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AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
AWS Customer Presenatation - SlingMedia uses AWS
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AWS Customer Presenatation - SlingMedia uses AWS

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Brian Lucas, Lead Architect, SlingMedia talks about how they use AWS cloud at the Enterprise Tour - SF - 2010

Brian Lucas, Lead Architect, SlingMedia talks about how they use AWS cloud at the Enterprise Tour - SF - 2010

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Transcript

  • 1. Sling Media
    Hurry up and Wait
    Hurry up and Wait
  • 2. Transcoding Challenges
    Transcoding converts video from one encoded format to another format.
    Effective real-world transcoding use requires significant CPU power
    Rendering farms
    Significant capex
    Grid environment
  • 3. In the early days
    Before Amazon, transcoding large amounts content was limited to an exclusive audience
    Large companies with budget to support significant capex (rendering farms, entertainment and production houses, SGI)
    Parallel encoding processes across many machines
    Machines largely go unused
    Wasting electricity, IT operations costs, maintenance
  • 4. Problems with a transcoding system
    Batch encoding can either be a horizontal scaling effort or a vertical one
    Faster computers don’t always result in significantly reduced encoding times
    Some codecs unable to multithread
    Generally more efficient to do one 1x transcode per CPU (core)
    Amazon solves the "hurry up and wait" problem in encoding and transcoding
  • 5. Sling.com At-A-Glance
    ContentPartners
    Cloud Ingestion
    Sling.com
    Grid
    Message Queue
    Encoder
    Storage
    Distribution
  • 6. Encoding Architecture
    Message Queue
    SQS
    EC2
    Transcode
    S3 or EBS
    Storage
    S3 or Cloudfront
    Distribution
  • 7. Encoding: How many servers?
    Most cost-efficient to maximize 1 hour (~55 minutes) of usage
    1,000 30 minute videos
    ~15 minutes encoding time per video (2x linear rate)
    (Total number of videos * average encode time in minutes) / (55 (minutes) * number of cores) = number of servers
  • 8. Encoding: Non-scientific cost comparison
    Traditional datacenter
    $3,000 / server * $1,200/yr electricity (8-core)
    (1,000 (videos) x 15 (minutes per video)) / ( 55 (minutes) x 8 (cores))= 34 (servers)
    34 * $3,000 * $1,200 = $142,800 first year capex and run costs
    EC2
    (1,000 (videos) x 15 (minutes per video)) / ( 55 (minutes) x 20 (cores))= 14 (servers)
    14 * $0.68 = $9.52 in costs
  • 9. Conclusion
    Elastic grid
    Ideal for scalable projects, rapid prototyping
    Collect metrics on CPU, network, disk IO
    Launch/terminate instances from metrics
    Encoding/transcoding/map-reduce
    Cost-savings
    Terminate instances after certain time period
    Most cost-efficient to maximize 1 hour of usage
    Use infrastructure-as-a-service where savings make sense (either cost or operational)

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