A Tool for Practical Garbage Collection Analysis in the Cloud
Increasingly more and more web applications are migrating to the cloud owing to higher scalability, low cost, and reduced time-to-market. For example, Amazon Web Services (AWS) hosts PBS, Reddit, Netflix, Zynga. Although the elasticity of cloud enables scaling, both up and down, a cluster in respons...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Increasingly more and more web applications are migrating to the cloud owing to higher scalability, low cost, and reduced time-to-market. For example, Amazon Web Services (AWS) hosts PBS, Reddit, Netflix, Zynga. Although the elasticity of cloud enables scaling, both up and down, a cluster in response to the incoming traffic, it makes performance modeling and analysis non-trivial. In the context of Java-based web applications, a key aspect is the performance of the garbage collector (GC). Existing tools for analyzing the performance of a GC are tailored for a single Java process, hence not suitable for use in the cloud. To this end, in this paper we present a tool called {\bf Shrek} for analyzing GC performance in the cloud. {\bf Shrek} facilitates analysis of GC logs of Java applications deployed across a cluster of hundreds of nodes in the cloud. Further, it supports analytics such as time series analysis of GC performance metrics to determine ``bad", nodes and supports visualization of, for example, promotion rate from the young generation to the old generation. {\bf Shrek} has already been used to diagnose performance problems for multiple applications at Netflix. |
---|---|
DOI: | 10.1109/IC2E.2013.13 |