Seer: Leveraging big data to navigate the complexity of performance debugging in cloud microservices
Y Gan, Y Zhang, K Hu, D Cheng, Y He… - Proceedings of the …, 2019 - dl.acm.org
Performance unpredictability is a major roadblock towards cloud adoption, and has
performance, cost, and revenue ramifications. Predictable performance is even more critical …
performance, cost, and revenue ramifications. Predictable performance is even more critical …
Architectural implications of function-as-a-service computing
Serverless computing is a rapidly growing cloud application model, popularized by
Amazon's Lambda platform. Serverless cloud services provide fine-grained provisioning of …
Amazon's Lambda platform. Serverless cloud services provide fine-grained provisioning of …
Face it yourselves: An llm-based two-stage strategy to localize configuration errors via logs
Configurable software systems are prone to configuration errors, resulting in significant
losses to companies. However, diagnosing these errors is challenging due to the vast and …
losses to companies. However, diagnosing these errors is challenging due to the vast and …
“Leagile” software development: An experience report analysis of the application of lean approaches in agile software development
In recent years there has been a noticeable shift in attention from those who use agile
software development toward lean software development, often labelled as a shift “from …
software development toward lean software development, often labelled as a shift “from …
Transfer learning for performance modeling of configurable systems: An exploratory analysis
Modern software systems provide many configuration options which significantly influence
their non-functional properties. To understand and predict the effect of configuration options …
their non-functional properties. To understand and predict the effect of configuration options …
Challenges and opportunities: an in-depth empirical study on configuration error injection testing
Configuration error injection testing (CEIT) could systematically evaluate software reliability
and diagnosability to runtime configuration errors. This paper explores the challenges and …
and diagnosability to runtime configuration errors. This paper explores the challenges and …
White-box analysis over machine learning: Modeling performance of configurable systems
Performance-influence models can help stakeholders understand how and where
configuration options and their interactions influence the performance of a system. With this …
configuration options and their interactions influence the performance of a system. With this …
Testing configuration changes in context to prevent production failures
Large-scale cloud services deploy hundreds of configuration changes to production systems
daily. At such velocity, configuration changes have inevitably become prevalent causes of …
daily. At such velocity, configuration changes have inevitably become prevalent causes of …
Inferring program transformations from singular examples via big code
Inferring program transformations from concrete program changes has many potential uses,
such as applying systematic program edits, refactoring, and automated program repair …
such as applying systematic program edits, refactoring, and automated program repair …
Understanding and auto-adjusting performance-sensitive configurations
Modern software systems are often equipped with hundreds to thousands of configurations,
many of which greatly affect performance. Unfortunately, properly setting these …
many of which greatly affect performance. Unfortunately, properly setting these …