Browse past weeks of engineering reads.
Netflix needed to manage governance, access control, and orchestration of millions of data warehouse tables and tens of thousands of scheduled workloads across their data platform.
Preventing corrupted catalog metadata from reaching millions of Netflix viewers by detecting data transformation failures in production before impact.
Managing millions of data assets, tables, and tens of thousands of scheduled workloads across Netflix's data platform while maintaining proper access control and execution governance at scale.
Netflix needed to efficiently partition and manage petabytes of time series event data across Cassandra clusters while maintaining millisecond-level query latency and handling dynamic workload changes.
Netflix needed to efficiently support diverse graph query patterns (OLAP and OLTP) across different use cases with varying performance requirements using a unified abstraction layer.
Netflix needed to consolidate multiple bespoke data movement connectors for Cassandra across different engineering organizations into a unified, centralized management system.
Netflix needed to efficiently partition and scale time series data across Cassandra clusters to handle petabytes of temporal event data while maintaining millisecond latency query performance.
Netflix needed a unified abstraction layer to efficiently handle multiple graph query paradigms (OLAP and OLTP) with different performance and functionality requirements across diverse business use cases.
Query performance degradation at massive scale (10+ trillion rows, 15M events/second) where repeated identical queries were consuming excessive resources and impacting latency.
Netflix's relational database ecosystem lacked standardization, with databases spread across RDS Postgres and other technologies, leading to inconsistent functionality, suboptimal performance, and higher total cost of ownership.
Netflix's localization analytics infrastructure (tracking dubbing, subtitling, and translation across hundreds of languages and regions) could not keep pace with the rapidly growing scale of global content, making it difficult to derive timely insights for content localization decisions.
Netflix's Graph Search platform for federated enterprise data required users to write structured queries, limiting accessibility and ease of use despite the system being scalable and configurable.