Webapplications performance testing

1
Web-applications performance testing

• Ilkka Myllylä
• Reaaliprosessi Ltd

2
Agenda

• Research results about web-application
  scalability
• Performance requirements specification
• Load testing tools
• Load test preparation
• Load test execution
• Analysis
• What is bottleneck and how to find it ?
• Optimization and tuning
• What is root cause and how to fix it ?

3
Research results about web-application
scalability
4
Is scalability problem ?

• Research results (Newport Group Inc.)
• Scalability in production
• as required 48
• worse than requirements 52 (average 30)
• Late from timetable and costs overrun
• as required 1 month and 70 000 euros
• worse 2 months and 140 000 euros
• What explains bad results ?
• performance testing timing is most important
  factor

5
Performance testing timing
6
Early start of testing is profitable

• Efficiency
• one and 2-5 user tests show average 80 of
  bottlenecks
• Costs
• late fixing costs many times more -gt wrong
  architecture risk for example

7
When to test performance ?

• Architecture validation
• Component performance
• New application system performance test
• Major changes to application made

8
Realistic performance testing is not easy

• Too optimistic results are common problem
• It worked in tests ! says 32 (Gartner Group)
  
• Bad environment
• Testing environment not equal to production
• Bad design implementation
• Load testing tool not used right way
• Wrong tool for a job
• Load test tool used not functional / does not
  include features needed

9
Performance requirementsspecification
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Performance requirements testability

• Requirements should be exact enough in order know
  how to test them
• Usage information
• Different users and their profiles ?
• Transaction amounts ?
• Response times
• Detailed response times requirements ?
• Technical constraints
• User terminals, software, connection speed ?
• Technical architecture
• Database size
• Security and reliability constraints

11
Completeness of requirements

• Sensibility check Are customers requirements /
  calculations right and sensible ?
• Completeness What information is missing ?
• Checklist

12
System usage information

• Goal Real usage simulation that is close enough
  to reality
• Business / use case scenarios are good starting
  point
• Close enough ?
• Not all functions are tested but most important
  and most used are tested
• 3-5 scenarios is usually enough for one
  application
• Usage information History info available ?
• Yes Future scenarios ?
• No Estimation and calculation with known facts

13
Transaction profile
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User profiles
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Does customers requirements / calculations make
sense ?

• Expectations can be too high
• Response time for all functions should be below
  2 sec
• In old system everything was very fast
• Different functions are not equal
• requirements should be set individually for
  important use cases
• and their functions
• Costs should be involved
• less response time, more costs
• technically chalenging requirements ?

16
How long user is willing to wait ?

• Not simple thing
• different users have different requirements for
  same functions
• Research results (Netforecast Inc)
• two important factors frequency and amount
• strong variation between applications and
  functions
• satisfactory average 10 s

17
Frequency of use

• Frequency How often user needs to use function
  ?
• more often user needs, less he/she is willing to
  wait
• Example 1 Frequency
• Use case Search customer info
• A. Once a hour requirement for response time 5
  s
• B. Once a month requirement for response time
  30 s

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Amount of information

• Amount How much valuable information we get as
  result ?
• more information one get, more he/she is willing
  to wait
• Example 2 Amount
• A. Saving function for few input fields
  requirement for response time 3 s
• B. Search function for product information (100
  fields) requirement for response time 10 s

19
Response time requirements
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Performance requirements in contracts

• Requirements for performance testing
• Appendix about performance requirements
• Test engineer validate testability
• Both customer and supplier benefit
• Good for customer
• No extra costs late in development cycle
• Good form supplier
• No new surprise requirements late in
  development cycle
• What about performance testing tools ?
• expensive investment

21
Load testing tools
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Types of performance testing

• Concurrency
• one to several users concurrently in risk
  scenarios
• manual testing normally
• Performance
• requirements for scalability ?
• load testing tool needed
• Load
• max number of users ?
• Reliability
• long usage possible without degrading performance
  ?

23
Load testing tools - markets

• Mercury Interactive market leader (gt 50)
• Big six have 90 of markets
• 100s of small companies
• Prices for major tools quite high
• Growing market

24
Load testing tools options to get one

• Buy licence ( consulting)
• usually virtual user count pricing
• Buy service
• load generation externally
• Rent licence ( consulting)
• need for only limited time and maybe for just
  this one project

25
Load testing tools main functions

• Recording and editing scripts
• Scenario design and running
• Analysis and reporting

26
Load testing tools - features

• Lots of obligatory features
• script recording
• parametrizing
• scenario design
• ramp up and weighting
• different scripts running concurrently
• online results / feedback
• error detection
• transaction level response times
• http protocol support

27
Load testing tools - features

• Lots of usually needed features
• Distributed clients
• Unix/Linux clients
• Multi protocol support
• Multi speed support
• Multi browser support
• Server monitoring
• Content validation
• Dynamic urls supported

28
Features - Make or buy

• Some features are possible to be done manually
• server monitoring
• analysis and reporting
• Usability
• best tools are really easy to use
• others need lots of work and programming
  experience
• Workarounds
• more features than promised with clever trics

29
Good tool combination

• Separate load and monitoring tool
• even from different vendor ?
• how about profiling ?
• Script reusability
• same scripts for functional and load testing

30
Load test preparation
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Testing environment

• Same as production environment
• Other applications dividing same resources
  (firewall etc) ?
• Controllable
• No outside disturbance

32
Basic optimization made

• What is basic optimization ?
• Server parameters are validated by responsible
  persons and list of values given to load testers
• Database sql performance checked and necessary
  indexes exists
• Without basic optimization load test is waste of
  time
• just first obvious bottleneck is found and no
  real information exists

33
Load test cases

• First each script separately with ramp-up usage
• easier to see what is problem straight away
• Real usage scenario with weighted scripts
• usually many test runs before goals are achieved
• time for repeated tests
• usual usage first then special occasions
• What-if scenarios
• one change at time to see influence of changing
  factor
• Risk based testing
• different location and speed testing
• hacker testing -gt Dos attack etc

34
Script selection

• User or process scripts ?
• both are possible
• Example Petshop application user oriented
• Create order - returning customer
• Create order - new customer
• Searching customer
• Example Petshop application process oriented
• Registeration
• Create order
• Search order

35
Script recording and editing

• Script Program code (C, Perl etc) to execute
  test automatically
• Basic recording
• execute test case with recording on
• check and set recording options before start
• generates script
• Editing
• parametrizing
• transactions
• think time changes
• checkpoints
• comments

36
Parametrizing

• Recorded script includes hard coded input values
• If we execute load test with hard coded values
  results are not realiastic (too good or bad)
• Parametrizing Different input values for
  different virtual users
• all users of system have different user
  information
• more realistic load

37
Test data generation

• Parameter data with right distribution
• Generation of test data to text files which load
  tools can use
• Real amount of data in databases
• Backup and restore procedures

38
Transaction

• Detailed response time information inside script
• Exact execution times and problem transactions
  could be seen
• script with 10 transactions -gt when response time
  increase, are all the tranasactions equally slow
  or just some ?

39
Checkpoint

• Functions in script that check correctness of
  results during execution
• In some tools could be set automatically
• Others need manual implementation
• Find errors otherwise not seen

40
Think time

• Think time Time user uses for looking and input
  before making next request to server
• Important parameter when estimating usage
• Less think time means more frequent request and
  more load to servers
• Example
• 100 users logged to system with 10 s average
  think time 1 user 6 transactions/ minute and
  100 users 600 t/min 10 tps
• If think time is 30 s load is 3 tps

41
Comments

• Making and testing scripts software development
• comments for meintenance
• tools own naming is not always good -gt changes
  needed to get readability

42
Script testing

• Executing single script succesfully
• at least twice
• with checkpoints and parameters

43
Scenario creation and testing

• Usage information and ramp-up of different
  scripts in same scenario
• Designed counters available and working for
  testing
• Test run with couple of users

44
Ramp-up

• Ramp-up
• User amount increase little by little
• In real life usually amounts does not change
  immediately
• When user amount increase little by little, it is
  easy to see how response time and utilization
  develop
• Stabilizing before next level of load
• Example 1000 users use system at same time
• first 50 users then 50 more every 10 minutes
  until response time is bad or errors start to
  increase

45
Collection of performance counters

• Responsiblity of getting performance counters is
  usually divided between
• administrators
• developers
• testers -gt Load Tool monitors
• Load tool monitors should tested
• not always so easy to get information from
  servers as vendor says

46
Load test execution
47
Reset and warm-up

• Reset situation
• Old tests should not influence
• Warm-up
• Before actual test, some usage need to done

48
Synchronizing people involved

• Test manager gets ready from all people involved
• When test ends syncronization again to stop
  monitors
• Collection of results

49
Active online following

• Counters
• following online monitors
• response time and throughput
• client and server system counters (cpu, memory,
  disk)
• Error messages
• if lot of errors occured test should be stopped
• errors occur often before application run out of
  system resourches

50
Response time

• Most important counter for performance
• Response time time user needs to wait before
  able to continue
• Industry standard for response time 8 seconds
• With response time usage information is needed
  too
• simultaneous user amount and what most of they
  are doing
• Example
• 100 simultaneous sessions, 50 update and 50
  search
• Response time requirement 4 s to 95 of insert
  and update of bill insert. To other functions
  requirement is 8 s.

51
Throughput

• Another important counter for validating
  scalability
• Amount of transactions, events, bytes or hits per
  second
• usual counter tps (transaction per second)
• Requirements could be told as throughput value
• Bottleneck could be seen easily with saturation
  point of throughput

52
Throughput and response time
53
Performance knee
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What is bottleneck and how to find it ?
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What is bottleneck and why it is important ?

• Any resource (software, hardware, network) which
  limits speed of application
• under requirements
• from good to even better (changing requirements)
• Bootleneck is result
• reason should be analysed and fixed
• for example disk i/o is bootleneck and fix is to
  distribute log file and database files to
  different disks
• Chain is as strong as its weakest link
• application is as fast as worse bottleneck
  permits

56
How can we identify bottleneck ?

• Using application and measuring
• response time and throughput
• resourche usage measuring
• One user
• ralative slowness and resourche utilization (
  not yet bottleneck but possible to see that
  bigger amounts of users will couse one)
• Several users
• trends possible to see already (1 user 1s, 5
  users 3 s, 1000 users ? s)
• Required amount of users
• Actual max usage scenatio

57
Not so nice features of bottleneck

• Real bottleneck influence load of other resources
• everything influences everything
• when disk is bottleneck, processor looks like one
  too (but is not)
• when real bottleneck is fixed other problem will
  be solved too
• if we increase processor power, it does not help
• Real bottleneck create other problems but hide
  them too
• first bottleneck should be solved in order to see
  next real bottleneck

58
Amount and finding of bottlenecks

• One application has usually many bottlenecks
• many changes are needed in order to
• One test finds only one bottleneck
• many iterations are needed in order to fix all
  bottlenecks

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Most common bottlenecks in web-applications
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Server counters and profiling

• What counters and log/profile information do we
  need in order see bottleneck and root cause ?
• Two levels of counters
• system counters cpu utilization
• application software counters Oracle cache hit
  ratio
• Log/profile information
• detail level resource usage information

61
Collecting system counters

• Memory, CPU, network and disk counters could be
  collected
• with operating system dependent programs like
  Windows Performance monitor or Unixin sar,top etc
• with load testing programs like LoadRunner or
  QALoad
• Collecting with load testing programs is easier
  and information is in easy to analyze/report form
• Counters for all four are needed

62
Interpreting system counters

• Most important counters
• CPU queue length tells if it is too busy
• Disk queue length tells if it is too busy
• Network - queue length tells if it is too busy
• Memory hard page faults (disk) tells if it is
  too small
• However one counter is not enough
• to be sure more counters are needed
• to see root couse more counters are needed

63
Application counters

• Collecting with load testing programs is easy and
  information is in easy to analyze/report form
• However all counters are not available to load
  testing tools
• online monitors (Websphere, WebLogic) could be
  used to complement information
• Different products have different counters
• need for understanding that particular product

64
Profiling tools

• Collecting exact information in call level
• memory usage
• disk i/o usage
• response time
• Collecting information may influence quite much
  to results
• one solution is to make two test runs one
  without logging/profiling and other with them

65
Example 1 One clear bottleneck

• One of four system resources is busy
• easy to see bottleneck

66
Example 2 More than one system resources looks
bad

• However only one resource is real bottleneck
• others are side effects of real bottleneck

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Example 3 None of system resources looks bad

• Where is the bottleneck then ?
• usually some software application uses works
  inefficiently internally or interface queue to
  external systems does not work efficiently

68
What is root cause and how to fix it ?
69
How to see root cause ?

• Application level information is usually needed
  and always good to have
• Software code problems could be solved when we
  see which is slow function
• Some root causes are easy to see while others
  needs sophisticated monitoring and profiling

70
Software implementation

• Database server
• Bad sql from performance point of view (works but
  not efficiently)
• No or not good enough indexes used
• Application server
• Object references not freed -gt too much objects
  in heap
• Bad methods used from performance point of view
• Idea is to decrease load to hardware resouches

71
Efficiency

• Not efficient use of existing hardware resources
• Parametrizing and configuring help

72
Capacity

• Resource too slow for handling events fast enough
• More resourches or reconfiguring existing
  resourches
• Cpu from web-server to db server

73
Hard constraints and requirements

• Clients complicated business logic requirements
• too much bytes needed in user interface (slow
  network speed)
• too many different sources of information needed
  (syncronous)
• long transactions single function needs many
  chained updates
• Security requirements
• too much request to web server -gt encrypted
  network traffic
• Online data needed
• many big updates needed immediately

74
Bad design

• Application tiers
• distribution of tiers possible (EJB vs pure
  Servlet)
• Technology
• too much information in session object
• Infrastructure
• not compatible versions of different vendors from
  performance point of view
• needed functionality not available ( distibution
  not supported)

75
Tuning

• Tuning
• application
• server software
• operating system
• network
• Usually good choice
• fast to do
• risks to regression small
• Usually tuning is not enough
• changes are needed

76
Changing

• Application code
• Application software
• Hardware
• Network infrastructure

77
Tuning vs change

• Tuning is not so risky
• Change is not always possible
• In practise both are valid and equally considered
  

78
Example Tuning vs change

• Sales system has application server processor
  bottleneck
• Could be removed
• More processing power
• Less processing needed -gt application code change
• If application logic need to be changed a lot
• More processing power choosed
• If application logic need to be changed a little
• application code change choosed
• If both are fast, easy and costs are low
• both are choosed

79
Removing bottlenecks

• Idea Removing root cause of bottleneck one by
  one
• Rerun same test to see influence

80
Testing part of system

• Sometimes it is difficult to see bottleneck and
  root cause
• More information is needed in order to understand
  system better
• Testing just one suspect at time is usually
  possible but could need much effort
• Testing only one extent at time is ultimate way

81
Top down optimizing

• When there is plenty of time
• not very fast, but efective
• Idea Optimize one level at time
• -gt Level by level readyness
• No jumping between levels

Application code
Application software
Operating system
Hardware
82
Memorycache-pool-area usage

• Idea Data or service that application needs is
  already in memory as much as possible
• System level
• big enough memory -gt not much swapping needed
• proxy server caches content
• Application level
• big enough database connection pool -gt new
  objects not needed
• big enough database sort area -gt not much
  swapping needed

83
Connection and thread pools

• Creating many objects at startup
• new user gets object from pool
• when used object returns to pool

84
Synchronous and asynchronous traffic

• If possible actions could happen asyncronously (
  no need to wait that action is ready)
• Interfaces to other systems

85
Distributing load

• Between servers
• load balancing
• Inside server
• cpus
• disks
• Between networks
• segments

86
Cut down features

• Sometimes only possibility is to cut down
  features and requirements
• deadline too neat to make other optimizing
• costs or risks too big when doing anything else

87
Making recomendations for correcting actions

• Need usually interpretion of results from
  different persons
• however understanding and criticality is needed
• Results should be clear
• usual It is not our software but yours
  conversations could be avoided if nobody can
  question results and recomendations
• need to show where problem is not !

88
Example Internet portal

• Application Many background systems develop
  data to this portal
• Response time in USAssa 5 s, when connections
  are fast
• In Asia every connection takes 2 sec and moving
  elements between server and client is slow too
• Logic 12 frames inside each other
• Result Opening first page takes 2 s12 30 s
  54 sec
• Requirement 8 sec

89
Corrective actions and ideas

• Idea 1 Faster connection
• not possible -gt thousands of internet customers
• Idea 2 Content nearer to customer
• pictures partly to client workstations -gt
  security regulations prevent partly
• content to servers near customers (Content
  Delivery Network)
• helps some but not enough
• Idea 3 Packaging of data
• helps some but not enough
• Idea 4 Application logic change -gt less frames
• lot of costs
• requirements achieved

90
Error and lessons learned

• Internet users with slow connections and
  different geagraphical areas
• can be important user group
• Technical design failed to this group
• Perfotmance testing late in development cycle
• too late
• not simulated real usage good enough
• Pilot users saved much
• not widely used when problems we seen
• Solution was found (as usual)
• but fixing took much time and money