Handbook Of Data Reliability Engineering
A Comprehensive Guide To Manage Reliability In Data Organizations
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The SRE principles pioneered by Google have proven effective in managing web and mobile applications over time. Drawing from this, Data Reliability Engineering (DRE) applies a similar ethos to data workloads. DRE prioritizes post-production observability methods, emphasizing observability, monitoring, performance, efficiency, and cost optimization. This book thoroughly explores the DRE framework, ensuring dependable data solutions. However, attaining the data reliability "North Star," minimizing data downtime, and meeting quality metrics like accuracy, freshness, and latency, is pivotal. The c...
The SRE principles pioneered by Google have proven effective in managing web and mobile applications over time. Drawing from this, Data Reliability Engineering (DRE) applies a similar ethos to data workloads. DRE prioritizes post-production observability methods, emphasizing observability, monitoring, performance, efficiency, and cost optimization. This book thoroughly explores the DRE framework, ensuring dependable data solutions. However, attaining the data reliability "North Star," minimizing data downtime, and meeting quality metrics like accuracy, freshness, and latency, is pivotal. The challenge lies in enhancing observability within intricate data solutions where numerous pipelines operate incessantly, while adhering to Google's SRE principles. This book provides comprehensive guidance from three angles: People, Process, and Technology. Unlike many SRE publications focusing solely on technology, it stresses the importance of aligning people and processes with the technical vision. In absence of this alignment, theory prevails over practicality. Fundamentally, this book dives into end-to-end Data Reliability Engineering strategies. Considering it potentially the first of its kind, it serves as a foundational resource for crafting strategies and roadmaps towards establishing data reliability.
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