2007
DOI: 10.1007/978-3-540-75694-1_11
|View full text |Cite
|
Sign up to set email alerts
|

Bottleneck Detection Using Statistical Intervention Analysis

Abstract: Abstract. The complexity of today's large-scale enterprise applications demands system administrators to monitor enormous amounts of metrics, and reconfigure their hardware as well as software at run-time without thorough understanding of monitoring results. The Elba project is designed to achieve an automated iterative staging to mitigate the risk of violating Service Level Objectives (SLOs). As part of Elba we undertake performance characterization of system to detect bottlenecks in their configurations. In … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2010
2010
2020
2020

Publication Types

Select...
5
2
1

Relationship

3
5

Authors

Journals

citations
Cited by 19 publications
(7 citation statements)
references
References 7 publications
0
7
0
Order By: Relevance
“…These control limits Statistical Intervention Analysis Bottleneck identification. [43] describe the range of expected variability in the data over a period of time. When new observations fall outside outside the set control limits they are detected as anomalies and their cause(s) must be identified and corrected [87].…”
Section: Statistical Process Controlmentioning
confidence: 99%
“…These control limits Statistical Intervention Analysis Bottleneck identification. [43] describe the range of expected variability in the data over a period of time. When new observations fall outside outside the set control limits they are detected as anomalies and their cause(s) must be identified and corrected [87].…”
Section: Statistical Process Controlmentioning
confidence: 99%
“…In order to approximate the exact workload that can saturate the critical hardware resource, the procedure uses a statistical intervention analysis [11] on the SLO-satisfaction of a system. The main idea of such analysis is to evaluate the stability of the SLO-satisfaction of the system as workload increases; the SLO-satisfaction should be nearly constant under low workload and start to deteriorate significantly once the workload saturates the critical hardware resource.…”
Section: ) Inferring a Good Allocation Of Local Soft Resourcesmentioning
confidence: 99%
“…The main idea of such analysis is to evaluate the stability of the SLO-satisfaction of the system as workload increases; the SLO-satisfaction should be nearly constant under low workload and start to deteriorate significantly once the workload saturates the critical hardware resource. Readers who are interested in more details can refer to our previous paper [11].…”
Section: ) Inferring a Good Allocation Of Local Soft Resourcesmentioning
confidence: 99%
“…In practice we use a simple statistical intervention analysis [13] to approximate N , where the main idea of this analysis is to find the minimum load (N ) beyond which the increments of throughput becomes negligible with further increment of load. Suppose the load in a server varies between [N min , N max ]; then we divide [N min , N max ] into k even intervals (e.g., k = 100) and calculate the average throughput in each load interval based on the load/throughput samples we collected during the experimental period.…”
Section: Congestion Point N Determinationmentioning
confidence: 99%