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Artemis - PowerPoint PPT Presentation


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Artemis. Distributed system. Hunting for Bugs with Artemis. Dryad Overview. Logs. System Architecture. Data Collection. Data collection. Database. View. GUI. Plug-ins. GUI. Plug-ins. Conclusions. Hunting for Bugs with Artemis. Gabriela F. Creţu-Ciocârlie Mihai Budiu

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Presentation Transcript
slide1

Artemis

Distributed system

Hunting for Bugs with Artemis

Dryad Overview

Logs

System Architecture

Data Collection

Data collection

Database

View

GUI

Plug-ins

GUI

Plug-ins

Conclusions

hunting for bugs with artemis

Hunting for Bugswith Artemis

Gabriela F. Creţu-Ciocârlie

Mihai Budiu

Moises Goldszmidt

Microsoft Research, Silicon Valley

WASL 2008

This presentation is built and should be viewed with pptPlex: http://www.officelabs.com/projects/pptPlex/Pages

artemis goal
Artemis Goal

One-stop shop for performance analysis of distributed systems

principles
Principles
  • 1) Modular: Separate generic from application specific parts
  • 2) Extensible: add new analyses via plug-ins
  • 3) Interactive: human expert part of the analysis loop
slide5

Distributed system

Distributed

Logs

Data collection

Database

Local

View

GUI

Plug-ins

slide6

Distributed system

Application-Specific

Logs

Data collection

Generic

Database

View

GUI

Plug-ins

dryad application structure
Dryad Application Structure

Inputfiles

Channels

Stage

Outputfiles

sort

grep

awk

sed

perl

sort

grep

awk

sed

grep

sort

Vertices

dryad system architecture
Dryad System Architecture

data plane

job schedule

V

V

V

Serv

Serv

Serv

control plane

Job manager

cluster

slide9

Text

Binary

XML

Perfmon

Data

Text

Binary

XML

Perfmon

Text

Binary

XML

Perfmon

10GB-1TB

Copy

DryadLINQ

application

Persisted data

Parse

Filter

Aggregate

100MB-1GB

complex statistics hilighter plug in
Complex statistics: HiLighter plug-in

Key Performance Indicator

Binary search overlogistic regression with

L1 regularization

Correlated metrics

Metrics

interactive analysis
Interactive Analysis

KPI Selection

Feature Computation

Visualization

Hilighter

conclusions
Conclusions

Automatic diagnosis

Goal

Statistical analyses

Feature extraction

Artemistoday

Summarization

Raw data

Distributed system