Transcript Siebel Remote Users

Performance Assessments of
Internet Systems
By
Kishore G. Kamath
SPAN Technologies
Testing solutions for the enterprise
www.spantechnologies.com
[email protected]
973-575-7235
 Copyright 2003 by SPAN Technologies.
Agenda
•
•
•
•
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Why do Internet systems under perform?
Performance analysis in the corporate world
How do automated tools work?
Simulating user load
Assessing computer systems
 Copyright 2003 by SPAN Technologies.
Performance Considerations for
Internet Applications
• Why do Internet applications under-perform?
– Application Design/Implementation
» In-efficient database queries
» Poorly written code
• Identification
Web Users
– Simulate light user-load
– Measure system metrics on Database / App Server
» CPU Utilization, Disk I/O and Processor Queue
Length
Database
Server
Web Server
App Server
 Copyright 2003 by SPAN Technologies.
Performance Considerations for
Internet Applications
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Performance Considerations for
Internet Applications
• Why do Internet applications underperform?
– Unbalanced System Topology
» Physical design and topology may be
in-efficient
» App Server components may not be
co-located on same box.
• Identification
Database
server
Web
Server 2
Load
balancer
– Simulate moderate user-load
– Measure system metrics on Database / App
Server
» CPU Utilization, Disk I/O and
Processor Queue Length
• Measure network metrics
– Characteristics
» High network load
» Moderate CPU Utilization
 Copyright 2003 by SPAN Technologies.
App
server
Performance Considerations for
Internet Applications
• Why do Internet applications under-perform?
– In-adequate Server/Network Capacity
» Server hardware under equipped to handle
software demands.
» Network pipe to the Internet is too small.
• Identification
– Simulate anticipated user-load
– Measure system metrics on Database / App Server
» CPU Utilization, Disk I/O and Processor Queue
Length
– Measure network metrics
– Characteristics
» High network load / High CPU Utilization, Disk I/O
or Processor Queue Length.
 Copyright 2003 by SPAN Technologies.
Performance Considerations for
Internet Applications
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Performance analysis in the corporate
world
• Create a Test Region a scale of production
• Simulate user activity using an automated performance tool
(Mercury Interactive LoadRunner, Compuware QALoad, Empirix
E-Load or Segue Silk Performer)
• Use automated tools to
– Record user activity
– Replay user activity x number of users to simulate.
• Examine system behavior under simulated load
– Review system metrics
– Do root-cause analysis.
 Copyright 2003 by SPAN Technologies.
How do automated tools work?
• How recording works
– Capture user activity at a protocol level
– Create a proxy server to capture HTTP requests from
a browser
– Capture HTTP request components including server
target requested and name value pairs.
– Store these HTTP requests into a script.
Record
Web
server
App
server
1
Private
HTTP Request Proxy
Script
name = “jane”
password = “courant”
 Copyright 2003 by SPAN Technologies.
Database
server
How do automated tools work?
• How replay and analysis work
– Make HTTP requests stored in script.
– Replace pivotal values in name-value pairs with other
values.
» Prevent caching from making results optimistic.
Replay
name = “jane”
password = “courant”
Web
server
Script
name = “john”
password =NYU”
name = “harry”
password = “edu”
App
server
HTTP Request
Script
Script
 Copyright 2003 by SPAN Technologies.
Database
server
How do automated tools work?
• How replay and analysis work
– Server cannot tell apart a script replay from a real-user
request.
– Multiple instances of script execution can simulate
multiple users.
» Instances can simulate increasing, decreasing,
steady-state or random user load.
– HTTP requests and server response and behavior
metrics can be monitored and collated.
– Correlations between requests and behavior can be
analyzed.
 Copyright 2003 by SPAN Technologies.
LoadRunner Installation: Review
6
Putting it all Together
Performance metrics
Web
servers
App
servers
Database
server
Load Simulator
Machine 2
LR
CONTROLLER
1.Control desk.
LOAD
GENERATOR 2
(NY)
2.Load Simulator
Machine 1
LOAD
GENERATOR 1
(SF)
3. Analysis Tool
LR
 Copyright 2003 by SPANANALYSIS
Technologies.
Performance analysis
• Light load
– Load is less than 10% of expected load.
– Review of transaction response times and
server/network metrics
» High response time coupled with high Disk I/O or
CPU Utilization is indicative of bad code/queries.
 Copyright 2003 by SPAN Technologies.
Performance analysis
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Performance analysis
• Steady state 100% load
– Review of server/network metrics
» Increasing trend indicates an issue
» Memory leaks can be determined
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Performance analysis
• Capacity Planning
– Increasing load past expected load levels
» Review of response times and server/network
metrics
• Response time under expected and future
load.
• Server/network utilization under expected
and future load
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Performance analysis
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
Comparative studies
• Run load under 2 different conditions
– Example
» With and without SSL.
» Two different server hardware configurations.
» Two different configuration settings
• Compare response times and metrics to study
impact of change
– Used for tuning, benchmarking.
 Copyright 2003 by SPAN Technologies.
Courtesy Mercury Interactive Corp
 Copyright 2003 by SPAN Technologies.
IP based load-balancing
• Load re-directors will send load from one IP address
to the same web server.
• Load simulation would need to use different IP
addresses to simulate multiple users
• Load simulator will spoof IP Addresses not in use
when making requests to the server.
– Max of 25-8192 IP addresses per Network card
depending upon OS.
• Load balancer uses IP address to direct load to
appropriate web-server based on hashing algorithm
• Server host alias file re-points IP addresses back to
the true load simulator IP address.
 Copyright 2003 by SPAN Technologies.
Summary
• Performance assessments of Internet systems
are achieved via simulation.
• Automated tools can create realistic load by
simulating HTTP requests while changing data.
• Correlation of system metrics with level of load
can identify performance issues and their root
cause.
 Copyright 2003 by SPAN Technologies.