Measurement Based Performance Characterization of Software Servers

Transcription

1 Measurement Based Performance Characterization of Software Servers B. Nagaprabhanjan Under the guidance of Prof. Varsha Apte Kanwal Rekhi School of Information Technology Indian Institute of Technology, Bombay M.Tech Project, Second Stage Presentation Project Sponsored by Intel

2 Outline Motivation Goals of this project Previous Work Overview 1 Motivation Goals of this project Previous Work Overview 2 Existing Profilers The Lite Java Profiler with Lite Java profiler 3 4

3 Motivation Motivation Goals of this project Previous Work Overview Finding resource profiles is one of the important steps for performance modelling of a system.

4 Motivation (Contd..) Motivation Goals of this project Previous Work Overview Fine grained resource profiles help construct better queueing models. Manually profiling becomes quickly complex and tedious.

5 Primary Goals Motivation Goals of this project Previous Work Overview To get fine grained resource consumption profiling information to construct better analytical models. To completely automate the process of resource consumption profiling for distributed transactions. To integrate it with the dependency determination tool.

6 Work done in Phase-I Motivation Goals of this project Previous Work Overview Some of the load generators were surveyed. httperf, torture, opensta, loadrunner, Web Avalanche, WAPT. The existing resource consumption profiling tools and their feasibility for the current purpose were studied. Operating Sytem Level Tools ps, sar, top, netstat, iostat, vmstat etc. Some open source projects. LKRM, ELSA, CSA. Linux Trace Tool kit. Found that the above tools are not suitable for getting fine grained information.

7 Overview Motivation Goals of this project Previous Work Overview Two choices for profiling. Java based profilers Can get fine grained information such as per method execution times. The Lite Java Profiler which is suitable for automation and provides fine grained information. Operating system tools Useful for rapid prototyping and cross validation. The provides a basic framework to automate the resource consumption profiling process for distributed transactions.

8 Outline Existing Profilers The Lite Java Profiler with Lite Java profiler 1 Motivation Goals of this project Previous Work Overview 2 Existing Profilers The Lite Java Profiler with Lite Java profiler 3 4

9 Existing Profilers Existing Profilers The Lite Java Profiler with Lite Java profiler Extensible Java Profiler (EJP) and Yourkit Java Profiler (YJP). Supports partial profiling. Profiling can be started and stopped when required. Produce accurate timing information. Has filtering capability. Problems Has support for only execution times. JVM needs to be shutdown in order to process logs. Both are written for simple to moderate Java applications. Profiling overhead is substantial and hence affects measurements. Not suitable for automation due to inherent implementation constraints.

10 The Lite Java Profiler Existing Profilers The Lite Java Profiler with Lite Java profiler Developed as a part of this project. Features Incurs minimal runtime overhead. Remotely controllable. Provide dynamic filtering facility. Extensible so that it can monitor more resources. Upon JVM start, the profiler initializes itself, spawns a seperate thread and listens to specified port for the following commands. start, stop, addfilter <String>, removefilter <String>, enable_event <Event>, disable_event <Event>.

11 with Lite Java profiler Existing Profilers The Lite Java Profiler with Lite Java profiler Sample Methods helloworld() getstring() newsession() CPU Times ms 2.91 ms ms Table: Results of profiling a sample application Large container overhead involved in serving an application s request. Response time was 1209 ms and the service time was only 120 ms. This issue needs further exploration.

12 Outline 1 Motivation Goals of this project Previous Work Overview 2 Existing Profilers The Lite Java Profiler with Lite Java profiler 3 4

13 To co-ordinate the process of resource consumption profiling. Master: generates the load and sends appropriate commands to the slaves. Slave: Monitoring the processes at the respective nodes.

14 Tool Components LoadGenerator Responsible for building the command line depending on the type of transaction, spawning the load generator process, parsing the output and retrieving response time metrics. SlaveInteractor Responsible for sending and receiving commands to and from slaves respectively. Listener Responsible for interpreting the commands from Master and calling appropriate functions. OsInteractor Responsible for interacting with the Operating System and getting necessary profiling information ProfilerInteractor (Yet to be implemented) Interacts the in-process JVM profiler and gets the necessary data from it. dataprocessor (Yet to be implemented) Processes the data given by the profilerinteractor to get resource consumption profiles.

15 Working of Reads the configuration file. Sends commands to the slaves to initialize. Generates load by starting the load generator. Sends commands to slaves to get the Profiling information. Tabulate results. Currently uses Operating system level tools to get resource profiles.

16 XML DTD for specifying configuration information <!ELEMENT services (TransInfo+)> <!ELEMENT TransInfo (Name, WebInterface, NodesInfo+)> <!ELEMENT NodesInfo (Node, Process)> <!ELEMENT WebInterface (url,port,(uri uriinfofile sessioninfofile))> <!ELEMENT Node (#PCDATA)> <!ELEMENT Name (#PCDATA)> <!ELEMENT Process (#PCDATA)> <!ELEMENT url (#PCDATA)> <!ELEMENT port (#PCDATA)> <!ELEMENT uri (#PCDATA)> <!ELEMENT uriinfofile (#PCDATA)> <!ELEMENT sessioninfofile (#PCDATA)>

17 Experimental Setup

18 Input XML file Only a few shown. <?xml version="1.0" encoding="utf-8"?> <services> <TransInfo> <Name>Order Status</Name> <WebInterface> <url>metcalfe.it.iitb.ac.in</url> <port>8080</port> <uriinfofile>orderstatus.uris</uriinfofile> </WebInterface> </TransInfo> <TransInfo> <Name>New Order</Name> <WebInterface> <url>metcalfe.it.iitb.ac.in</url> <port>8080</port> <sessioninfofile>neworder.uris</sessioninfofile> </WebInterface> </TransInfo> <TransInfo> <Name>Schedule work order</name> <WebInterface> <url>metcalfe.it.iitb.ac.in</url> <port>8080</port> <uriinfofile>schedworkorder.uris</uriinfofile> </WebInterface> </TransInfo> <TransInfo> <Name>Cancel work order</name> <WebInterface> <url>metcalfe.it.iitb.ac.in</url> <port>8080</port> <uriinfofile>cancelworkorder.uris</uriinfofile> </WebInterface> </TransInfo> </services>

19 Output Only a few shown. Transaction := Order Status ============================== Average Response Time: 58.1 ms Service Times: metcalfe.it.iitb.ac.in ms ms Transaction := Customer Status ============================== Average Response Time: 93 ms Service Times: metcalfe.it.iitb.ac.in - 80 ms ms Transaction := Schedule Work Order ============================== Average Response Time: 36.1 ms Service Times: metcalfe.it.iitb.ac.in 28 ms ms Transaction := Update Work Order ============================== Average Response Time: 34 ms Service Times: metcalfe.it.iitb.ac.in 20 ms ms

20 Outline 1 Motivation Goals of this project Previous Work Overview 2 Existing Profilers The Lite Java Profiler with Lite Java profiler 3 4

21 Developed Lite Java profiler. Suitable for automation and is remotely controllable. Developed to profile distributed transactions. A basic framework is ready which can accomodate more advanced profilers. Preliminary experiments done on ECperf benchmark. Main Observations: Large container overhead. Further exploration needs to be done to characterize JVMPI output.

22 Future Work Further development of Lite Java profiler. Integrate Lite Java profiler with. Add more features to to profile session based transactions. Integrate with topology determination tool. To conduct experiments to confirm the need for fine grained resource consumption information.