In this presentation, Everett Williams, SL’s Oracle Coherence Expert, discusses problems with analyzing host metrics and Oracle Coherence metrics within a cluster using the current tool sets. He also discusses how to integrate statistics to solve problems that relate between the two in an integrated and intelligent manner. Users of SL’s Oracle Coherence Monitor can address these issues and understand if their Coherence issues are related to issues within the underlying hardware, or whether they reside somewhere else.

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
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2. 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.
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3. Agenda
•
•
•
•
•
•
•
Customer quotes/Problem Statement
Data Collected
Current Tools/Analysis capabilities
Architecture
Demo
Expanding to App Servers
Challenges
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4. 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.
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5. Assumptions
•
•
•
•
•
100-500 JVMS
10-50 of Hosts
100s of caches
Analysis over time
Overlapping Data set (more than outlier analysis)
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6. 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.
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7. What makes Coherence “unique”
• Single task spread across multiple processes and servers.
• Impact of Network and latency
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8. Server view of data
•
•
•
•
Single Server
Single state
No Context
Doesn’t scale visually
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9. Top
• Single Server
• Single state
• No Context
Doesn’t scale visually
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10. Top/NMon
• Single Server
• Single state
• No Context
Doesn’t scale visually
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11. Taskmon Graphs
• Single Server
• No Context
• Time Series not aligned
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12. Stacked Graphs
• Doesn’t visually scale
• Top N Servers don’t re-sort
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13. Single Graph with Multiple Trends
•
•
•
•
Good for Outlier analysis
Not good for overlapping trends.
Single Server
No Context
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14. RTView Enterprise Solution
Collect, Analyze, Correlate, and Visualize data from multiple disparate sources
RTView
Enterprise System
RTView
Developer
Oracle
Coherence
Oracle
Database
Generic
JVM
TIBCO
…
Oracle
WebLogic
System
Metrics
VMware
Custom
Package
IBM
…
OEM
Connector
OEM
… and many more
Target Systems
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15. RTView Enterprise Solution
Users
.
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.
EM Central Server(s)
CMDB
Display
Server
ALERTDEFS
Configuration
Management
Alert
Aggregation
Directory
Cache Map
HISTORY
DataServers
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16. RTView DataServer – with H/A Deployment
Primary / Backup Servers run on different machines
DataServer
<primary>
DataServer
components obtain
configuration
information via EM
ConfigServer
Systems
Being
Monitored
DataServer Configuration
RTView EM
ConfigServer
DataServer
<backup>
Host
B
Host
A
Historian
<primary>
Historian
<backup>
…
H/A Database
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17. End-To-End Monitoring
• Capture the nested levels systems are implemented in –
heterogeneous component layering
Servlet
JSP
EJB
Topic
Queue
Cache
Service
Route
App Server
Messaging
Caching
Host Layer
Physical Servers, Network, Disk, OS
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18. DEMO
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19. Challenges
•
Consolidated snapshot of data
•
Visual scalability
•
Multiple combinations of trends
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20. Process/Node
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21. Network/Service
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22. Network/Service #2
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23. Host/Service
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24. Network/TCMP
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25. Network/TCMP #2
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26. Expanding to Application Servers
Correlation of WebLogic and Coherence
Monitoring Metrics
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27. On-Line Store Overview Diagram
System overview diagram
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28. WebLogic Cluster/Server Summary
All Servers Organized by Cluster, with Health State
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29. WebLogic Cluster App Summary
Each Cluster shown as a unit, with server metrics aggregated
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30. Load Balance Analysis
Load Balance Comparison of multiple metrics across WebLogic and Coherence
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31. Aggregating Other Middleware Information
Health State of each service aggregated from multiple components
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32. Aggregating Other Middleware Information
Health State of each service aggregated from multiple components
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33. Aggregating Other Middleware Information
Including Aggregate Service Alert History over Time
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34. Aggregating Other Middleware Information
Including Detailed History of Coherence Cache Service
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35. Thank you!
For more information, please visit
www.sl.com
+
www.sl.com/blog
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