How can Big data accelerate CDN services ?


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CDN (Content delivery network) service offerings has challenges over the way visibility can be provided over the contents as well as the infrastructure. Bigdata solves the challenges by enabling data collection , correlation and analytics over the data pulled from various CDN sources, BigData enables a highly efficient network that enables a constant watch on ROI and help course corrections.

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How can Big data accelerate CDN services ?

  1. 1. How BigData can accelerate CDN services ? AKP @anoopkumar_p #BIGDATA #CDN #HADOOP #HBASE #MAPREDUCE
  2. 2. Scope ● What are CDN service offerings? ● What challenges they face ? ● What are BigData value propositions?
  3. 3. CDN networks ● Content delivery network is an ecosystem that comprises of the Content hosting orchestration- mashup - transport - edge access system ● They are essentially robust , reliable with highest level of performance ● They are an aggregation of various technologies
  4. 4. CDNs are complex multi tier systems VOD Services DVR Services Application/Content Tiers Distribution Services Distribution Tiers Edge Tiers Edge Media Services Load balancer Services Streaming Services Management Tiers Performance management System management Fault management Configuration management ● CDN is an aggregation of technologies ● Each technology has an FCAPS system ● There can be multiple vendors within the same technology tiers ● The Content - nature , organization, needs are very agile
  5. 5. Business challenges with CDN service offering stacks ● ● ● ● ● Contents evolve and the service stacks need to adapt based on content profiles Service stack optimization is profit ! , but difficult Service stack optimization needs 360 degree view of entire ecosystems, which is challenging Service management is achieved by multiple complex bespoke systems ● ● ● ● ›Correlation Analytics of “operational data “ for usage visibility is challenging because of bespoke model implementations of data islands ›Lack of standardization of raw data formats from various data sources ›Need of heavy processing/storing capabilities to store and analyse data from various CDN elements ›Need of future proof implementations to adapt to new content organization and distribution scenarios is limited ›Lesser Flexibility to implement and adapt new services
  6. 6. BigData approaches for solving CDN operational optimization challenges ● Deploy BigData mechanism to collect and analyse log data from various sources of CDN network ● Offload CDN sources from correlation & analytics overheads ● Use a push based mechanism from sources for optimal performance to upload data to BigData engines ● Define a standardized channel to get data from various CDN data sources ● Create a Scalable & Efficient BigData Tier for storing , processing and deriving analytics ● Create a flexible programming model that can be extended for new value engine creations
  7. 7. BigData approaches over CDN VOD Services Streaming Services DVR Services Performance management Application/Content Tiers Distribution Services Distribution Tiers Edge Tiers Management Tiers Edge Media Services Fault management Load balancer Services Configuration management Push Channels Data Sync Service HDFS MAP Reduce (Programming model) - Content consumption profiling - KPI generation - Prediction engines HBASE Analytics Portal System management
  8. 8. BigData Acceleration for CDNs ● ● ● ● ● BigData enables Value Models over CDN assets which provides ○ Content consumption analytics ○ User to Content consumption analytics ○ Content Ranking ○ Server consumption analytics ○ Traffic consumption analytics User profiling based on content consumption Create Foundation models over which Business services can be built The Value Models also give accurate insights to business operations Accelerate the definition and rollout of new CDN business services
  9. 9. Thank You AKP @anoopkumar_p