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AWS Customer Presenatation - SlingMedia uses AWS
 

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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    AWS Customer Presenatation - SlingMedia uses AWS AWS Customer Presenatation - SlingMedia uses AWS Presentation Transcript

    • Sling Media
      Hurry up and Wait
      Hurry up and Wait
    • 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
    • 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
    • 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
    • Sling.com At-A-Glance
      ContentPartners
      Cloud Ingestion
      Sling.com
      Grid
      Message Queue
      Encoder
      Storage
      Distribution
    • Encoding Architecture
      Message Queue
      SQS
      EC2
      Transcode
      S3 or EBS
      Storage
      S3 or Cloudfront
      Distribution
    • 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
    • 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
    • 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)