1. Lect2..ppt - 08/11/04 CIS 4100 Systems Performance and Evaluation Lecture 1 by Zornitza Genova Prodanoff

2. ZGP002 Lecture Outline: The Web as an evolving system Web site performance Client/Server performance Capacity planning Corporate Portal/ISP performance

3. ZGP003 Introduction: How is performance evaluation used? How good is current system? Why is my system so slow? What would happen if some component would be changed to a twice as fast component? How long will current system be ”fast enough”? How many transactions (per second) can current system handle? Do we need complete system upgrade, or just larger message buffers?

4. ZGP004 Introduction: Goals of Performance Evaluation What is the overall process of systems performance evaluation? How are performance evaluation models developed, solved, and used? How are parameter values determined? What specific analytical solution methods are there and how do they work? What are the limits of analytical solution methods, I.e., when is simulation needed?

5. ZGP005 Introduction: Course Contents Introduction −Probability Theory −Statistics Performance and Capacity Planning −Methods for Capacity Planning −Models for Performance Evaluation −Solutions to Simple Models −Practical Examples

6. ZGP006 Introduction: Why Do Capacity Planning? To avoid financial losses To ensure customer satisfaction To preserve company’s external image Capacity problems are solved slowly and related expenses could be substantial

7. ZGP02 server modem PC Transmission Medium Introduction: What is Internet communication? 010001001011… information

8. ZGP02 Introduction: Internet communication (Continued) Twisted pair cable Coaxial cable Fiber optic cable

9. … is the largest computer network What are computers? PCs, mainframes, pocket PCs, mobile phones, microwave ovens, toasters, produced by: Intel, AIX, SPARC, … SW: Windows, UNIX, Linux, Mac OS X, … ZGP02 Introduction: The Internet

10. ZGP02 Introduction: The Internet: exp. (2 n ) growth y axis : computers in millions 80M 2000 1982 Source: D. E. Comer, “Computer Networks and Internets”, 3 rd edition, Purdue University

11. ZGP02 Introduction: The Internet (Continued) the illusion of a single network, but a network of networks depicted as a cloud for clarity Internet

12. ZGP02 Introduction: Internet addressing 10000001 0011010000000011 Octet (8 bit) 1295263 00000110 IP addresses: an ID unique for each computer 129.52.6.3

13. ZGP02 Introduction: Internet addressing (Continued) IP Addresses are written using dotted decimal notation: 4 groups of 8 bits Each group can be 0 – 255 Example: Source: D. E. Comer, “Computer Networks and Internets”, 3 rd edition, Purdue University

14. ZGP02 Introduction: Packets packets can get lost, duplicated, delayed, and corrupted Packets (server to client) Client Server Ethernet (cable, link) Source and Destination address

15. ZGP02 Introduction: Packets (Continued) Source and Destination IP address Header Data 10000000 0000101000011110 Octet (8 bit) …

16. ZGP02 Introduction: Packets (Continued) ~22ms (=0.02sec) Electromagnetic signal speed ~ 300, 000km/sec Network links have capacity (data rate) – dial-in link: 56-Kbps – Ethernet: 10 or 100 (or 1000) Mbps – “T1”: 1.544 Mbps

17. ZGP02 Introduction: Routing A router connects two or more physical networks A router is part of each network (has 2+ IP addresses) Forwarding packets to the right destination Glue smaller networks together Data travel packet by packet

18. ZGP02 Introduction: IP Routing Source: D. E. Comer, “Computer Networks and Internets”, 3 rd edition, Purdue University Host IP address 129.52.6.3 Destination IP address 129.52.6.3

19. Introduction: Routing on the WWW ZGP02 Client Origin Server CacheClient Request Distributed Server URL: http://www.somesite.com Internet

20. ZGP0020 The Web as an Evolving System Interconnect (Web) pages into a web of (Web) sites by using hyper links –Static content –Dynamic content Applications: –Digital libraries –Video-on-demand –Distance Learning –E-commerce

21. ZGP0021 Web site administrators need to find the balance between: –IT infrastructure size –Quality of Service (QoS) user requirements Web browser Human user –Budget and other business considerations Realize this goal by: –Tracking intensity of workload –Detecting bottlenecks –Predicting traffic burstiness and peak demands The Web as an Evolving System (continued)

22. ZGP0022 The Web evolved from a publishing medium to a system that supports transaction processing –Dynamic content –Personalized content –Integration with Databases –Planning, scheduling, tracking systems Web services categories: –Informational –Interactive –Transactional –Workflow –Collaborative environments –On-line communities –Web portals The Web as an Evolving System (continued)

23. ZGP0023 Virtual Car Dealer –Store car make and model, etc. information in a RDBMS –Allow execution of remote queries Types of requests –Requests for documents and images (static pages) –Database searches (dynamic pages) –Response time –Requests’ Arrival rate –Increase/Decrease in arrival rate Web Site Performance

24. ZGP0024 Management needs to answer these capacity planning questions: –Will the Web site support load increase, while keeping response time acceptable (below threshold)? –At which point could the capacity be saturated and why? –What is the (daily) opportunity cost of saturating the Web site, while demand increases (request arrival rate increases)? Web Site Performance (continued)

25. ZGP0025 Web Site Performance (continued)

26. ZGP0026 What servers should be used? –Number and type of processors –Number and type of discs capacity plus RAID or other striping technology –Operating Systems Should a transaction processing monitor be used? What database server and RDBMS should be used? What LAN and WAN networking technology should be used? How much LAN / WAN bandwidth? Client/Server Performance

27. ZGP0027 Client/Server Performance (continued)

28. ZGP0028 Client/Server Performance (continued)

29. ZGP0029 Client/Server Performance (continued) % of the response time attributed to each major system component > 50% of the response time is dominated by the database server bottleneck is the component where a transaction spends most of its time If car rentals increase by 5, 10, and then 15% with respect to the current level, will the system support the corresponding increase in the number of transactions, while maintaining the response time within the desired levels?

30. ZGP0030 Capacity Planning is: The process of predicting when future load levels would saturate the system Determine the most cost effective way of delaying system saturation Must consider evolution of the workload and the desired service levels Client/Server Performance (continued)

31. ZGP0031 Performance Evaluation Goals: What is the overall process of systems performance evaluation? How are performance evaluation models developed, solved, and used? How are parameter values determined? What specific analytical solution methods are there and how do they work? What are the limits of analytical solution methods, i.e., when is simulation needed? Client/Server Performance (continued)

32. ZGP0032 Client/Server Performance (continued) By using performance evaluation and capacity planning we can predict response time of: local reservations road assistance requests car pickup phone reservations.

33. ZGP0033 Client/Server Performance (continued)

34. ZGP0034 Client/Server Performance (continued) Table 1.3 shows response times of: current load load increase of 5% of the current load load increase of 10% of the current load load increase of 15% of the current load. Load is the average transaction arrival rate

35. ZGP0035 Examples

36. ZGP0036 Examples (continued) Fig. 1.2 shows that the increase in response time is not linear with the load increase −e.g. 15% increase in the arrival rate of phone reservations generates a 5x increase in response time −Local reservations will exceed their max. acceptable response time of (2 sec.) at around a 7% increase in the current load; −Phone reservations will be able to support a 10% increase in the current load before the 2-sec. response time service level is violated; −Car pickup transactions will not get near their 3-sec. threshold, even if the load increases by 15%; −Road assistance transactions will exhibit a response time slightly higher (about 7% higher) than its 3-sec. threshold at arrival rate of 15%.

37. ZGP0037 We say that if any of the service levels has been violated, as in the case of the reservation transactions at a 15% higher load, the capacity of the system reaches saturation. The term saturation should not be used to indicate that the utilization of a device (e.g., CPU, disk) reaches 100%, because service levels can be violated well before the utilization of any device reaches 100%. Examples (continued)

38. ZGP0038 Capacity Planning will include both: predicting if performance requirements will be met by either a new system or an existing system under a higher load situation determine why performance will not be met Examples (continued)

39. ZGP0039 Example (Fig. 1.2): local reservation transactions spend 83% of their time doing Input/Output (I/O) at the database (DB) server located at the reservation center Improve the DB server performance by: spreading the same I/O load among more disks, using faster disks, increasing the cache size at either the storage box increasing the cache size or at the DB server. Examples (continued)

40. ZGP0040 Examples (continued)

41. ZGP0041 Figure 1.3 shows that when the arrival rate of requests doubles from the current value of about 0.3 tps to 0.6 tps, the response time approaches 50 seconds − > 3x increase from the 16-sec. response time at the current load At 0.6 tps, a saturation on the response time value is observed (the number of requests in the system reaches its max. value). − Connections start to be refused, showing a very poor performance of the help desk application. Examples (continued)

42. ZGP0042 Solutions to the performance problem at the help desk site: −upgrading the server's CPU, −adding more CPUs, −more disks, −splitting the load among more servers. Examples (continued)

43. ZGP0043 An ISP has 100,000 users. Average of 2 12 minutes sessions per day, per customer Customers who do not find an available modem to connect get a busy signal Volume-based-customers have 2 hours of free time per month, after which they pay by the minute of connected time Move to the following rate structure: customers will pay a flat fee independent of the amount of time they spend connected to the service Expected is a significant boost in the number of users Expected is that users to spend more time using the service since they will not be charged by connection time Examples (continued)

44. ZGP0044 The management of the ISP wants to know how many modems it should have in order to guarantee that the probability of a customer finding all modems busy is less than 5%. The ISP currently has 1,500 modems. Using models to be discussed in later chapters of this book, the performance analyst was able to show what would happen with the probability that a user gets a busy signal as the number of users varies. Examples (continued)

45. ZGP0045 Figure 1.4 shows this probability for two values of the session duration: 12 minutes and 18 minutes. As the graph shows, if the number of users doubles, the busy probability increases to 55% for 12-minute sessions and to 70% for 18-minute sessions QoS complains are expected if number of users doubles −closing accounts −suing the ISP Figure 1.5 shows how the busy probability varies as a function of the number of modems. It shows that if the ISP wants to keep a 5% busy probability, it needs 2,400 modems when sessions last 18 minutes on average. Examples (continued)

46. ZGP0046 Examples (continued)

47. ZGP0047 Figure 1.5 shows how the busy probability varies as a function of the number of modems If the ISP wants to keep a 5% busy probability, it needs 2,400 modems when sessions last 18 minutes on average Examples (continued)

48. ZGP0048 Examples (continued)

49. ZGP0049 Web site with numerous functions is of no use if it takes forever to connect or get useful information from it Performance problems can bring all sorts of undesired consequences: −financial and sales losses −decreased productivity −a bad reputation for a company Examples (continued)

50. ZGP0050 We consider the capacity of networked systems Capacity planning involves prediction Performance prediction is accomplished through the performance models presented in later chapters Capacity planning is also important when predicting the performance of a new application under development or when predicting the performance of applications that are being downsized to C/S environments An increasing number of organizations are moving mission- critical applications into C/S systems Examples (continued)