Dependability Measurement and Evaluation Tool

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1 : Dependability Measurement and Evaluation Tool Yutaka Ishikawa, Mitsuhisa Sato, Toshihiro Hanawa, Hajime Fujita, Takayuki Banzai, Hitoshi Koizumi, and Shin ichi Miura University of Tokyo and University of Tsukuba A tool to execute dependability benchmarks measuring availability, reliability, performance, and power consumption under an anomaly situation Benchmark targets Whole system Subsystems Network driver Server processes The results of benchmarks are used as the evidence of dependability required by in the design and test t phases D-Logger D-Analyzer D-Effector D-System Type/Model DS-Bench/ D-Visor D-Box Monitor Walker Editor Checker D-Cloud Anomalydetection Quick Evidence DCase DCase Evidenceby EvidencebyUnittest Analysis Responsiveness management Execution Update Integrationtest test DEOS FrameworkTools DEOS Process growthcycle Requirement/Environment Changeaccommodatingcycle Systemchangerequests basedonstakeholders Design Implementation Verification Test agreement Stakeholders requirements/ System environment Causeanalysis changes Responsiveaction Failurereactingcycle Failureprevention Anomalydetection/ Unexpectedfailure Achievementof happen accountability Normal operation Bottom Structure Sub-Goal Evidence Sub-Goal Evidence 2

2 with Content sizes increase. The stakeholder and the developer decide increasing the network bandwidth Client Normal state reports 1.5 million requests /sec using SpecWEB benchmark reports 0.5 milli- second recovery time when faults happen reports 920 Mbps Faulty state Web server Heartbeat Stand-by The server must handle 1 million requests per second reports 1.5 million requests /sec using SpecWEB benchmark One more network link is added WEB Server is dependable Hardware components are argued HA server is used High availability and performance are argued When the system goes down, it must recover within 1 milli-second reports 0.5 millisecond recovery time when faults happen The network link offers at least 1.6 Gbps under the safe condition reports 1.8 Gbps in the normal state and 850 Mbps under one network link fails The network link offers at least 800Mbps reports 920 Mbps 3 An Overview of Anomaly situations hardware faults, software bugs, human errors Two Measurement Environments Target Hardware Specific Environment Cloud Environment Virtual Machines Key Features Benchmark Database Customization of Anomaly Scenario Benchmark Cloud 4

3 An Overview of Key Features Benchmark Database Customization of Anomaly Scenario Benchmark Cloud Benchmark Database Performance Benchmarks (Workload), Measurement Tools, Anomaly Generators, Anomaly Scripts Resultsof dependability d benchmarks The system maintainer can confirm whether the behavior observed at the operation phase has been reported during some previous anomaly situation. 5 An Overview of Key Features Benchmark Database Customization of Anomaly Scenario Benchmark Cloud Anomaly is constructed with anomaly generators and an anomaly script written in XML. An anomaly script gives instructions on how to use anomaly generators. A new anomaly script tfor a new application field is described using anomaly generators. Anomaly scripts may also be used and modified by other users for other target environments. 6

4 An Overview of Key Features Benchmark Database Customization of Anomaly Benchmark Cloud Considerable computing resources are required in order to test many dependability benchmarks. Some benchmarks may run on any computer that provides a virtual machine environment in which h a hardware simulator can operate. A benchmark cloud is a benchmark execution environment which uses general purpose computer resources, in which virtual machines run, and which can model application-specific hardware. Dependability benchmarks run in parallel with the benchmark cloud, and thus the benchmark cloud contributes to reducing the execution time of dependability benchmarks. 7 Limitations and Intentions The is only effective for anticipated anomaly conditions. It does not reveal weaknesses of the system in unexpected anomaly conditions It does not find the cause of such conditions. D-Logger D-Analyzer D-System D-Visor When an unknown cause of a new anomaly Monitor Anomalydetection Quick situation is faced, Analysis DEOS FrameworkTools 1. Finding the cause DEOS Process 2. Developing a program to generate the anomaly, Requirement/Environment i.e. anomaly load. Changeaccommodatingcycle 3. Registering the program in the database The range of testing for dependability in the target system is increased. Dependability in other systems is also increased using this new benchmark Stakeholders requirements/ System environment changes D-Effector D-Box Walker Evidence DCase Responsiveness management Execution Systemchangerequests basedonstakeholders agreement Causeanalysis Responsiveaction Failureprevention Design Anomalydetection/ Unexpectedfailure happen Editor DCase Update Implementation Type/Model Checker EvidencebyUnittest Failurereactingcycle Normal operation growthcycle Verification DS-Bench/ D-Cloud Evidenceby Integrationtest Test Achievementof accountability 8

5 The Rest of Talk Details of DS-Bench Details of D-Cloud 9 DETAILS OF DS-BENCH 10

6 Details of DS-Bench: Basic Components Tester DS-Bench Controller & Frontend Basic Workflow of DS-Bench 1. Edit benchmark configurations 2. Execute the benchmark 3. Examine the benchmark result 4. Compare the result with previously recorded results Web Interface Benchmark Database XML (Benchmark Results) XML (Benchmark Scenario & Anomaly Script) Target Hardware Specific Environment Target Machines Network Switch (Network Port is controlled via SNMP Tool Measurement Tool Benchmark Benchmark Results Performance Benchmark Anomaly Generator Anomaly Script PDU Power is controlled via HTTP,SNMP 11 DS-Bench: Usage Example Providing evidences for LinkRefuse: Shutting off a network link Anomaly Load Diagram Gn: RI2N RI2N The network link offers at least 1.6Gbps under normal situation 800Mbps under one link failure Sub Goal En: DS-Bench result: iperf achieved around 1.8Gbps under normal situation around 850Mbps under one link failure Benchmark Result = Evidence Target Machines iperf: Network bandwidth measurement Benchmark Program RI2N: Redundant Interconnection with Inexpensive Networks 2010/11/4 Version 12

7 Screenshot of DS-Bench Upper row Benchmark programs Lower row Anomaly loads This border shows the current time Time-line of the benchmark 2010/11/4 Version 13 Retrieving Data from Benchmark Outputs Usually the benchmark output comes with pre-formatted text tables In DS-Bench Bench, they are automatically converted to machine-readable values, by user-provided text cutting rule <caption>iperf</caption> <table> <header> Client connecting to , TCP port [ s*id ] s*interval s*transfer s*bandwidth 5001 TCP window size: 0.02 MByte (default) </header> <rheader> [ 3] local port connected ID,Interval,Transfer,Bandwidth, with,,, port 5001 </rheader> <data> [ 3] sec 205 MBytes 1718 Mbits/sec ( d+). s*(.* sec) s*(.* [MGK]Bytes) s*(.*.*) </data> [ 3] sec 218 MBytes 1828 Mbits/sec <begin> [ s*id ] s*interval s*transfer s*bandwidth [ 3] sec 220 MBytes 1847 Mbits/sec </begin> <key>0111</key> [ 3] sec 222 MBytes 1866 Mbits/sec <value>0111</value> </table> [ 3] sec 220 MBytes 1844 Mbits/sec [ 3] sec 222 MBytes 1859 Mbits/sec [ 3] sec 88.5 MBytes 742 Mbits/sec Raw Text Output Text Matching Rule Per Each Benchmark Program Processed Data 14

8 DS-Bench: Supported Benchmarks and Anomaly Loads While benchmark programs and anomaly loads can be added to the framework by users, the following programs are supported by default. Name Description Bonnie++ Disk I/O benchmark cpustress A program just consuming a lot of CPU time (*) Hackbench System benchmark by generating a lot of processes simultaneously IMB Intel MPI Benchmark iperf Network bandwidth benchmark LinkRefuse Shutting off ports on a network switch (*) (*) Mainly used as anomaly loads LMBench System performance benchmark memstress A program just allocating a lot of memory (*) MPD MPI daemon NetCMD Adjusting network output bandwidth, injecting packet loss and packet reordering (*) NPB NAS Parallel Benchmark SupplyRefuse Shutting down power distribution to a target machine (*) terminator A program to unconditionally kill the specified process (*) 2010/11/4 Version 15 DETAILS OF D-CLOUD 16

9 Details of D-Cloud: Operation Flow of D-Cloud Eucalyptus Controller Transferfilesfor configuration,input data,program,etc. Startup guestos Transferoflog, snapshot,outputdata DCloud Controller Tester Complete guestos VMnodes Buildupup Test,injectfaults, tf environment createsnapshotalongscenario onguestos Obtainlog,snapshot, etc. 17 Testing Process Using D-Cloud User describes configuration file in XML manner. Contents of configuration file Definitions Machine definition: Hardware specification System definition: Software, libraries, Injection definition: Fault type, duration of fault Scenario for test Assignment of machine instance Designation of execution host Command for execution, fault injection Timing specification Description of configuration file <jobdescription> <machinedefinition> Machine description </machinedefinition> <systemdefinition> System description </systemdefinition> <injectiondefinition> iti Fault injection description </injectiondefinition> <testdescription> Scenario for test </testdescription> </jobdescription> Reference 18

10 Example of System Test Using D-Cloud: HA Server System High Availability Server Load-balancing of the access to Web servers Load balancer is redundant with stand-by operation. Load balancer monitors each other by heartbeat. The system behavior is evaluated under the faulty state. t Obtain the evidence for the D- Case Responses to HTTP requests are observed on the client. Diagram Client Goal G0: HA Server is dependable. S0: Sub-Goal G-LVS: Load-balancer continue to work when the fault occurs. Evidence Load balancer (Linux Virtual Server) Normal state Faulty state lv0 Heartbeat E-LVS: D-Cloud result: Lv1 can replace lv0 after heartbeat period. Web server (Apache) Stand-by lv1 ws1 19 ws0 Example Test Scenario for HA Server(1) <machinedefinition> <machine> <name>lvs</name> <cpu>1</cpu> <mem>2048</mem> <nic>1</nic> <id>emi-1d8c0caa</id> </machine> <machine> <name>ws</name> <cpu>1</cpu> <mem>2048</mem> <nic>1</nic> <id>emi-0acc0c2d</id> </machine> </machinedefinition> <systemdefinition> <systemconf> <name>systema</name> <host> <hostname>lv0</hostname> <machinename>lvs</machinename> <config>lvconfig</config> </host> <host> <hostname>lv1</hostname> <machinename>lvs</machinename> <config>lvconfig</config> </host> Client <host> <hostname>ws0</hostname> <machinename>ws</machinename> <config>wsconfig</config> </host> <host> <hostname>ws1</hostname> <machinename>ws</machinename> <config>wsconfig</config> </host> </systemconf> </systemdefinition> Load balancer (Linux Virtual Server) lv0 lv1 Web server (Apache) ws0 ws1 20

11 Example Test Scenario for HA Server(2) <injectiondefinition> <injection> <name>injectiona</name> <fault> <location>network</location> # fault location = network <target>eth0</target> # faulty device = eth0 <kind>loss</kind> # fault type = packet loss <time>50</time> # duration of the fault events = 50sec. </fault> </injection> </injectiondefinition> <testdescription> <run> <name>testa</name> System definition iti error <systemname>systema</systemname> e a e <halt when="300">down</halt> # 300sec. later after power-on, <script> # halt systema <on>lv0</on> <putfile>test.sh</putfile> #Put test.sh test.sh on lv0 <exec>test.sh</exec> # Execute test.sh on lv0 <inject when= 150">injectionA</inject> # 150sec. later after power-on, </script> # inject injectiona event. </run> </testdescription> </jobdescription> Injection definition Types of pre-defined fault injection Devices Contents Elements Hard disk Error of specified sector badblock Network Memory Specified sector is readonly Error detection by ECC Received data contains error Response of disk becomes slow 1bit error of packet 2bit error of packet Error detection by CRC Packet loss NIC is not responding bit error Byte at specified address contains error readonly ecc corrupt slow 1bit 2bit crc loss nic Bit byte 21 Screen Shot of D-Cloud System lv0 lv1 Fault injection 22

12 Example Using D-Cloud with SpecC Device Model Simulation with SpecC device model can be realized. SpecC Hardware status SpecC description Linux console on VM Keypad Display Linux on VM(QEMU) select() read() User program Keypad Device Driver Interrupt signal SpecC simulator (SCRC) Interrupt Control Status / Control Registers Socket TCP write() Display Device Driver Output buffer Socket TCP 23 Future R&D Plan Description of Evidence for An evidence provided by is currently the set of the benchmark description and its result. How to describe evidences for to handle them How the stakeholder and developer agree using the results of Testing Coverage Integration of 24

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