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2. Agenda > Digital River > Case Study > The Cloud> Challenges > Capacity > Accuracy > Connectivity> Optimization > Summary 3. >Global Cloud Commerce Solution Provider > Founded in 1994 > Over $3 billion in annual online sales>Daily Stats > > > >20 million page views 30 million emails 175,000 orders 5 terabytes of digital content>8 global data centers>Industries > > > >Software Consumer Electronics Games Payment Processing 4. Case Study > Dec, 2011 Digital River launched high-capacity order capture solution > Capable of capturing 6,000 orders per second > Per hour, thats > 2 million orders > 400 stadiums > The state of Nevada> 3 day timeline for external performance validation 5. Challenges > Load Generators > Capacity > Tuning> Space > Supporting teams> License cost > Internal network infrastructure > Time! 6. Solutions > Add internal generators > Cost, space, infrastructure, installation, time > Not external> External vendor > Cost, connectivity, unfamiliar with app> External generators in public cloud > Connectivity 7. The Cloud > Virtual machine (VM) impermanence> Capacity and accuracy > Connectivity 8. The Cloud 9. The Cloud Impermanence 10. The Cloud Impermanence 11. The Cloud Capacity and accuracy> http://aws.amazon.com/ec2/instance-types/ > Dedicated CPU, memory, local storage> Shared network, disk subsystem > Larger instances guarantee less variability in shared resources 12. Cost > http://aws.amazon.com/ec2/pricing/ 13. The Cloud Connectivity54345 ControllerGenerator50500 Controller System Under Test (SUT)443MI ListenerGeneratorSystem Under Test (SUT) 14. The Cloud Connectivity54345 Controller GeneratorSystem Under Test (SUT) RDP (3389) - SSH (22) 15. Installation > Launch an Instance 16. Associate an IP Address > Each generator needs a static IP 17. Installation - Windows > Windows Server 2008 > Limited to c1.xlarge > 8 Cores, 7GB RAM> I/O performance: High1. RDP to running instance 2. Download LoadRunner3. Mount image 4. Install 5. Open port 54345 18. Installation - Linux > A little more complicated ... > Red Hat Enterprise Linux 6.2 > Limited to c1.xlarge > 8 Cores, 7GB RAM > I/O performance: High1. Connect via SSH and Keyfile >Windows - Use PuttyGen to generate .ppk file from .pem file2. Log in as root user 19. Installation - Linux 4. Set environment variables > To set automatically on startup, create a .profile file in the /root directory, add this to the file: export M_LROOT=/opt/HP/HP_LoadGenerator export LD_LIBRARY_PATH=${M_LROOT}/bin export PATH=${M_LROOT}/bin:${PATH} export DISPLAY=localhost0.05. Copy LoadRunner installation files to the instance >Use WINSCP to connect and copy via SFTP 20. Installation - Linux 6. Unzip the archive > unzip 7. Mount the image Create the directory i.e. mount point: > mkdir -p /mnt/diskUse mount command as follows to mount iso file called disk1.iso: > mount -o loop LG_Linux_Install.iso /mnt/disk Change directory to list files stored inside an ISO image:> cd /mnt/disk > ls -l 21. Installation - Linux 8. Run the installer: > /mnt/disk/Linux/installer.sh9. Check files in path of LoadRunner installation: > /opt/HP/HP_LoadGenerator10. Install additional required packages > yum install compat-lib* > yum install glibc.i686 > yum install libstdc++.so.511. Install daemon process /opt/HP/HP_LoadGenerator/bin/m_daemon_setup -install 22. Installation - Linux 12. Create a wrapper script the starts the m_daemon_setup process in /usr/local/bin (to follow common practices) #!/bin/bash # LoadRunner load generator daemon startup script echo Initializing load generator daemon process echo This process is required to connect to the generator from the controller machine echo without using RSH # Installation command is: # /opt/HP/HP_LoadGenerator/bin/m_daemon_setup -install # If the daemon is already installed, just start it with the following commandm_daemon_setup start $M_LROOT/bin # Other args include: -kill, -remove, -start, -stop, -stat 23. Installation - Linux 13. Add this to your .profile file to run the script on startup > source /usr/local/bin/init_loadgenerator_daemon> Considerations, additional security > MI Listener configuration > RSH vs. daemon process > Host Security Manager (since LR 9.5) 24. Connect Controller to Generators > Windows, no extra steps > Linux, specify UNIX OS > Log in via SSH, verify connectivity and daemon process> Generator Details > Controller > Unix Environment > Check Dont use RSH 25. Generator - Unix Environment Settings 26. Optimize for High Throughput > Load generators create thousands of connections > Limit of 65,534 connections per network interface> Avoid port starvation, increase the port range used, and allow reuse of sockets in TIME_WAIT > Windows > HKEY_LOCAL_MACHINESYSTEMCurrentControlSetServi cesTcpipParameters > Set value to 65534> Linux > sysctl -w net.ipv4.ip_local_port_range="1024 65535 > sysctl -w net.ipv4.tcp_tw_recycle=1> Linux has a throughput advantage here! 27. Use Multiple Data SourcesControllerCloud GeneratorPhysical GeneratorSystem Under Test (SUT)External Monitor 28. Case Study Results > Cloud generators yielded reliable results > Alignment across internal generators, external generators, and independent client validation> Results from single server yielded 2,000+ orders per second 29. Case Study Results > Linear scale confirmed Orders Captured per Second by Server Count 35,00030,000Orders per Second25,00020,00015,00010,0005,0000 12345678Server Count9101112131415 30. Summary > The cloud is cost effective but unpredictable > Capacity > Use the largest footprint possible> Accuracy > Compare results across data sources > Monitor physical and virtual utilization (if possible)> Connectivity > 54345 or MI Listener > Linux - LR Daemon or RSH > Configure optimal port range, remember Linux advantage 31. Benefits > Cost Savings > Hardware > $4000 for 8 core, 8GB server> $400 monthly maintenance> External vendor - $20K> Time > No dependence on infrastructure team for provisioning/support/maintenance> On demand flexibility 32. Questions?
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