get the big picture! end-to-end monitoring of heterogeneous middleware and apps

© 2012 SL Corporation. All Rights Reserved.

© 2013 SL Corporation. All Rights Reserved.1

Get the Big Picture! End-to-End Monitoring of Heterogeneous Middleware and Apps

Tom Lubinski, CTO, SL Corporation

8/9 October, 2013



RTView – Get the Big Picture !

• What is end-to-end monitoring• Why should you care about it ?

• Traditional system management tools are not enough• Agent-based transaction monitoring tools not enough

• What RTView does differently to address this need• Customer Use Case



What is End-To-End Monitoring ?

• Most people think this is end-to-end monitoring:

A B C D E

A Linear Data Flow …

Where A, B, C are JSPs, Servlets, Topics, Queues, etc.




• Sometimes it can be more complex:

A B C D E

With Loops and Error Paths …but it’s still “one-dimensional”

G F

Error




• It’s even more complex than this

• Two more dimensions must be added to the picture …




• A second dimension to capture the nested levels systems are implemented in – component layering

Host LayerPhysical Servers, Network, Disk, OS

App Server CachingMessaging

Servlet JSP

EJB

Topic Queue

Route

Cache Service




WebLogicServer

CoherenceCache

Load-Balanced Servers backed by Distributed Cache

A third dimension that most people don’t even think of … process distribution



Why Should You Care ?

• These three dimensions create complexity – all going on at same time

• Taken together they generate huge volumes of monitoring data and complex relationships between the application and the underlying components.

• Add in a fourth dimension, time, and the challenge becomes even greater



Why Should You Care ?

• System Mgmt tools give you lots of data, but typically one component at time … only the 2nd dimension

• Transaction monitoring tools only 1st dimension.

• Both are essentially “after the fact” - like alerts … you can tell when a transaction or component has failed but it needs to be correlated with state of entire system



How RTView Addresses This Problem

• RTView collects data from all these dimensions and is aware of the relationships.

• If an app is dependent on a specific msg queue, RTView can map this to the JMS server that contains the queue, as well as the system that hosts the server and correlate the metrics

• RTView is aware of Server load-balancing and the distributed nature of Coherence caches



How RTView Addresses This Problem

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RTView Use Case

Application: On-Line Store

Large on-line store providing product search and ordering services for consumer software products

WebLogic for Application Server

Coherence for Database Caching

Multiple other technologies, including TIBCO EMS for communications services

VMWare Virtual Infrastructure



RTView Use Case

Application Team

Small Group (< 10) responsible for 100+ WebLogic Servers + 100 Coherence nodes replicated in DEV,

TEST, and PROD

Some peripheral monitoring, e.g. Splunk for log files, Omniture for web tracking, OEM for WLS and OC



RTView Use Case

Support Challenges

Difficult to have confidence that store is “OK”Only know when something goes wrong

When it does, difficult to determine the cause

Each subsystem implemented as a WL ClusterWebLogic = OEM only allows them to see one server at a

time, but the store works off of “clusters”

Coherence = complete black box



RTView Use Case

RTView Solution

Hi-Level Overview Diagram showing “health state” – provides confidence that all subsystems are OK

Present WebLogic information in “clusters” – makes it possible to see aggregate metrics and load

balancing for each app

Correlate Coherence metrics with WL to provide confidence that Coherence black box is OK



On-Line Store Overview Diagram

RTView used to create 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



The Emerging Standard Oracle Stack

VMware

Oracle Coherence/DatabasesMessaging Middleware

Fusion / TIBCO / MQ

Oracle WebLogic



Conclusion

• 3-Dimensional End-to-end monitoring required for the emerging standard Oracle application stack

• High-level overviews showing “health state” give confidence that all subsystems are OK

• Ability to present WebLogic information in “clusters” makes it possible to see aggregate metrics and load balancing for each app

• Ability to correlate Coherence metrics with WebLogic helps to ensure that Coherence black box is OK

• Include Virtual Infrastructure State and Components from Other Vendors



Thank you!For more information, please visit

www.sl.com

http://www.sl.com/

get the big picture! end-to-end monitoring of heterogeneous middleware and apps

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