Headroom
A Measure of Server Remaining Capacity
Prem S. Sinha, PhD.
President, CEO
PerfCap Corporation
85, Perimeter Road, Nashua, NH 03063
www.PerfCap.com; Info@PerfCap.com; 603-594-0222
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Challenges
• Pro-active Vs. Re-active planning
• Large number of geographically
dispersed systems
• Traditional Capacity Planning
Methodology takes too long
• Automated process – daily basis:
–
–
–
–
Collect/consolidate data
Generate reports
Publish on a web site
Notify – “need to know” basis
2
Capacity Planning
Definition:
 A process to determine how much computing resources are
required to meet business growth
Or
 How much business can grow before some device will run
out of capacity
 To answer “What if” questions like:
– Can my current configuration handle three times of current workload – when will
my current configuration saturate
– What will be impact of a new application on current system performance
– What will be impact of upgrading a current server or adding a new server
– Can I reduce the number of servers with out violating my “Service Level
Agreement” – a.k.a Server Consolidation
3
Sizing Methods
Real
System
Benchmarks
Simulation
Models
Rules
of
Thumb
Analytic
Models
Linear
Projections
Accuracy
4
Capacity Planning via Modeling
Steps:
• Data Collection
• Identifying Peak Interval(s)
• Workload Characterization
• Model Validation
• Saturation Analysis
• “What If” Analysis
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Capacity Planning via Trending
Performance Metric
(Av. or Peak CPU Utilization)
Capacity Limit
Today
Remaining
Capacity
J F M A M J J A S O N
D
Time
• Simple to produce and follow
• Issues
• defining right Capacity Limit
• single vs composite metric
• end user satisfaction
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PAWZ Planner
Where do you want to operate?
Response Time
Response Time = S{Service Time + Queuing Time}
Headroom
Saturation Point
Current Workload
l
Workload
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System Capacity – An Example
A Trading System
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Response Time = S{Service Time + Queuing Time}
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Normalized Response Time
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Significant
performance
degradation
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6
5
4
3
Today
2
1
Headroom today is ~60%
0
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Quotes/sec
System capacity is ~8500 quotes/sec.
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Each Day PAWZ Automatically Models Each
System
to Determine
System Capacity
PAWZ
– Saturation
Analysis
At 125% growth from
Nov. 25th, system will
reach capacity.
-100% is no load.
0% is Nov. 25th load.
Headroom is 55% of capacity
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PAWZ Maintains Trend of Daily Headroom
To Forecast Decline of to Critical Level
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Still not enough …
Problem:
Not enough time to examine response time
curves or headroom trends for many systems:
Solution:
Risk Analysis provides high-level overview
of headroom trends of all systems.
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Risk Analysis
• Need to know how soon headroom will
reach a given level.
• Daily risk state determined by time left until
headroom will decline to user-defined
thresholds.
• Risk states for multiple systems displayed
as color status (red, green, amber) counts.
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Headroom Risk Analysis
Headroom reaches 0
Headroom
Headroom crosses threshold
Current state
Lead time
Lead time
Headroom threshold
Time
Amber status – system
within lead time of dropping
below headroom threshold.
Red status – system
within lead time of
exhausting capacity.
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PAWZ Maintains Trend of Daily Headroom
To Forecast Decline of to Critical Level
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Risk Analysis Summary
Group of Systems
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Headroom
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Asset Location
Configuration
Change Report
Critical Systems
Asset
Reports
PAWZ
FindIT
Server
Daily, Weekly
Health Reports
(NT/W2K)
Intranet
HP-UX
Real Time
LINUX
Trending
Performance
Reports
Windows
NT/2000/XP
Applications
Events
Clusters
Networks
SUN Solaris
Storage
Tru64 UNIX
IBM-AIX
OpenVMS
Cluster
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Automated Daily Performance Reports
CPU Usage by Applications
Disk Usage by Drives
Memory Allocation by Type
Network Traffic by Protocol
Dashboard Style Summary by Group
Exceptions by Type
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Automated Daily Capacity Reports
Historical CPU Usage Trend
Daily Capacity Saturation Graph
Remaining Headroom Capacity Trend
Daily Risk Trend
Web Based “What-if”
Before
Upgrade
After
Upgrade
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Summary
• Headroom provides a composite index to measure
remaining Capacity of a Server
• By automating the process of
–
–
–
–
Data Collection
Data Consolidation
Saturation Analysis
Risk Analysis
one can do Capacity Planning of large number
Servers in a timely manner
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