A Framework for Modeling and Execution of Infrastructure Contention Experiments

1. A Framework for Modelingand Execution ofInfrastructure Contention Experiments Carmelo Ragusa, Philip Robinson and Sergej SvorobejMERMAT 2013, FIA, 7 May, Dublin

2. Agenda Introduction • Problem analysis of conducting experiments about resource sharing in multi-tenancy systems Proposed solution • COCOMA framework: objectives, design, benefits and stakeholders Use case • How resource contention affect users for different physical resources partitioning configurations Summary and future work

3. Motivation • Problem: • How can we study these issues? • How can we emulate multi-tenancy behaviour? • How can we reproduce the same experiments? • Resource (memory, disk, network, cpu) contention occurs in shared multy-tenancy environments such as clouds SuT Unknown Cloud Infrastructure More detailed cloud experiments can be interested to investigate how the System under Test (SuT) performs under various contention patterns that may occur in practice.

4. Requirements for supporting rigoroussoftware testing in contentious, multi-tenant environments • Scalability • Reproducibility • Portability • Extensibility • Self-containment • Controllability

5. Current approaches to reproduce operational conditions such as contention Manual: use of a number of resource-specific tools and command-line operations in order to manipulate operational conditions. Client-Based: simulation of usage, using multithreaded client-side request generators in order to load target environment and raise required operational conditions. Ad-Hoc Scripting: use of custom-built scripts for higher-level coordination of load generation and test execution.  Each one fails in same way to meet the previous listed requirements

6. Proposed solution • A framework for COntrolledCOntentious and Malicious (COCOMA) patterns: deliberately make the platform “misbehave” – contention, faults and attacks. SuT Unknown COCOMA Cloud Infrastructure Experimenters will be able to: • study their system under real world effects conditions • control those conditions • reproduce exact conditions • correlate conditions and results of their system under test • use those findings to discover weaknesses and tune/enhance their system

7. Design principles Virtual Machine Experiment XML • Separation of concerns • Provide unified and coherent interface for staging experiments • Allowing advanced workload patterns via distribution algorithms • Abstraction from low level tools • Easy composition of complex patterns • Easy extensibility COCOMA DistributionAlgorithms DistributionAlgorithms DistributionAlgorithms Emulators Stressapptest Iperf Iperf Iperf etc. Lookbusy Resource contention

8. Concepts and terminology * 1 Emulation Emulator 1 1 1 1 * 1 Distribution Resource-Type • An emulation is composed of pairs of distribution-emulator • An emulator in a distribution is bound to a specific resource type • A distribution is a workload trend • Distributions are broken down into multiple runs to create the desired trend • Runs are single instantiation of low level tools • For complex scenarios users can specify multiple distribution-emulator pairs e.g. CPU, RAM, Net, I/O - type - duration - granularity - parameters[] e.g. linear, trapezoidal, exp, trace Distribution-3 (NET) Distribution-2 (RAM) Distribution-4 (I/O) Distribution-1 (CPU) Emulation time tn t1

9. Use case: How resource contention affect users for different physical resources partitioning configurations Test environment: single machine with 4 CPU cores and 16 GB of RAM We abstract resources’ values with ranges from Low to High Each configuration represents VMs with different resources assigned, providing a specific physical resources partitioning

10. Validation use case • sysbench CPU benchmark calculating the first 100K prime numbers • memspeed RAM benchmark • tiobench IO benchmark

11. Stakeholders • Performance testers/engineers • Cloud Service Providers • Cloud Application Administrators • Application Developers and Testers • Benchmarks and Standards Groups

12. Summary • Experimenters need means that recreate conditions in cloud-like multy-tenancy shared systems to enable testing their solutions • Current approaches are limited as they fail to meet requirements for such environments • We proposed a solution that • abstracts from low level tools • enables from simple to complex repeatable scenarios, reducing experimenters’ effort • allows investigating the system behaviour and correlate it to the specific conditions created • A simple validation use case was presented

13. Future work Implementing malicious and faultiness modules, and relative distributions Real system workload traces parsing and replay capability Distributed COCOMA solution to enable large complex distributed scenarios Web UI to manage the framework Contention at CPU cache level Tool to record system traces in a COCOMA compatible format for reply purpose Extend emulation analyser for distributed version to get warnings for large scenarios' emulations

14. Acknowledgements This work has being carried out within the BonFIRE project, which has received research funding from the EC’s Seventh Framework Programs (EU ICT-2009-257386 IP under the Information and Communication Technologies Program)

15. Thank you Contact information: Carmelo Ragusa SAP HANA Cloud Infrastructure, Belfast carmelo.ragusa@sap.com COCOMA is released as Open Source under Apache v2 license: https://github.com/cragusa/cocoma