Management for Cloud Computing Michael Salsburg amp Steve Guarrieri Unisys CMG Late Breaking Paper Datacenter Evolution Upgrades were planned many quarters in advance Each upgrade represented a major portion of the IT budget ID: 414956
Download Presentation The PPT/PDF document "Extreme Capacity" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
Slide1
Extreme Capacity Management for Cloud Computing
Michael Salsburg & Steve Guarrieri
Unisys
CMG Late Breaking PaperSlide2
Datacenter Evolution
Upgrades were planned many quarters in advance
Each upgrade represented a major portion of the IT budget
Virtuous Cycle
Integration
Simplification
CommoditizationSlide3
Administration Evolution
Ratio of Operators / Administrators to servers has reversed
Commoditization of administration is under waySlide4
Cloud Computing - Escape Velocity
Page
4
Utility Computing
SOA
Server Virtualization
Cloud ComputingSlide5
Cloud Computing
Providers and Consumers
Vendors
Integrator
Provides
Hardware / Software
Components
Provider
Provides
ITSM / Self-Service / Automation
Capabilities
Tenant
Provides
IaaS / PaaS
End Users
Sub Tenants
Provides
Added Capabilities
Provides
Cloud Services /
SaaS / ApplicationsSlide6
Key Attributes of Cloud Computing
Self-Service -
This principle is described using the NIST definition.
With self-service, a consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service’s provider.
It is the availability of cloud infrastructure as a service
that differentiates cloud computing from more traditional approaches.Ubiquity – services can be consumed from an Internet-enabled deviceElasticity –
As service demands change, the amount of cloud infrastructure dedicated to these services can grow and shrink accordinglyUtility – This is the economic catalyst for using a cloud.
Pay as you Grow and ShrinkMulti-tenancyNo Capital Expenses
Page
6Slide7
FEED ME!!!
Cloud Computing
Sizing without prior knowledge of workloads
Keeping up with the commitment to elasticity
Quick provisioning process may cause over-provisioning of specific resourcesSlide8
Applications follow a PatternSlide9
Utilization and Balance
Data Tier
Application Tier
Web Tier
Define Perfect Balance
When one component of the “trinity” is exhausted the other two should also be near exhaustion
Hypothesis
There are essentially three profiles, matching the three tiersSlide10
Hardware-Independent Approach
Issues with the tuple
What happens when a workload is moved from one type of server to another?
What happens when files are moved to SSD?What is the real definition of network utilization from the server’s point of view?Slide11
Example – Vmmark results
Web Server
App Server
File Server
DB Server
Application
SPECweb™
2005-based
SPECjbb™
2005-based
dbench
MySQL
VM OS
SLES 10 64-bit
Win 2003 64 bit
SLES 10 64-bit
SLES 10 64-bit
VM Platform
2 CPU
512MB RAM
8 GB disk
2 CPU
1GB RAM
8 GB disk
1 CPU
256MB RAM
8 GB disk
2 CPU
2GB RAM
10 GB disk
CPU Utilization
30%
10%
14%
19%
Storage I/O/s
11
.7
417.6
84
Network I/O/s
3412
1
1564
1772
http://www.vmware.com/products/vmmark/Slide12
Further Investigation
Develop rules of thumb (ROT) based on recognizable patterns and relative arrival rates within these tuples
Study empirical data from cloud workloads
This implies knowledge of utilizations / arrival rates / service times as well as the type of processes using these servers
Input to our evolving rules of thumb from other investigators (that’s YOU)Slide13
Questions?
Michael.salsburg@unisys.com