Webinar soasta correlsense_retail_ready_slideshare
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Webinar slides from Correlsense and SOASTA presentation on retail web and mobile performance monitoring and testing.
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Webinar soasta correlsense_retail_ready_slideshare
- 1. New Approaches to Real-Time Application Testing and Performance Monitoring December 15, 2011
- 2. Agenda • Best practices for holiday performance testing • New testing and monitoring techniques • Demo • Q&A
- 3. The Online Market You are here!
- 4. Cyber Monday 2011 • $1.3B • 33% y/y growth in traffic • 10.8% is Mobile (3.9% last year)
- 5. iCommerce: Biggest Mobile Influence
- 6. The IT Landscape Has Changed What is “Peak Load”? • 100%, 200%...500%+? • How much mobile traffic should we prepare for…and how? What Are The Most Important Transactions? • What are the most profitable paths users follow? • What is the affect of non-buying “browsing” on paying customers? What System Do You Test In? • Is the lab good enough? • Production testing is taboo (isn’t it)? How Will You Find The Issues? • Complexity reigns • How do we see where issues are at load?
- 7. The IT Landscape Has Changed What is “Peak Load”? • You must to test to new limitswith a mix of web and mobile traffic What Are The Most Important Transactions? • Those that you determine as profitable, complex and/or risky What System Do You Test In? • Testing is a continuous process from the lab to live production How Will You Find The Issues? • Monitoring during tests for the the end-to-end view while tests run
- 9. Monitoring best practice 1 “Assume Nothing” Oops. A production server! UAT Environment topology autodetected
- 10. Monitoring best practice 2 Visibility explains REAL phenomenas Specific transaction type is failing Specific location is failing
- 11. Monitoring best practice 2 Visibility explains REAL phenomenas It is pretty easy to see the load balance mismatch You can see that the % Time spent between User and Data Center is the issue here When compared Or the %Time to % Time spent spent rendering within the Data on the user’s Center device
- 12. Monitoring best practice 3 Baseline and compare Compare application model of 100% load vs. 150% of load
- 13. Testing best practice 1 • Start early & test progressively. – Begin in development – Run many iterative tests that address performance from code though infrastructure – Finish in production (Live prod to really be sure)
- 14. Testing best practice 2 • Test realistically. – Model users acting like humans – Stress & measure at a realistic pace – Run at true scale – From different locations and devices
- 15. Testing best practice 3 • Seek a single source of performance truth. – Get Dev & Ops on the same page. (Is 2 seconds okay?) – Measure with the same tools in Dev, Test & Ops – Correlate monitoring data with test data as tests run
- 16. Thankfully, There is a Solution SharePath identifies critical transactions to test what matters most CloudTest enables testing to any level with web or mobile traffic – in lab or production environments Monitor critical metrics during and after tests to isolate and prevent production outages
- 17. Demo
- 18. Summary • The IT Landscape has changed • Start your testing early, test progressively, and test realistically • When monitoring critical applications, assume nothing, look for root cause phenomena, use baselines, and compare • SharePath and CloudTest provide an integrated solution
- 19. Questions Contact SOASTA: Contact Correlsense: www.soasta.com/cloudtest/ www.correlsense.com/demo info@soasta.com www.real-user-monitoring.com 866.344.8766 info@correlsense.com Follow us: Follow us: twitter.com/cloudtest twitter.com/correlsense facebook.com/cloudtest facebook.com/correlsense Get your free copy Download GET STARTED SharePath RUM! CloudTest Lite - FREE! TODAY! http://www.real-user-monitoring.com/ www.soasta.com/cloudtest/lite/
Notas do Editor
- Testing with a production server. Every day at the same time, production outage that was not explained. Turned out this was the time they ran the tests. Part of the team had to stop the test because they got called in to a Production war room, not knowing it was directly related.
- CPU is spiking. So what? Example about network monitoring complaining about high throughput. What does it affect? Is it burning the cable?Should be the other way around – look for phenomenas affecting users and drill to root cause
- CPU is spiking. So what? Example about network monitoring complaining about high throughput. What does it affect? Is it burning the cable?Should be the other way around – look for phenomenas affecting users and drill to root cause
- Give example of chatty application – transaction calling a webservice that has changed. For each call, now making 540 calls instead of 20. Response time stayed the same, but model has changed. This would have popped up in production. Must compare models.
- Dan