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How LinkedIn Uses gRPC

8 engineering articles about gRPC from LinkedIn's engineering team

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The article discusses how LinkedIn developed the Contextual Agent Playbooks & Tools (CAPT) to enhance AI coding agents with organizational context, enabling them to better assist engineers in their...
Ajay Prakash
17 min read
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The article discusses how LinkedIn enhanced its recommendation systems using SGLang, an open-source LLM serving framework.
Steven Shimizu
10 min read
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The article discusses LinkedIn's implementation of a Stateful Workload Operator for managing stateful systems on Kubernetes.
Michael Youssef
14 min read
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The article discusses LinkedIn's innovative use of Apache Beam for real-time streaming processing, handling over 4 trillion events daily across more than 3,000 pipelines.
Bingfeng Xia
16 min read
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The article discusses LinkedIn's transition to a GraphQL architecture for product development, highlighting the challenges faced with their existing microservices and the reasons for adopting Graph...
LinkedIn Engineering Team
13 min read
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LinkedIn
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LinkedIn has integrated Google Protocol Buffers (Protobuf) with Rest. li to enhance microservices performance, achieving significant reductions in latency and improvements in resource utilization.
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The article discusses the implementation of multi-task learning for homepage feed ranking at LinkedIn using TensorFlow.
Ian Ackerman
14 min read
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