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www.metron-athene.com
Top 5 Key Capacity Management Concerns
for UNIX/Linux
Jamie Baker
Principal Consultant
www.metron-athene.com
Agenda
• UNIX and the Datacenter
• Virtualization and VM Principals
• Performance Concerns
• Linux Differences
• Cloud Concerns
• Big Data Concerns
• Big Data Capacity Challenges
• Key Capacity Metrics
• Conclusion
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UNIX and the Datacenter
• Physical and Virtual hosts– Web Servers
– Database hosts
• Licensing concerns – vCPUs, pCPUs
• KPIs– Reduction in physical estate (servers)
– Reduction in physical space
– Reduction of power usage, cooling, associated costs
• Use of Internal / External / Hybrid clouds– Underpinned by virtualization
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Virtualization
• Why virtualize?
• Commercial Vendors
– IBM,HP, Oracle, VMware, Microsoft
• Open source (Linux)
– KVM
– Xen
• Underpins cloud technology
– IaaS, PaaS, SaaS
• Oracle’s Linux offering and its cost differences
over Solaris Containers
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VM Principals
• Isolation
– Own root (/), processes, files, security
• Virtualization
– Instance of Solaris O/S
• Granularity
– Resource allocation, Pools
• Transparency
– Standard Solaris interfaces
• Security
– No global reboots, isolated within each zone
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Performance Concerns
• Hypervisor – x86 virtualization
– Shared resources and additional overhead
– Contention, queuing and response times
– Paravirtualization
• Data
– Local or Remote capture – overhead?
– Accuracy?
• sysstat version
• memory double counting
• o/s bugs
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Zone Memory Reporting
0
100
200
300
400
500
600
700
800
05/06/2013
RSS GB, ss-280,global
RSS GB, ss-280,ss291
RSS GB, ss-280,ss313
RSS GB, ss-280,ss314
RSS GB, ss-280,ss315
RSS GB, ss-280,ss317
RSS GB, ss-280,ss318
RSS GB, ss-280,ss319
RSS GB, ss-280,ss320
RSS GB, ss-280,ss321
RSS GB, ss-280,ss355
RSS GB, ss-280,ss356
RSS GB, ss-280,ss357
RSS GB, ss-280,ss358
RSS GB, ss-280,ss359
RSS GB, ss-280,ss365
Total Memsize GB, ss-280
RSS Memory Usage vs. Total Server Memory CapacitySun Server 280
Wednesday June 5 2013
Total Memory Capacity (GB)
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Linux differences
• Open source, freely available
• Originally considered for academics (MINIX)
• Now most major software vendors are porting to Linux
• Linux user base > 25 million
• UNIX was choice for large multiprocessor systems,
but since 2011 Linux powers over 90% of the top 500
servers
• Is installed on mobile phones, tablet computers, video
game consoles, to mainframes and supercomputers
• x86 virtualized operating system
• Increasing popularity because of application in
embedded technologies, free and easily available
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Cloud Concerns
• Cloud (Internal, External, Hybrid)
– Rapid Provisioning
– Metering (Chargeback) CoD
– Resource Pooling and Elasticity
• Hybrid popularity growing
– At present less secure tasks being handled in
external clouds
– Increasing confidence in security
– How easy is access to data? Do we care?
– SLA’s and appropriate penalties if breaches occur
9
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Big Data Concerns
• What is Big Data?
– Data sets whose size grows beyond the management
capabilities of traditional software that has been used in
the past.
• Support for Hexa and Peta bytes
• Hadoop (HDFS)
– MapReduce function
– not recommended for SAN/NAS
– local block storage
• What should we be monitoring?
• What are the challenges?
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Big Data Capacity Challenges
• Working with the business to predict usage
• New technology, limited knowledge around
performance tuning
• Very dynamic environment
• Multiple tuning options that can greatly affect
the utilization/performance of systems
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Key Capacity Metrics
• Standard CPU metrics
o utilization, system/user breakdown
• Memory
o Usage, Paging, Swapping
• User/Process breakdown – define workloads
• File System
o Size
o Number of Files
o Number of Blocks
o Ratio’s
o User breakdown
• I/O
o Response time
o Read/Writes
o Service times
o Utilization
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CPU Breakdown
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0
5
10
15
20
25
02/04/2012
Core Sy stem Estd % Core User Estd % Core Total Estd %
CPU System/User Breakdown vs. Total sparczones
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I/O Response Time
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0
5
10
15
20
25
30
35
40
ss-280,md10 ss-280,md15 ss-280,md20 ss-280,md35 ss-280,sd10 ss-280
Disk I/O Response Time msecs
SS280Disk I/O Response Time msecs
June 2013
Remainder (aggregated)
Top 5 disks
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Conclusion
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• UNIX/Linux systems are a well established part of any
datacenter
• Extensive use of virtualization, underpins Cloud
Computing
• Monitor and analyze the OS data, can you trust it?
• Linux popularity ever increasing, GUI driven, similar
model to Windows, supported on x86 virtualization
• UNIX/Linux systems support Big Data
implementations, using HDFS (Hadoop)
• Do we fully understand the technology to be able to
perform effective CM?
• Identify what you need to monitor and analyze, get the
business information, predict future usage
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References
Unix and Linux differences
http://www.diffen.com/difference/Linux_vs_Unix
Cloud Computing – An explanation
http://www.cloudstacking.com/?page_id=318
Big Data
http://metron-athene.com/_downloads/on-demand-
webinars/index_2.asp
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Top 5 Key Capacity Management Concerns
for UNIX/Linux
Jamie Baker
Principal Consultant
