3 Keys to Performance Testing at the Speed of Agile
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The document outlines three key strategies for efficient performance testing within agile software development, emphasizing the integration of performance metrics into the planning phase, establishing appropriate feedback loops, and minimizing scripting waste. It discusses the importance of consistent performance evaluation at different stages, including API, databases, and user interfaces, to ensure a confidently shippable product. The need for continuous performance monitoring and testing is underscored to adapt to the rapid pace of modern software delivery.
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![Quick Poll: When do you measure system performance?
[multiple choice]
● Just before MAJOR releases
● Just before MINOR releases
● A few times, throughout sprints
● As part of a Continuous Delivery pipeline
● No schedule, project-based, as-needed](https://image.slidesharecdn.com/3keystoperformancetestingatthespeedofagile-190828123520/85/3-Keys-to-Performance-Testing-at-the-Speed-of-Agile-5-320.jpg)
![“We didn’t bother with scalability because they wanted an MVP ASAP…”
“The stakeholders didn’t say they want to integrate this with [that other service]...”
“We’ll deliver documentation...if there’s time at the end of the sprint.”
“Security is for a hardening stage...which as usual, got eaten up by bug fixing…”
“We’ve been doing stand-ups for weeks, and no one mentioned performance criteria!”
“That isn’t in the definition of done, so the customer shouldn’t expect it in the product.”
“That’s someone else’s area of expertise...I’ll assign the task to them next.”
Agile “faster theater” anti-patterns](https://image.slidesharecdn.com/3keystoperformancetestingatthespeedofagile-190828123520/85/3-Keys-to-Performance-Testing-at-the-Speed-of-Agile-9-320.jpg)
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- 3. 1. Agile Challenges and Anti-patterns 2. The Goal: Potentially Confidently Shippable Product 3. 3 Keys to Efficient Performance Testing in Sprints 4. Q&A Roundtable What We’ll Cover
- 4. Today’s Presenter Paul Bruce Sr. Performance Engineer, Neotys USA @paulsbruce @neotys linkedin.com/in/paulsbruce
- 5. Quick Poll: When do you measure system performance? [multiple choice] ● Just before MAJOR releases ● Just before MINOR releases ● A few times, throughout sprints ● As part of a Continuous Delivery pipeline ● No schedule, project-based, as-needed
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- 7. Consistency: across all digital properties (web, mobile, API…) Fast activity completion: checkout, subscribe, approve Abandonment: page or mobile app uninstalls Ubiquitous connectivity: WiFi, mobile, broadband… What kind of performance do customers expect?
- 8. “Faster” Isn’t Good Enough Anymore Value Customer Centricity Business Technology Accelerated Delivery Small, frequent changes Efficiency: skills, process, tools
- 9. “We didn’t bother with scalability because they wanted an MVP ASAP…” “The stakeholders didn’t say they want to integrate this with [that other service]...” “We’ll deliver documentation...if there’s time at the end of the sprint.” “Security is for a hardening stage...which as usual, got eaten up by bug fixing…” “We’ve been doing stand-ups for weeks, and no one mentioned performance criteria!” “That isn’t in the definition of done, so the customer shouldn’t expect it in the product.” “That’s someone else’s area of expertise...I’ll assign the task to them next.” Agile “faster theater” anti-patterns
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- 11. 1. What is ‘Progressive Testing’? 2. What needs to be performance tested (and when)? 3. The “right” performance test for the job 4. Example triggers and schedules The Goal: Confidently Shippable Product
- 12. Progressive Testing Across the Delivery Pipeline Feature X… API update Y… Patch N...For: Time budget for testing: seconds minutes hours Days Weeks
- 13. Each layer must be tested for performance:. API, database, web/mobile, networks, 3rd parties, cloud infrastructure, failover/recovery behaviors. What needs to be load tested? Data Stores Core microservices 3rd-party APIs Load Balancers Front-facing servers Network / Edges Short, fast performance feedback loop Longer burn / more complex performance testing API perf testing DB latency testing Windowed perf tests Web & mobile testing Spike/failover testing Distributed geo load
- 14. . The “right” performance test for the job Real-world dependencies Easy & fast Takes time
- 15. The “right” performance test for the job Development and Architecture ● Load (does it handle N users?) ○ Cloud migration baselines ○ Build-over-build performance trends ○ Meeting contractual SLA obligations ● Soak (are there leaks or degradations over time?) ○ Server RAM, CPU, disk ● Spike (how does it handle dramatic changes?) ○ Load balancing ○ Rate throttling ○ Garbage collection Operations and Change Management ● Stress (where is the max?) ○ Capacity planning ○ EUX degradation and ajax timeout handling ● Configuration (is this tweak better or detrimental?) ○ Routing, SSL termination, database tuning ○ Logging, retention policies ● Network (what latencies are in the pipes?) ○ 3rd-party API SLAs ○ Service distribution (architectural latency) ○ Multi-cloud deployments
- 16. Example: Triggers and schedules for performance testing Event Max CI duration DB API Web & mobile 3rdParty Infra Network Regression Code check- in 10-15 min Sm Sm Sm Merge 15-30 min Med Med Med Overnight 1-4hrs Med/Lg Med/Lg Med/Lg Sm Weekly Lg Lg Lg Sm Med Med Med Pre- release Lg Lg Lg Lg Lg Lg Lg Test Coverage (Sm / Med / Lg): ● Volume (VUs) ● Scope (# flows) ● Conditions (geo, wifi/LTE)Small Medium Large “Right fit” is the biggest challenge.
- 17. 1. Integrate performance into planning phase 2. Establish “right-sized” feedback loops 3. Reduce waste in scripting and analysis 3 Keys to Efficient Performance Testing
- 18. 2017 study: ● Release every other day; 2x user stories w/ performance criteria Key #1: Integrate performance into planning phase bit.ly/performance-feature How to “bake performance in” to user stories? ● “Back of card” / DoD - performance criteria ● “Think 4th dimensionally” → Time ● Concerns and guidelines, not testing performed ● Performance-specific: ○ Concurrency: “how many users at the same time?” ○ Conditions: “which devices from where?” ○ Capacity: “what resources will this take?”
- 19. Key #1: Integrate performance into planning phase techbeacon.com/how-build-performance-your-user-stories Todd DeCapua - @appperfeng
- 20. ● Small load test on new features ● Critical-path performance regression ● Baselines and comparisons accessible to everyone ● Including metrics that tell the complete story: ○ The “efficacy” of the test (load health and bias) ○ The “impact” side of the story (server monitoring) ○ The “customer” side of the story (end-user experience) Key #2: Establish Right-Sized Feedback Loops Value vs. time cost Risk Prevention Early Detection End-to-end visibility
- 21. Key #2: Establish Right-Sized Feedback Loops
- 22. Key #3: Reduce Waste in Scripting Time ● Record through a browser, low-code approaches ● Carry customizations during re-scripting / recording ● Build library of reusable test assets ● Reuse existing functional test assets (“Self-healing” load scripts) ● Share test assets across teams and engineers Easy & Intuitive Efficient Consistent Realistic Collaborative
- 23. Key #3: Reduce Waste in Scripting Time
- 24. 1. Integrate performance into planning phase 2. Establish “right-sized” feedback loops 3. Reduce waste in scripting and analysis 3 Keys to Efficient Performance Testing
- 25. 1. Agile Challenges and Anti-patterns 2. The Goal: Confidently Shippable Product 3. 3 Keys to Efficient Performance Testing in Sprints What We’ve Covered
- 26. Q&A Roundtable Paul Bruce Sr. Performance Engineer, Neotys USA @paulsbruce @neotys linkedin.com/in/paulsbruce