OpenStack Assessment : Profiling & Tracing



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Transcription:

OpenStack Assessment : Profiling & Tracing Presentation by Hicham ABDELFATTAH Master Director Mohamed Cheriet

Outline Introduction OpenStack Issues Rally Perspectives 2

Definition Cloud computing is a model for enabling ubiquitous, convenient, on demand network access to a shared pool of configurable computing resources [ ] that can be rapidly provisioned and released with minimal management effort or service provider interaction. NIST 3

Delivery models Applications Applications Applications Data Data Data Runtime Middleware Operating System Virtualization Runtime Middleware Operating System Virtualization Runtime Middleware Operating System Virtualization Delivered as a Service User manages Servers Servers Servers Storage Storage Storage Networking Networking Networking Infrastructure as a Service Platform as a Service Software as a Service 4

OPENSTACK 5

OpenStack OpenStack is a cloud operating system that controls large pools of compute, storage, and networking resources throughout a data center, all managed through a dashboard that gives administrators control while empowering users to provision resources through a web interface. OpenStack Foundation 6

Release History Austin 22 October 2010 Bexar 3 February 2011 Cactus 15 April 2011 Diablo 22 September 2011 Essex 5 April 2012 Folsom 27 September 2012 Grizzly 4 April 2013 Codenames alphabetically ordered 6 month development cycle Havana 17 October 2013 Icehouse 17 April 2014 Juno 16 October 2014 Kilo 30 April 2015 https://wiki.openstack.org/wiki/release_naming https://wiki.openstack.org/wiki/releases 7

Horizon Swift Glanc e Nov a Cinder Neutron Keyston e Heat 98 Ceilometer Sahar a

Issues And Operator s wishes How Operators can verify their cloud works well easily in a short time During/After setting up After adding compute/controller nodes Minor software update How we can ensure that OpenStack work at scale? How we can detect performance issues quickly and improve OpenStack scalability? 10 9

Which element should be improved? Is it.. Hardware? Deploy? Code? BUT How deployment topology influences performances? Which piece of the code is a bottleneck? What hardware limits are hit? 11 10

List of Metrics Metric Availability Rate Mean-Time Between Failures (MTBF) Network Capacity Storage Device Capacity Server Capacity Instance Starting Time Description Percentage of service uptime; measured as total uptime against total time" Expected time between consecutive service failures"; measured by normal operational period duration and number of failures "Measurable characteristics of network capacity"; measured by bandwidth, throughput in bits per second; expressed as number of megabits per second. "Measurable characteristics of storage device capacity"; measured and expressed in storage size in gigabytes. "Measurable characteristics of server capacity"; measured and expressed as number of CPUs, CPU frequency in GHz, RAM and storage size in GBs. "Length of time required to initialize a new instance"; measured by data and time the instance was up and the date and time of the start request. Cloud Computing: Concepts, Technology & Architecture, - authors Thomas Erl, Zaigham Mahmood and Ricardo 11

List of Metrics Response Time Storage Scalability (Horizontal) Server Scalability (Horizontal) Server Scalability (Vertical) "Time required to perform synchronous operation"; measured by date and time of response and total number of requests, expressed as averages in milliseconds. "Permissible storage device capacity changes in response to increased workloads"; measured and expressed in storage size in gigabytes. "Permissible server capacity changes in response to increased workloads"; measured and expressed as number of virtual servers in resource pool. "Permissible server capacity fluctuations in response to workload fluctuations"; measured and expressed as number of CPUs, RAM size in gigabytes. Cloud Computing: Concepts, Technology & Architecture, - authors Thomas Erl, Zaigham Mahmood and Ricardo 12

What is Rally? Rally is a community-based project that allows OpenStack developers and operators to get relevant and repeatable benchmarking data of how their cloud operates at scale. https://wiki.openstack.org/wiki/rally 15 13

Use Case https://wiki.openstack.org/wiki/rally 16 14

How Rally works Deploy OpenStack Cloud Run Specified Scenarios Get results Parameters Number of users Number of tenants Concurrency Duration Get results Execution time breakdown Failure rates Graphics Profiling data 15

Next Step Nova-api Schedul er Network READY TO USE Nova-db Comput e Glance How many seconds/minutes were spent in every component!? 16

Next Step : OpenStack Demo Setup Private Networks: eth0: 172.16.0.40/24 Control Nodes Compute Nodes compute Neutron scheduler volume glance Ceilometer Heat 172.16.0.71 172.16.0.51 172.16.0.52 172.16.0.53 172.16.0.54 compute Neutron compute Neutron compute Neutron Compute Neutron 10.0.9.10 10.0.9.11 10.0.9.12 10.0.9.13 10.0.9.14 Scale Out Public Networks: eth1: 10.0.9.0/25 19 17

Q&A 20 18