LinkedIn faced challenges in scaling its platform as its user base and content grew. They adopted a distributed and partitioned graph system, built a search service using Lucene, and migrated to a service-oriented architecture. They also used caching and implemented data collection with Kafka. Additionally, LinkedIn developed tools like Rest.li for API development, introduced super blocks to manage multiple services, and implemented multi-data center support. Other advanced developments included real-time analytics with Pinot and managing authorization at scale.
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10 Insights On Real-World Container Usage (Sponsored)Humble Beginning with LeoThe First Need of ScalingScaling LeoLatest articlesKilling Leo with Service-Oriented ArchitectureManaging Hypergrowth with CachingData Collection with KafkaScaling the Organization with InversionAdvanced Developments Around ScalabilityConclusionSPONSOR USSort: