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PERFTEST FOR WEB BASED APPS
The document discusses cloud testing services from NetEase CloudTest. It notes that CloudTest was the first cloud testing company and has tested over 10,000 hours in the cloud. It provides real-time analytics, performance intelligence, and the ability to simulate hundreds to millions of users on demand from the cloud at an affordable cost and scale. CloudTest gives metrics from both outside and inside the firewall.
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- 8. Netflix Goes DownFor 11 Hours TurboTax Site Crashes, 300,000 miss Tax Deadline! The Web Collapses Under The Weight Of Jackson's Death Bank Of America Online Banking Site Crashes Schwab Website Crashes During Trading
- 9. Net Ease : Turnkey, Scalable Test Cloud On-Demand Cost: Using the Cloud to Test is Affordable Speed : Performance Intelligence in Real Time Scale: Simulate Hundreds up to Millions of Users
- 10. Net First CloudTesting Company (2007) First 1M User Web Test – Ever Performed Provisioned Over 300,000 Cloud Servers Tested Over 10,000 Hours in the Cloud AWARD Winning: Top 50 VC-backed Company (WSJ) Top Ten New Cloud Services (IW) Best Cloud Application (IT Mgmt) Visionary Leader MQ (Gartner)
- 11. Actionable Performance IntelligencePerformance Intelligence PEOPLE ENVIRONMENT CLOUDTEST APPLICATION Aggregation & Correlation (OLAP) REAL-TIME ANALYTICS ENGINE Test Editors Test Builder BUILDING TESTS App & System Monitors Load Generators PROVISIONING LAB
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- 15. CloudTest™ Provides Metricsfrom Outside the Firewall Monitoring data can come from SOASTA agents or enterprise monitoring solutions such as Wily Introscope Without internal monitoring you get real time analytics from the outside, but no server-side visibility Monitoring Provides Metrics from Inside the Firewall
Editor's Notes
- #2 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #3 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #4 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #5 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #6 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #7 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #8 Finger Pointing Complex interdependencies due to frameworks Too many sockets used Full heap due to memory leak Inefficient algorithms Inefficient or redundant calls File handle leaks Poor choice of object representation High serialization (data marshalling) cost (SOAP, XML) High latency and heavy payload for specific calls High CPU usage Too many SQL calls Full connection pool
- #10 Killer app, including functional
- #11 80 Users for Schlumberger