1. Pro-Active Performance Engineering
Vijay Amrit Raj Sharma
Sr. Manager, Software Development
Oracle, Identity Cloud Services (IDCS/OICS)
May 10, 2017
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2. Confidential – Oracle Internal/Restricted

3. Agenda
Introduction Scope Re-Active Performance Engineering Why Pro-Active Performance Engineering Pro-Active Performance Engineering – Measures Continuous Performance 1 2 3 4 5 6
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4. Introduction Performance Engineering
“Yeaah.. It’s important but will take it up soon”
One solution fit all – Does not work with performance problems.
Varied KPIs, Software Ecosystem etc
Performance in Cloud
Performance practices from ongoing product development at OICS/IDCS (Oracle Identity Cloud Services)
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5. Scope In Scope Not in scope Pro-Active Performance Engineering
Performance Monitoring
Performance Testing aka Load/Stress testing
Performance issue troubleshooting methodologies and tools
Performance based scalability
Capacity Planning
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6. Re-Active Performance Engineering
To ensure that software is meeting the performance objectives (KPIs)
Response Time, Throughput, Resource Utilization, Workload etc
Traditional approach to Performance Engineering
Dependent on load/stress testing and KPIs (Key Performance Indicator)
Helps in sizing and capacity planning to meet objectives
Covers network, hardware, third-party frameworks etc
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7. Why Pro-Active Performance Engineering
To keep focus on code optimizations (with tools, automation, reviews etc)
Performance issues in production result of
Initial design, patterns, framework, coding constructs
Reduced “Cost Of Ownership”
To align with agile development
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8. Who does Pro-Active Performance Engineering
New Term:
DevPerf
Development + Performance
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9. Pro-Active Performance Measures - Manual
Performance improvement at design time
Performance: Design Guidelines
Right choices of non functional artefacts makes big difference
Caching : Distributed Cache – Near Cache versus Far/Remote Cache
Algorithms
Coupling and Cohesion
Shared resources : Threads, connections, storage, I/O etc
Third party frameworks and libraries
Performance improvement during coding and code reviews
Performance: Coding Guidelines
Different caching frameworks have different strength. If requirement is only for local cache (and not distributed) then EHCache has superb read and write performance. But if distributed scalability is something you are targeting then Hazelcast provides superb in-memory data grid for dynamic scalability.
Reddis is very easy intergratable with AWS
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10. Pro-Active Performance Measures : Automation
Optimization via static code ruleset
Use of static code analyzer framework
PMD, FindBug, CheckStyle etc.
100s of rules available out of the box
Can add your own rules (based on the review comments)
Very Powerful and Fast Approach
Integrated with IDE and build scripts.
Analyzing code without executing it. Generally used to find bugs or ensure conformance to coding guidelines. The classic example is a compiler which finds lexical, syntactic and even some semantic mistakes
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11. Pro-Active Performance Measures : Automation (Cont.)
Examples* of Performance static code ruleset (PMD)
AvoidInstantiatingObjectsInLoops
New objects created within loops should be checked to see if they can be created outside them and reused.
public class Something {
public static void main( String as[] ) {
for (int i = 0; i < 10; i++) {
Foo f = new Foo(); // Avoid this whenever you can it's really expensive }
UseStringBufferForStringAppends
UseArrayListInsteadOfVector
UseArraysAsList
*Source
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12. Pro-Active Performance Measures - Code Profiling
Optimize code performance by observing code’s runtime behavior
Can be done on developers machines. No need of heavy standard infra.
Runtime ‘profiles’ :
Breakdown of the entire call flow execution
Hotpaths
Tools: jProfiler, JRAT, VisualVM (JDK7), JMC etc
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13. Pro-Active Performance Measures - Code Profiling (Continued)
The profile below is from OCIS/IDCS showing duplicate/extra DB Calls to fetch user information for user modify operation
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14. Pro-Active Performance Measures - Code Profiling (Continued)
Below is the screen shot showing code flow of 54% in CachedDataProvider
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15. Pro-Active Performance Measures
Continuous Performance
(CP)
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16. OIDC/IDCS Continuous Performance
What is Continuous Performance ?
Continuous check for performance degradation
Check code’s runtime behavior for its optimization
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17. Continuous Performance (CP)… (Continued)
How “Continuous Performance” is achieved ?
Microservice REST Endpoints based test invocations
Single thread execution (iterated over 600 times).
Server latency only (Response Time) based comparison with baseline
Automation using Gradle and Teamcity
Relative performance measurement : No sophisticated H/W or Infra
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18. Continuous Performance : Framework Architecture
Data Seeder
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19. Continuous Performance (CP).. Lifecycle/Process
Teamcity
Performance Test Suite Run
Developer runs the test locally
Developer adds performance test
Analyze issues reported in generated report
Performance Deviation Test Report ( ed to all dev)
Developer fixes the issues
Developer fixes Performance Bugs
JIRA Bugs For high deviation
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20. Continuous Performance : Test Report
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21. Continuous Performance : Conclusion
Not a replacement for load testing
Measures before code goes to QA/Performance Testing Team
Remarkable framework/tool developed almost first time in software development industry and no parallel tool or framework exists that provide or supports Continuous Performance in software product/application development
*Patent Under Progress
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