Adaptive Server Farms for the Data Center
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Transcript of Adaptive Server Farms for the Data Center
Adaptive Server Farms for the Data CenterContact: Ron Sheen Fujitsu Siemens Computers, Inc
Sever Blade Summit, Getting the most from your blade servers, March 22, 2005
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The challenge – over provisioned, inflexible infrastructure
Today‘s computing infrastructure – Static and unshared islands for each service
Inefficient
Costly
Over provisioned
Hard to manage
Inflexible
Utilization of UNIX/Windows servers is low (<25% over 24 hours across all servers)Source: 2003 META Group – The Data Center of the Future
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The challenge – Cost Reduction
Labor costs - 75% of IT budgets - inefficiently applied across multiple, separate systems – mostly sustaining costs Excessive administration, upgrades, support, service, overhead
Administration and routine IT tasks are mostly manual Limited labor resources/budget focused on manual, low value tasks
IT over invests in resources for static, standalone systems Provisioning to meet peak demand Provisioning for backup systems and applications Resources duplicated; cannot be efficiently shared
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Addressing these challengesThe tools exist to address these challenges by:
Restructuring the data center to remove the barriers that isolate the various services into their various islands
Add tools to provision and monitor services and hardware
Add automation to automatically adapt to the changing needs of the services and users.
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Pooling and sharing of the overall resourceRemove
Boundaries
ConsolidateStorage
Establish overall management
Assign Services
Service A Service B Service C Service D Service E
ServiceServiceEE
ServiceServiceBB
ServiceServiceAA
ServiceServiceCC
ServiceServiceDD
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Shared Storage B1 B2 B3 Bn
.…
R/3 R/3 R/3R/3
LAN2 (Storage)
LAN1 (Public)
Shared Storage
Automation for QoS, Scaling, HA, Configuration and Provisioning
Assume a typical blade server farm - multiple blades/shared storage
Add server management, provisioning service, and control logic
Define policies and install monitoring and control agents
Server ManagementAnd Provisioning
Management Cluster
Management Cluster
AA A A
Monitoring and control agents (A) provide information on application state and QoS
Clients
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QoS Monitoring & Management
High Water Mark
Low Water Mark
Target Metric Range
Time
QoS Metric
Measured QoS metric exceeds the specified maximum acceptable valueAllocate more satellite nodes and deploy needed application to meet QoS target
Measured QoS metric is below the specified minimal acceptable value (too many resources)
Perform orderly shutdown of some instances thus reducing cost and freeing the resources for other work.
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Continuous Services
ServiceServiceBB
ServiceServiceAA
ServiceServiceCC
ServiceServiceDD
Adaptive infrastructure provides automated, continuous service and high availability without the costs of traditional infrastructure Application or server fails:
redirect user traffic …then
restart application or server
If no restart, but application service performance is satisfactory, there is no adjustment
If service performance is not satisfactory, then provision or reallocate another application/server
Control Nodes
Control Nodes
Server ManagementAnd Provisioning
ServiceServiceEE
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Summary of steps To implement adaptive server farms:
Establish an infrastructure with sharable server platforms, storage and networks
Implement a deployment service This can be a traditional deployment service like e.g. Altiris or Remote
Deploy Or a virtual server deployment like VMWare
Provide a highly-available management platform Monitor and collect information from all servers Correlate data and execute reaction scripts
Include agents on each server to provide data for the management platform Direct agents for monitoring application availability and performance Interfaces to application suite tools like Oracle Grid Manager
The following slides illustrate two example deployments with SAP suite and Oracle.
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Cost Reduction – Solution with server consolidation and automation
ServiceServiceAA
ServiceServiceCC
ServiceServiceDD
ServiceServiceBB
Service AService A Service BService B Svc CSvc C Svc DSvc DControl Systems
Unshared
Utilization 10%
Peak 50%
Different peaks
Reduced investment
Higher utilization
Automation saves labor cost
Spares
Before
After: Application Service Pools Spares with Automated Provisioning
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Server Consolidation example - SAP
Sample configuration for a SAP test environment
Images
SAP App
SAP CI
SAP Web
WIN SQL
SA
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Sample configuration for a SAP prod. environment
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Server Consolidation example - Oracle
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Oracle App S
Oracle RAC
Web Cache & J2EE
Oracle RDBMS
SA
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Oracle front end environment
Oracle decision support environment
OLTP application environment
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Automated Server Farm Management
Dynamic service provisioning and workload management for blade server farms Automated, mass installation of bare-metal
blade servers Automated, mass software deployment and
software updates Priority and workload-based reusage of
resources Continuous services
Benefits Reduced administration Low-cost scalability Simplified continuous availability
Images
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W2K + IIS
Linux + Apache
W2K + Citrix + MS Office
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Conclusion
Many of the costly operations in the data center can be automated
These techniques will provide high available and high quality of service without the overhead and complexity of traditional clustering
The following demo will illustrate how this all works together.