real-time coherence monitoring in integrated environments

© 2012 SL Corporation. All Rights Reserved.

© 2013 SL Corporation. All Rights Reserved. 1

Real-Time Coherence Monitoring in Integrated Environments

Correlating Coherence Monitoring Metrics with Infrastructure, Database, and Application Server Metrics

5 December 2013 - London, UK

Everett Williams

Senior Director of Technology

SL Corporation

Tom Lubinski

Chief Technology Officer

SL Corporation



Disclaimer

The following is intended to outline our general product direction. It is

intended for information purposes only, and may not be incorporated

into any contract. It is not a commitment to deliver any material, code,

or functionality, and should not be relied upon in making purchasing

decisions. The development, release, and timing of any features or

functionality described for SL’s products remains at the sole discretion

of SL.



Agenda

• Customer quotes/Problem Statement

• Data Collected

• Current Tools/Analysis capabilities

• Architecture

• Demo

• Expanding to App Servers

• Challenges



Customer Questions/Comments

• Nodes, Caches, and Services are nice. But we are server people. –

Online Major Retailer

• How do I know if hardware/network are causing my coherence

problem – Major Apparel Company

• Does blade configuration #1 or blade configuration #2 run my

application better? – Major Retailer

• We spend a great deal of time “poking around” looking for system

metrics – Investment Bank.



Assumptions

• 100-500 JVMS

• 10-50 of Hosts

• 100s of caches

• Analysis over time

• Overlapping Data set (more than outlier analysis)



Data Collected and Aggregated

• Coherence Information

– Cache

– Service

– Node

– Storage Manager

• Host Information

– Host CPU/Memory

– Host Network

– Host Process CPU Memory

• Coherence information aggregated to the host level.



What makes Coherence “unique”

• Single task spread across multiple processes and servers.

• Impact of Network and latency



Server view of data

• Single Server

• Single state

• No Context

• Doesn’t scale visually



Top

• Single Server

• Single state

• No Context




Top/NMon

• Single Server

• Single state

• No Context




Taskmon Graphs

• Single Server

• No Context

• Time Series not aligned



Stacked Graphs

• Doesn’t visually scale

• Top N Servers don’t re-sort



Single Graph with Multiple Trends

• Good for Outlier analysis

• Not good for overlapping trends.

• Single Server

• No Context



RTView Enterprise Solution

Collect, Analyze, Correlate, and Visualize data from multiple disparate sources

RTView

Enterprise System RTView

Developer

Generic

JVM

VMware Oracle

WebLogic

Oracle

Coherence

… and many more

TIBCO

…

IBM

…

Oracle

Database

Custom

Package

OEM

Connector System

Metrics

OEM

Target Systems



DataServers

RTView Enterprise Solution

Users

EM Central Server(s)

.

CMDB

ALERTDEFS

Configuration

Management

Alert

Aggregation

Directory

Cache Map

Display

Server

HISTORY

EM Central Server(s) provide configuration to

dataservers and alert management to users.

It also provides a CacheMap identifying the

location of all data contained in DataServers.



DataServer Configuration

Primary / Backup Servers run on different machines

RTView DataServer – with H/A Deployment

DataServer

<primary>

DataServer

<backup>

Historian

<primary>

Historian

<backup>

RTView EM

ConfigServer

Host

A

Systems

Being

Monitored

…

DataServer

components obtain

configuration

information via EM

ConfigServer

Host

B

H/A Database



End-To-End Monitoring

• Capture the nested levels systems are implemented in –

heterogeneous component layering

Host Layer

Physical Servers, Network, Disk, OS

App Server Caching Messaging

Servlet JSP

EJB

Topic Queue

Route

Cache Service



DEMO



Challenges

• Consolidated snapshot of data

• Visual scalability

• Multiple combinations of trends



Process/Node



Network/Service



Network/Service #2



Host/Service



Network/TCMP



Network/TCMP #2



Expanding to Application Servers

Correlation of WebLogic and Coherence

Monitoring Metrics



On-Line Store Overview Diagram

System overview diagram



WebLogic Cluster/Server Summary

All Servers Organized by Cluster, with Health State



WebLogic Cluster App Summary

Each Cluster shown as a unit, with server metrics aggregated



Load Balance Analysis

Load Balance Comparison of multiple metrics across WebLogic and Coherence



Aggregating Other Middleware Information

Health State of each service aggregated from multiple components




Health State of each service aggregated from multiple components




Including Aggregate Service Alert History over Time




Including Detailed History of Coherence Cache Service



Thank you!

For more information, please visit

www.sl.com + www.sl.com/blog

http://www.sl.com/

real-time coherence monitoring in integrated environments

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