Not all n1-standard-32 nodes are the same
• Haswell was best performance, only available in certain zones
• Arnold was 20% faster on the Haswell vs Ivy Bridge
Qube Integration
• Utilized startup and shutdown scripts from Google to facilitate
adding and removing workers to Qube
• Instance Groups create instances with new names every time
• Need to register and unregister workers on startup and shutdown
• Didn’t have to configure much else, everything else was setup just
like it is on-site
Forecasting Renders
• We utilized preview frames to estimate render times for the farm
• Preview frames usually include the first, middle and last frames of
each shot sent to the farm
• Preview frames have the highest priority on the farm
Forecasting Workflow
• Artists submit their jobs to the farm before they leave.
• Pipeline team waits until preview frames have been rendered
• Run forecasting tool which calculates the # of cloud render nodes
required to finish the renders by the next morning
• Spin-up the required amount of nodes on Google Cloud
• Shutdown the instances the next morning
Tile Rendering
• On submission of jobs to Qube we built support to split frames into
tiles.
• Goal with tiles is to decrease maximum time for a render to about 30
minutes.
• Less risk of losing work in Pre-emptible instances
• Allows frames to finish quicker, especially preview frames
Stats
• Ping time to Google Cloud Iowa data: 35ms
• Ingress: 12TB
• Egress: 2TB
• 60% of renders were done on Google Cloud
• 4,000 Render Jobs Total
• 3,000 Arnold Jobs
• ~1,800 were completed on Google Cloud
Stats
• 124,000 Frames
• 50,000 Render Hours
• Average render time per frame: ~30min
Results
• We met our deadlines!
• Worked really well once we got the VPN connection figured out
• Will save a lot of time planning and budgeting
• Allows render farm to work around the schedule instead of the
schedule around the farm.
• Saves time managing local hardware
• Allows us to stay nimble as a small company, don’t have to invest
large capital into render farm
Google Cloud Platform for
Rendering & Animation
Jeff Kember, Cloud Solutions Architect,
Google Cloud Platform
Pipeline services for end-to-end workflow
Ingestion Rendering Transcoding Archival Distribution
Run at Google scale
Fast VM startup times
with consistent performance
Custom Machine Types
70+ points of presence
across 33 countries
Category-defining cold
storage with Nearline
Sustained
use discounts
Pay for what you use:
Per minute billing
Preemptible VMs
Moore’s Law pricing, passed onto customers
Partner ecosystem
Strong networking partners
for both CDN and
interconnect use cases
Strong partners across all
media use cases
Growing list of click-to-deploy
partner solutions
Security
Industry standard
compliance and certification
Custom-built security in data
centers from hardware to OS
Data encryption in transit and
at rest on Google’s network
Pipeline services for end-to-end workflow
Ingestion Rendering Transcoding Archival Distribution
Ingestion: Quickly and securely upload media
Cloud Interconnect
ensures the fastest, most reliable route by
connecting your network to Google directly
or via service provider partners
70+ points of presence
across 33 countries ensures the
low latency and reliability users expect
from Google services
Offline media import/export
enables customers to have large volumes
of data shipped to partners who upload data
on their behalf
Cloud render farm (burst + sustained)
Rendering for Large Studios
Create
100’s–1000’s of artists
Global distribution
Render
20K–100K cores
Avere performance acceleration
Storage
Multiple tiers
Cost effective and resilient
Artists
LA, Vancouver, NY,
London, India
On-premises render farm
Avere FXT
Google
Compute
Engine
Virtual
Avere
FXT
VIRTUAL
Google Cloud Storage
Standard + Nearline
On-premises storage
Physical computers T1: 100’s TB T2: Multi-PB T3: Tape
Hybrid Rendering Environment - Caching with Avere
Run at Google scale
Fast VM startup times
with consistent performance
Custom Machine Types
70+ points of presence
across 33 countries
Category-defining cold
storage with Nearline
Select Rendering Customers
Pipeline services for end-to-end workflow
Ingestion Rendering Transcoding Archival Distribution
Archival: Nearline storage
Industry-defining
cold storage product
Data available instantly:
~3 second response times
Low cost:
1 cent per GB/month
Archival & Disaster Recovery - Cloud Storage & Nearline
Cloud Accessibility
Aaron Wetherold, Systems Engineer, Avere Systems
Render Cloud Bursting Use Case
Customer Requirements
• Overflow render capacity into
Google Cloud Platform
• No copying of data back and
forth
• Avoid deploying additional
hardware
• No application rewrite
• Provide flexibility to adjust to
project demands
Avere Solutions
• Deploy the scalable vFXT cluster
within GCE
• Access and accelerate existing
on-prem NAS and GCS storage
while hiding access latency
• Dynamically tier active working
set into SSD and DRAM
• Standard NFS and SMB client
access
• Ease of deployment,
management and expansion
The Challenge
Google Cloud StorageGoogle Compute Engine
On-Prem Storage
NAS
On-Prem Compute
Virtual
Render
Farm
Render
Farm
Artist
Workstations
The Avere vFXT Solution
Google Cloud StorageGoogle Compute Engine
On-Prem Storage
NAS
On-Prem Compute
Virtual
Render
Farm
Render
Farm
Artist
Workstations
Virtual
FXT
Avere Deployment Flexibility
Google Cloud StorageGoogle Compute Engine
Physical
FXT
On-Prem Storage
NAS Object
On-Prem Compute
Virtual
Render
Farm
Render
Farm
Artist
Workstations
Virtual
FXT
Avere Product Line
Virtual FXT
Performance
Google
Google
Hardware
n1-highmem-
8
n1-highmem-
32
FXT 3200 FXT 3850 FXT 4850
DRAM (GB) 52 208 96 288 288
SSD (TB)
1 (persistent)
or 1.5 (local)
4 (persistent) - 0.8 4.8
SAS (TB) - - 4.8 7.8 -
Network 10GbE 10GbE 2x10GbE, 6x1GbE
Physical FXT
4850
3850
3200
Protocols
•To Client: NFSv3
(TCP/UDP), CIFS (SMB1.0
& 2.0)
•To Core Filer: NFSv3
(TCP), S3 API
Clustering
•Cluster from 3 to 50 FXT
nodes for performance and
capacity scaling
•HA failover, mirrored writes,
redundant network ports &
power
Management
•GUI, analytics, email alerts,
SNMP, XML-RPC interface,
policy-based management•Persistent and Local SSD Support
•Standard, DRA and Nearline GCS Support
•Per minute billing
Next Steps
• Ask questions
• Review the attachments section for relevant resources
• Rate this webinar
Today’s Speakers
Sara Hebert
Director of Marketing
Moonbot Studios
Jeff Kember
Cloud Solutions Architect
Google Cloud Platform
Aaron Wetherold
Systems Engineer
Avere Systems
Brennan Chapman
Pipeline Supervisor
Moonbot Studios
Moonbotstudios.com
cloud.google.com Averesystems.com

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Rendering Takes Flight

  • 1. Three Steps to Modern Media Asset Management with Active Archive
  • 2. Housekeeping • Recording • Available on-demand approximately 5 minutes after today’s presentation • Resources • Questions • Please rate this webinar
  • 3. Agenda • Learn about Moonbot & Taking Flight • Hear specifics about Moonbot Studios – Why the cloud? – Goals – Details, details, details – Result Statistics • Using Google Cloud Platform for Rendering • Ensuring Accessibility and Performance
  • 4. Today’s Speakers Sara Hebert Director of Marketing Moonbot Studios Jeff Kember Cloud Solutions Architect Google Cloud Platform Aaron Wetherold Systems Engineer Avere Systems Brennan Chapman Pipeline Supervisor Moonbot Studios
  • 5. Moonbot Studios Sara Hebert, Director of Marketing, Moonbot Studios
  • 6. • FOUNDED: 2009 • LOCATION: Shreveport, Louisiana • EMPLOYEES: 50+ • AWARDS: 239, including… – 1 Oscar – 4 Emmys – 14 Cannes Lions – 12 Clios – 5 Webbys “Top-shelf creative pedigree” – FAST COMPANY “Storytelling of the future” – LA TIMES
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  • 9. Taking Flight to the Cloud Brennan Chapman, Pipeline Supervisor, Moonbot Studios
  • 10. Why we decided to use the cloud • 3 overlapping projects with high volume of renders – 30 second spot – 5 minute short film – 11 minute pilot episode • No space on-site for required equipment – Additional space, power, networking needed for on-site • Faster Scaling
  • 11. Our Current Setup • Moonbot has about 50 people on staff • 12 Lighters across the 3 projects • Software – Maya 2015 – Arnold – Nuke • Qube Render Management • Shotgun
  • 12. Our Current Setup • Isilon Storage NAS – 100TB • 32 IBM blades – 2x E5450 @ 3Ghz – 32GB RAM • 40 Dell FX2 (Rentals) – 2x E5-2650 v3 @ 2.3Ghz – 64GB RAM
  • 13. Arnold Notes • We found it more cost effective to use Arnold licenses on fastest nodes. • Old IBM blades were 4x slower than the new FX2s
  • 14. Targets We Set • Overnight Renders • Compute power should scale hourly if needed • Add up to 2,500 additional cores • Easy to use for both pipeline and artists • Need forecasting system to predict when we need cloud capacity • Minimal amount of new tools • Consistency between setup of on-site render nodes and cloud
  • 15. Targets We Set • Use Qube for Render Management • Only use cloud for Arnold renders, keep Nuke renders on-site
  • 16. Previous Experiences with Cloud • Zync for Silent, a project for Dolby Laboratories – Rendered a few thousand frames – Worked well, but added complexity for artists
  • 17. How to Handle Storage • Projects required transfer of about 12TB • Limited to a 100Mbps connection • Need to copy assets to cloud • Need to copy results back on-site
  • 18. How to Handle Storage • Avere solved most of this for us • Used a vFXT Edge filer
  • 19. How to Handle Storage • Presents the Avere storage to render nodes the same way on-site renders nodes see on-site storage • Handles all transfers to and from cloud for assets and rendered images • Uses clustered system to spread load across multiple nodes • Simple to setup • Mounts via NFS
  • 20. How to Handle Storage • Faster and easier to setup using Avere to automatically load only the required files needed to perform each render Vs. • Developing scripts that find and copy all dependencies, then start the render
  • 21. How to Handle Storage • We used the cache read and write with 30 second write-back • Using the write cache allowed the render nodes finish faster, transfer was then completed by the Avere cluster • ISSUE: No way to get notification from Avere when the writeback transfers were finished.
  • 22. Cloud Render Node Configuration • Cent OS • Use fstab to mount nfs storage from Avere just like on-site nodes mount the nfs storage from the Isilon • Used Ansible to configure our instance, and then saved it to an image in Google Cloud
  • 23. Preemptible vs On-Demand Instances • On-Demand – Higher cost – Availability guaranteed • Preemptible instances – Lower Cost, 1/3 of price – Restarts every 24 hours – Availability not guaranteed
  • 24. Instance Groups • Google Cloud offers a system for managing pools of instances using Instance Groups and Templates. • This automatically handles starting and stopping instances. • When using pre-emptible instances, they are automatically added/removed based on their availability. • Using this system we had spin-up times at around 2-3 minutes.
  • 25. Security • No public IP’s on render nodes • All traffic goes through VPN tunnel
  • 26. Arnold Notes • Not all n1-standard-32 nodes are the same • Haswell was best performance, only available in certain zones • Arnold was 20% faster on the Haswell vs Ivy Bridge
  • 27. Qube Integration • Utilized startup and shutdown scripts from Google to facilitate adding and removing workers to Qube • Instance Groups create instances with new names every time • Need to register and unregister workers on startup and shutdown • Didn’t have to configure much else, everything else was setup just like it is on-site
  • 28. Forecasting Renders • We utilized preview frames to estimate render times for the farm • Preview frames usually include the first, middle and last frames of each shot sent to the farm • Preview frames have the highest priority on the farm
  • 29. Forecasting Workflow • Artists submit their jobs to the farm before they leave. • Pipeline team waits until preview frames have been rendered • Run forecasting tool which calculates the # of cloud render nodes required to finish the renders by the next morning • Spin-up the required amount of nodes on Google Cloud • Shutdown the instances the next morning
  • 30. Tile Rendering • On submission of jobs to Qube we built support to split frames into tiles. • Goal with tiles is to decrease maximum time for a render to about 30 minutes. • Less risk of losing work in Pre-emptible instances • Allows frames to finish quicker, especially preview frames
  • 31. Stats • Ping time to Google Cloud Iowa data: 35ms • Ingress: 12TB • Egress: 2TB • 60% of renders were done on Google Cloud • 4,000 Render Jobs Total • 3,000 Arnold Jobs • ~1,800 were completed on Google Cloud
  • 32. Stats • 124,000 Frames • 50,000 Render Hours • Average render time per frame: ~30min
  • 33. Results • We met our deadlines! • Worked really well once we got the VPN connection figured out • Will save a lot of time planning and budgeting • Allows render farm to work around the schedule instead of the schedule around the farm. • Saves time managing local hardware • Allows us to stay nimble as a small company, don’t have to invest large capital into render farm
  • 34. Google Cloud Platform for Rendering & Animation Jeff Kember, Cloud Solutions Architect, Google Cloud Platform
  • 35. Pipeline services for end-to-end workflow Ingestion Rendering Transcoding Archival Distribution
  • 36. Run at Google scale Fast VM startup times with consistent performance Custom Machine Types 70+ points of presence across 33 countries Category-defining cold storage with Nearline
  • 37. Sustained use discounts Pay for what you use: Per minute billing Preemptible VMs Moore’s Law pricing, passed onto customers
  • 38. Partner ecosystem Strong networking partners for both CDN and interconnect use cases Strong partners across all media use cases Growing list of click-to-deploy partner solutions
  • 39. Security Industry standard compliance and certification Custom-built security in data centers from hardware to OS Data encryption in transit and at rest on Google’s network
  • 40. Pipeline services for end-to-end workflow Ingestion Rendering Transcoding Archival Distribution
  • 41. Ingestion: Quickly and securely upload media Cloud Interconnect ensures the fastest, most reliable route by connecting your network to Google directly or via service provider partners 70+ points of presence across 33 countries ensures the low latency and reliability users expect from Google services Offline media import/export enables customers to have large volumes of data shipped to partners who upload data on their behalf
  • 42. Cloud render farm (burst + sustained) Rendering for Large Studios Create 100’s–1000’s of artists Global distribution Render 20K–100K cores Avere performance acceleration Storage Multiple tiers Cost effective and resilient Artists LA, Vancouver, NY, London, India On-premises render farm Avere FXT Google Compute Engine Virtual Avere FXT VIRTUAL Google Cloud Storage Standard + Nearline On-premises storage Physical computers T1: 100’s TB T2: Multi-PB T3: Tape
  • 43. Hybrid Rendering Environment - Caching with Avere
  • 44. Run at Google scale Fast VM startup times with consistent performance Custom Machine Types 70+ points of presence across 33 countries Category-defining cold storage with Nearline Select Rendering Customers
  • 45. Pipeline services for end-to-end workflow Ingestion Rendering Transcoding Archival Distribution
  • 46. Archival: Nearline storage Industry-defining cold storage product Data available instantly: ~3 second response times Low cost: 1 cent per GB/month
  • 47. Archival & Disaster Recovery - Cloud Storage & Nearline
  • 48. Cloud Accessibility Aaron Wetherold, Systems Engineer, Avere Systems
  • 49. Render Cloud Bursting Use Case Customer Requirements • Overflow render capacity into Google Cloud Platform • No copying of data back and forth • Avoid deploying additional hardware • No application rewrite • Provide flexibility to adjust to project demands Avere Solutions • Deploy the scalable vFXT cluster within GCE • Access and accelerate existing on-prem NAS and GCS storage while hiding access latency • Dynamically tier active working set into SSD and DRAM • Standard NFS and SMB client access • Ease of deployment, management and expansion
  • 50. The Challenge Google Cloud StorageGoogle Compute Engine On-Prem Storage NAS On-Prem Compute Virtual Render Farm Render Farm Artist Workstations
  • 51. The Avere vFXT Solution Google Cloud StorageGoogle Compute Engine On-Prem Storage NAS On-Prem Compute Virtual Render Farm Render Farm Artist Workstations Virtual FXT
  • 52. Avere Deployment Flexibility Google Cloud StorageGoogle Compute Engine Physical FXT On-Prem Storage NAS Object On-Prem Compute Virtual Render Farm Render Farm Artist Workstations Virtual FXT
  • 53. Avere Product Line Virtual FXT Performance Google Google Hardware n1-highmem- 8 n1-highmem- 32 FXT 3200 FXT 3850 FXT 4850 DRAM (GB) 52 208 96 288 288 SSD (TB) 1 (persistent) or 1.5 (local) 4 (persistent) - 0.8 4.8 SAS (TB) - - 4.8 7.8 - Network 10GbE 10GbE 2x10GbE, 6x1GbE Physical FXT 4850 3850 3200 Protocols •To Client: NFSv3 (TCP/UDP), CIFS (SMB1.0 & 2.0) •To Core Filer: NFSv3 (TCP), S3 API Clustering •Cluster from 3 to 50 FXT nodes for performance and capacity scaling •HA failover, mirrored writes, redundant network ports & power Management •GUI, analytics, email alerts, SNMP, XML-RPC interface, policy-based management•Persistent and Local SSD Support •Standard, DRA and Nearline GCS Support •Per minute billing
  • 54. Next Steps • Ask questions • Review the attachments section for relevant resources • Rate this webinar
  • 55. Today’s Speakers Sara Hebert Director of Marketing Moonbot Studios Jeff Kember Cloud Solutions Architect Google Cloud Platform Aaron Wetherold Systems Engineer Avere Systems Brennan Chapman Pipeline Supervisor Moonbot Studios Moonbotstudios.com cloud.google.com Averesystems.com

Editor's Notes

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  2. We are a multiplatform storytelling studio specializing in feature-quality animation, traditional publishing and game development Shreveport Growing quickly – everyone on the team is an artist, hardworking and nimble Founded in 2009 by Bill, Brandon and Lampton
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