Performance management for SOA applications - Randy Stafford Performance of SOA applications is a serious concern for their owners and architects, especially as usage and complexity increase over the life of an application. The fact is that attending to quality attributes like performance, scalability, and availability will always be part of architecting systems, even as technology platforms evolve and new development models emerge over the years. This presentation will review the fundamental aspects of a pragmatic performance management approach for operational SOA applications, borne of first-hand experience in responsible positions. And it will drill into specialties such as performance analysis including understanding resource utilization and response time breakdown, and performance optimization using offline request stream replay and patterns specific to applications of different types and architectural styles. Attendees will gain a working knowledge of concepts, vocabulary, and measures from the world of performance management, in categories such as load, performance, and resource utilization. They will see examples of the kinds of charts and other artifacts that are useful in performance analysis activities, and learn of simple techniques and tools they can use to initiate a performance management program for their own systems. Attendees need not meet any special prerequisites, but an appreciation of evidence-based decision-making would be helpful. Ultimately, the more we are able to describe and manage the performance of our applications using common measures, the more mature we will be as a profession.

4. Typical Path for Heap Problems Seen in Traditional J2EE Apps and Integration Apps Java VM unresponsive Hypothesis: GC-bound Monitor heap, GC activity Recommend tuning, redesign Note this is not the only possible cause! Param chg Too small PermGen OutOfMemError Redesign GC-bound Unresponsive Heap over-consumption CPU-bound Blocked on IFs Deadlock Possible Cause Redesign OutOfMemError Upgrade? Unresponsive Redesign Unresponsive Redesign Unresponsive Likely Fix Symptom Unexpected termination StackOverflowError Frequent major GC OutOfMemoryError Manifestation Infinite recursion Infinite recursion Heap over-consumption Heap over-consumption Problem

5. Analyzing Heap Issues Look from VM Perspective, not OS Perspective 13900.575: [Full GC 1854335K->1687971K(1975744K), 10.5195922 secs] 13911.456: [Full GC 1854335K->1696808K(1975744K), 8.1486279 secs] 13920.094: [Full GC 1854335K->1690473K(1975744K), 8.2035046 secs] 13928.622: [Full GC 1854335K->1697287K(1975744K), 8.1587776 secs] 13937.049: [Full GC 1854335K->1688773K(1975744K), 10.4990567 secs] 13948.293: [Full GC 1854335K->1699080K(1975744K), 8.2193787 secs] 13956.974: [Full GC 1854335K->1692996K(1975744K), 8.2299517 secs] 13965.561: [Full GC 1854335K->1700780K(1975744K), 8.2348413 secs] 13973.968: [Full GC

6. Analyzing Heap Issues First Level of Tooling: jstat -t -gc <pid> 60s Timestamp S0C S1C S0U S1U EC EU OC OU PC PU YGC YGCT FGC FGCT GCT 71126.4 1280.0 1408.0 584.1 0.0 171648.0 113746.6 932096.0 422943.4 109568.0 109239.4 2538 54.318 1165 1165.298 1219.616 71186.4 1408.0 1600.0 1336.1 0.0 171520.0 165054.3 932096.0 423536.4 109568.0 109245.6 2560 54.988 1166 1167.631 1222.619 71246.4 1728.0 1856.0 544.0 0.0 170816.0 117204.8 932096.0 423600.7 109568.0 109261.4 2584 55.720 1167 1169.948 1225.668 71306.4 1600.0 1600.0 0.0 1048.6 171136.0 145917.6 932096.0 418206.3 109568.0 109160.3 2599 56.182 1168 1172.607 1228.789 71366.5 1600.0 1536.0 0.0 1000.1 171456.0 63392.6 932096.0 422258.1 109568.0 109175.3 2617 56.744 1169 1174.944 1231.688 71426.4 1600.0 1536.0 0.0 1529.7 171584.0 45124.1 932096.0 422541.6 109568.0 109354.1 2619 56.811 1170 1177.296 1234.108 71486.5 1600.0 2112.0 0.0 0.0 170496.0 32226.8 932096.0 378758.2 109824.0 109359.3 2620 56.846 1171 1179.798 1236.643

9. JADE Heap Analysis

10. JADE Heap Comparison

12. BPEL Console Statistics Page

13. ESB Control Instances View Statistics

14. OWSM Monitor See Chapter 6 of OWSM Administrator’s Guide

15. EM Transaction Tracing

19. Example Response Time Analysis Correlated with Load – Endpoint Overloaded?

22. Example Response Time Analysis Endpoint Response Time Distribution

26. BPEL Application Architecture NAÏVE! BPEL Host BPEL Server Must be product defect!

28. BPEL Application Architecture Pattern: Tier per Pipeline Stage BPEL Host BPEL Server BPEL Host BPEL Server BPEL Host BPEL Server BPEL Host BPEL Server BPEL Host BPEL Server

34. <Insert Picture Here> Summary, Q&A

36. Summary Prospects for Standarization Collect, store, and chart standard measures Yes Montoring At a high level, it’s a development lifecycle activity, with best practices Maybe Engineering Can have a standard APM program of monitoring, analysis, optimization Yes Management Patterns and playbooks apply here, but there is context-sensitivity & art Probably not Optimization Maybe Standardizable? Use the scientific method. It’s often a matter of understanding the response time breakdown or the throughput bottleneck. Analysis Remarks Activity

37. A Q & Q U E S T I O N S A N S W E R S

38. For More Information search.oracle.com +&quot;application performance management&quot; +&quot;service-oriented architecture&quot;