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How Gannett Achieved Scalability and Agility with NoSQL – Couchbase Live NYC

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Gannett is one of America’s largest media companies. Gannett provides full national coverage through 93 local and national sites that reach 96 million total monthly digital visitors. Gannett’s total mobile reach alone hits 31 million unique monthly visitors. To support our various products we needed our stories, videos and photos to flow through our publishing system and be retrievable in a matter of seconds. In this talk we will discuss how Gannett moved away from SQL Server to Couchbase for storing updating and retrieving millions of documents. We will also discuss how we use Couchbase to power our User Generated Content. Finally we will also touch on our future plans to integrate N1QL into our new Authoring and Scheduling systems.

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How Gannett Achieved Scalability and Agility with NoSQL – Couchbase Live NYC

  1. 1. Couchbase @ GANNETT How Couchbase has become an integral part of GANNETT’ s next generation publishing systems
  2. 2. Who we are Alon Motro - Content Platform Services Manager. Oversees publishing systems and the presentation APIs that power the consuming applications. Kristopher Alexander - Platform Architecture Lead. Works with various stakeholders within the Technology division on technical vision, process, and culture.
  3. 3. Who we are ● Gannett is one of America’s largest media companies. ● We provide full national coverage through 93 local and national sites that reach 96 million total monthly digital visitors. ● Sites include USA TODAY, The Indianapolis Star, The Arizona Republic, etc. ● For each property we produce a suite of products including desktop and mobile sites and native iOS and Android applications. ● Our digital products produce many types of assets including articles, photo galleries, videos and oembeds ● We also provide numerous APIs for developers as well as syndicated content for vendors
  4. 4. Our Current Architecture
  5. 5. Current Challenges ● SQL Server is extremely expensive ● Utilize on-prem pet servers that have difficulty scaling ● Numerous replication issues with SQL Server ● A multitude of business logic coded into Stored Procedures causes significant delay between publish time and presentation time
  6. 6. How We Used to Retrieve an Asset/Front
  7. 7. What were our transition goals? ● Decrease the latency between publish time and presentation time ● Remove business logic from data layer ● Write as you want to Read ● Allow for growth and scalability in the cloud and move away from pet servers ● Lower cost
  8. 8. New Architecture - Phase 1
  9. 9. How We Retrieve an Asset/Front Now
  10. 10. New Architecture - Phase 2
  11. 11. A Telling Load Test ● Our publishing system required around 500 writes per second and 3000 reads per second ● Successful Load Test of 10,000 writes per second and 30,000 reads per second ● Included spikes of up to 300,000 reads ● This was done with 8 r3.xlarge nodes in Amazon (32 vCPU and 172 GB Memory Allocated)
  12. 12. UGC http://www.usatoday. com/yourtake/
  13. 13. Memcached Replacement ● 5 Memcached Servers shared by several applications ● Each application had to manage its own keyspace correctly ● Moved to a single couchbase cluster ● Each application gets a bucket
  14. 14. Mongo DB Replacement ● Application Settings ● User Preferences For The CMS ● Mean JS/ Mean IO ● Workflow Planning Module
  15. 15. Cloud Strategy ● “Hybrid Cloud” approach that blends different public offerings with Gannett’s private cloud ● Automation tools simplify configuration management ● RabbitMQ, Solr, Couchbase, and Node JS replace .NET, SQL Server, and MSMQ ● Reduced Cache footprint in the architecture
  16. 16. N1QL ● Reduce reliance on documents that point at other keys (manifests) ● Reduce reliance on views ● Migrate some simple lookups from Solr ● Reduce cognitive load for interacting with documents
  17. 17. Questions?

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