What is it about?
Modern software systems often rely on microservices, which are smaller, independent components that work together to handle user requests. These systems are designed to keep running smoothly even when small errors occur during communication between components. However, these unnoticed errors can still slow down user responses. In this study, we analyzed billions of operations within Uber's microservice architecture to understand how these errors impact performance. We developed a method to measure and reduce the delays caused by these errors, improving system speed by up to 30% in some cases. Our findings offer practical solutions for optimizing complex software systems.
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Why is it important?
Our study addresses a significant yet often overlooked challenge in modern microservice architectures: the impact of non-fatal errors on system performance. Unlike previous research that primarily focuses on fatal errors or total system failures, our work highlights the hidden inefficiencies caused by recoverable errors that do not crash the system but increase latency. Using billions of real-world data points from Uber's microservices, we developed a novel methodology to quantify and mitigate these delays, achieving up to 30% latency reduction for critical services. This is particularly timely as organizations increasingly adopt microservices at scale, and our findings offer actionable insights to enhance their efficiency and user experience.
Perspectives
This publication is particularly meaningful to me because it bridges the gap between academic research and practical, real-world challenges in modern software systems. Working with such a vast dataset and addressing a critical, yet underexplored, issue in microservices was both intellectually stimulating and rewarding. Collaborating with talented co-authors on this project has deepened my appreciation for the complexity of distributed systems and the potential for meaningful optimization. I hope this work inspires others to look beyond catastrophic failures and address the hidden inefficiencies that impact the performance and scalability of systems we rely on daily.
Zhizhou Zhang
Uber Technologies Inc.
Read the Original
This page is a summary of: The Tale of Errors in Microservices, Proceedings of the ACM on Measurement and Analysis of Computing Systems, December 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3700436.
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