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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. Challenges. Pro-active Vs. Re-active planning Large number of geographically dispersed systems
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HeadroomA 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
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
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
Sizing Methods Real System Bench- marks Cost Simula- tion Models Analytic Models Linear Projec- tions Rules of Thumb Accuracy
Capacity Planning via Modeling Steps: • Data Collection • Identifying Peak Interval(s) • Workload Characterization • Model Validation • Saturation Analysis • “What If” Analysis
Capacity Limit Today RemainingCapacity J F M A M J J A S O N D Capacity Planning via Trending Performance Metric(Av. or Peak CPU Utilization) Time • Simple to produce and follow • Issues • defining right Capacity Limit • single vs composite metric • end user satisfaction
Response Time Headroom Saturation Point Current Workload l Workload PAWZ Planner Where do you want to operate? Response Time = S{Service Time + Queuing Time}
Significant performance degradation Today Headroom today is ~60% System capacity is ~8500 quotes/sec. System Capacity – An ExampleA Trading System 10 Response Time = S{Service Time + Queuing Time} 9 8 7 6 Normalized Response Time 5 4 3 2 1 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Quotes/sec
Each Day PAWZ Automatically Models Each System to Determine System Capacity At 125% growth from Nov. 25th, system will reach capacity. -100% is no load. 0% is Nov. 25th load. Headroom is 55% of capacity
PAWZ Maintains Trend of Daily HeadroomTo Forecast Decline of to Critical Level
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.
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.
Headroom reaches 0 Headroom crosses threshold Current state Lead time Lead time Headroom threshold Red status – system within lead time of exhausting capacity. Amber status – system within lead time of dropping below headroom threshold. Headroom Risk Analysis Headroom Time
PAWZ Maintains Trend of Daily HeadroomTo Forecast Decline of to Critical Level
Asset Location Desk TopBrowser Configuration Change Report Critical Systems Asset Reports PAWZ FindIT Server (NT/W2K) Daily, Weekly Health Reports Intranet HP-UX Real Time LINUX Trending Performance Reports Windows NT/2000/XP Applications Events Clusters OpenVMS Cluster SUN Solaris Networks Storage IBM-AIX Tru64 UNIX
Disk Usage by Drives Memory Allocation by Type Network Traffic by Protocol Dashboard Style Summary by Group Exceptions by Type Automated Daily Performance Reports CPU Usage by Applications
Daily Capacity Saturation Graph Historical CPU Usage Trend Remaining Headroom Capacity Trend Web Based “What-if” Daily Risk Trend After Upgrade Before Upgrade Automated Daily Capacity Reports
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