Capacity Planning - Managing the hardware resources for your servers.

Slides:



Advertisements
Similar presentations
Capacity Planning in a Virtual Environment
Advertisements

1 Magnetic Disks 1956: IBM (RAMAC) first disk drive 5 Mb – Mb/in $/year 9 Kb/sec 1980: SEAGATE first 5.25’’ disk drive 5 Mb – 1.96 Mb/in2 625.
Chapter 5: Server Hardware and Availability. Hardware Reliability and LAN The more reliable a component, the more expensive it is. Server hardware is.
High Availability 24 hours a day, 7 days a week, 365 days a year… Vik Nagjee Product Manager, Core Technologies InterSystems Corporation.
June 23rd, 2009Inflectra Proprietary InformationPage: 1 SpiraTest/Plan/Team Deployment Considerations How to deploy for high-availability and strategies.
Chapter Physical Database Design Methodology Software & Hardware Mapping Logical Design to DBMS Physical Implementation Security Implementation Monitoring.
Introduction to Systems Architecture Kieran Mathieson.
1.1 Installing Windows Server 2008 Windows Server 2008 Editions Windows Server 2008 Installation Requirements X64 Installation Considerations Preparing.
Measuring Performance Chapter 12 CSE807. Performance Measurement To assist in guaranteeing Service Level Agreements For capacity planning For troubleshooting.
1 Software Testing and Quality Assurance Lecture 40 – Software Quality Assurance.
Virtualization Infrastructure Administration Cluster Jakub Yaghob.
Virtual Network Servers. What is a Server? 1. A software application that provides a specific one or more services to other computers  Example: Apache.
Presented by Jacob Wilson SharePoint Practice Lead Bross Group 1.
Implementing High Availability
Load Test Planning Especially with HP LoadRunner >>>>>>>>>>>>>>>>>>>>>>
PowerVM and VMware. What this presentation is Basic Terms that can be used to discuss multiple forms of virtualization Concepts common to virtualization.
Measuring zSeries System Performance Dr. Chu J. Jong School of Information Technology Illinois State University 06/11/2012 Sponsored in part by Deer &
Network and Active Directory Performance Monitoring and Troubleshooting NETW4008 Lecture 8.
MCITP Administrator: Microsoft SQL Server 2005 Database Server Infrastructure Design Study Guide (70-443) Chapter 1: Designing the Hardware and Software.
Rensselaer Polytechnic Institute CSC 432 – Operating Systems David Goldschmidt, Ph.D.
Chapter 2: Designing Physical Storage MCITP Administrator: Microsoft SQL Server 2005 Database Server Infrastructure Design Study Guide (70-443)
How to Resolve Bottlenecks and Optimize your Virtual Environment Chris Chesley, Sr. Systems Engineer
Microsoft ® Official Course Module 10 Optimizing and Maintaining Windows ® 8 Client Computers.
Virtualization. Virtualization  In computing, virtualization is a broad term that refers to the abstraction of computer resources  It is "a technique.
Chapter 3: Operating-System Structures System Components Operating System Services System Calls System Programs System Structure Virtual Machines System.
EarthLink Server Management and Monitoring Updated August 6, 2015.
Chapter 8 Implementing Disaster Recovery and High Availability Hands-On Virtual Computing.
By Lecturer / Aisha Dawood 1.  Dedicated and Shared Server Processes  Configuring Oracle Database for Shared Server  Oracle Database Background Processes.
Guide to Linux Installation and Administration, 2e1 Chapter 10 Managing System Resources.
BW Know-How Call : Performance Tuning dial-in phone numbers! U.S. Toll-free: (877) International: (612) Passcode: “BW”
Module 10: Maintaining High-Availability. Overview Introduction to Availability Increasing Availability Using Failover Clustering Standby Servers and.
What is Sure Stats? Sure Stats is an add-on for SAP that provides Organizations with detailed Statistical Information about how their SAP system is being.
Operating System Principles And Multitasking
11 CLUSTERING AND AVAILABILITY Chapter 11. Chapter 11: CLUSTERING AND AVAILABILITY2 OVERVIEW  Describe the clustering capabilities of Microsoft Windows.
Chapter 13: LAN Maintenance. Documentation Document your LAN so that you have a record of equipment location and configuration. Documentation should include.
VMware vSphere Configuration and Management v6
Copyright 2007, Information Builders. Slide 1 Machine Sizing and Scalability Mark Nesson, Vashti Ragoonath June 2008.
Cloud Computing Lecture 5-6 Muhammad Ahmad Jan.
1 Chapter 9 Tuning Table Access. 2 Overview Improve performance of access to single table Explain access methods – Full Table Scan – Index – Partition-level.
Network management Network management refers to the activities, methods, procedures, and tools that pertain to the operation, administration, maintenance,
for all Hyperion video tutorial/Training/Certification/Material Essbase Optimization Techniques by Amit.
Cloud Computing – UNIT - II. VIRTUALIZATION Virtualization Hiding the reality The mantra of smart computing is to intelligently hide the reality Binary->
Virtual Machine Movement and Hyper-V Replica
VCS Building Blocks. Topic 1: Cluster Terminology After completing this topic, you will be able to define clustering terminology.
Capacity Planning in a Virtual Environment Chris Chesley, Sr. Systems Engineer
Software System Performance CS 560. Performance of computer systems In most computer systems:  The cost of people (development) is much greater than.
Deploying Highly Available SQL Server in Windows Azure A Presentation and Demonstration by Microsoft Cluster MVP David Bermingham.
If you have a transaction processing system, John Meisenbacher
Cofax Scalability Document Version Scaling Cofax in General The scalability of Cofax is directly related to the system software, hardware and network.
System Components Operating System Services System Calls.
Unix Server Consolidation
Workload Distribution Architecture
Services DFS, DHCP, and WINS are cluster-aware.
High Availability 24 hours a day, 7 days a week, 365 days a year…
Network Tools and Utilities
Hands-On Microsoft Windows Server 2008
Network Load Balancing
A Technical Overview of Microsoft® SQL Server™ 2005 High Availability Beta 2 Matthew Stephen IT Pro Evangelist (SQL Server)
Oracle Solaris Zones Study Purpose Only
Introduction of Week 6 Assignment Discussion
Networking for Home and Small Businesses – Chapter 2
Design Unit 26 Design a small or home office network
AlwaysOn Availability Groups
Cloud Computing Architecture
Networking for Home and Small Businesses – Chapter 2
Backup Monitoring – EMC NetWorker
Backup Monitoring – EMC NetWorker
Performance And Scalability In Oracle9i And SQL Server 2000
Presentation transcript:

Capacity Planning - Managing the hardware resources for your servers.

Capacity Planning  What is it? A method to insure that a given set of hardware is adequate for current and projected needs  Why is this important? Determine current hardware utilization Identify possible problems Identify available capacity for new projects Plan future hardware acquisitions Forecast how multiple packages will behave if co-hosted

What information is needed?  Network Capacity Relatively easily collected and analyzed –sysmon or Monitor tables and netstat  Disk IO Capacity Relatively easily collected and analyzed –sysmon or Monitor tables and iostat or SAR  Memory Usage Relatively easily collected and analyzed –sysmon or Monitor tables and vmstat  CPU Utilization Easily collected and Not easily analyzed –sysmon or Monitor tables and SAR

Why CPU Utilization?  Host CPU utilization statistics do not reflect actual use Includes time server spends spinning looking for work  Server Engine statistics do not reflect actual usage System usage required to service server request not included –Disk IO –Network IO

Host vs Server Statistics

Sybase Environment  Hardware Large verity of host Numerous host clusters Multiple data centers  Servers Varied usage, no two alike An ASE may serve 1 application or more than 50  Replication Used heavily for standard replication Increased use warm standby

Hardware Environment  3 Data Centers  57 Solaris Hosts Varied hardware –Over 10 Different Sun Models (several are domains) –4 Versions of OS 13 Veritas Clusters –3 Clusters of 4 or More Hosts –10 Clusters of 2 Hosts –SAN Disk Arrays 13 Standalone Hosts  2 HP Hosts

Sybase Environment  62 ASE Servers 45 Production –34 Running on Clustered Hosts –11 Running on Standalone Hosts –4 Warm Standby –8 are 3 rd party venders 16 Test –6 Running on Clustered Hosts –10 Running on Standalone Hosts 1 Test/Integration

Replication Environment  3 Replication Servers All on Clustered Hosts Standard replication –ASE to ASE –DB2 to ASE –ASE to DB2 4 Warm Standby

ASE Packages  ASE servers are installed in Veritas packages A “package” or “service group” can contain: –One or more file systems and mount points –Application processes –Sybase installation device –All disk devices –Dump devices for transaction logs A package has its own IP address (or virtual IP) and DNS entry and can be moved between the hosts of a cluster as needed Will automatically switch to another host upon any one of several types of system failures

Clustered Environment SAN A SAN B Host B Host A Host DHost C Data Center 1 Data Center 2 ASE

Goals of Project  Come up with a measurement that can be used to: Evaluate the current host utilization Identify problem server groupings Compare servers running on different host in some meaningful way Predict the effects of moving servers around within a cluster or to a new clusters Gauge the impact of host and data center failures Determine the effect of server failovers to warm standby servers Anticipate the hardware requirements of server expansion and increased use of warm standby servers

What Data Needs to be Collected  Location of servers Track movement of servers  Host SAR CPU statistics Sample size and timing to match server engine  Server engine statistics Sample size and timing to match host CPU

Tracking Server Movements  Servers can move from host to host for a number of reasons. Semi-annual package switch test Planed moves for hardware or OS maintenance Hardware or software failures To guarantee that the primary and secondary are not in the same data center Load balancing  Need to ensure that the calculations are using the correct server and host statistics

How is the Server Tracked?  Number of possible methods Agent on each host that would report and update the information Check the mounted file systems on each host Track the virtual IP to it’s current host  Record new host and the date and time the server moved from old host to new host  Side benefits Determine at where each server quickly Know when package was switched and from where

Host Map (Clustered)

Host Map (Clustered and Non-clustered)

What is a ‘Capacity Number’?  It is the statistical maximum of the total available host CPU capacity a server was using a specified hour on a specified day.  What does that mean? A ‘capacity number’ is calculated using the data for the past 3 months for each hour of the day for each day of the week. –24 capacity numbers per day –168 capacity numbers for a week Maximum for that hour, for that day – limited by statistics for the 3 month sample

Usage 24 Hour period

Calculating Capacity Number

How is the ‘Capacity Number’ Calculated?  Each night the ‘Capacity Numbers’ for the previous day are calculated for all the servers The allocation of host utilization is based on the number of engines configured for each server on the host and how active the server is. –(cpu_busy * engines) / sum (cpu_busy * engines) for all servers Second step is to adjust the allocation based on the number of server engines vs total CPUs. –Host CPU / Server engines or –Allocated CPU / Server engines

Calculating the ‘Capacity Number’  Host CPUs vs Allocated engines Host CPUs > Allocated engines (servers represent all activity) (pessimistic) 70 * allocation Host CPUs > Allocated engines (servers do not represent all activity) (optimistic) 70 * allocation * (Allocated engines / Host CPUs) Allocated engines > Host CPUs 70 * allocation

Calculating the ‘Capacity Number’ (Continue)  Calculate the range limits Calculate the median for all data points within the selected hour and.5 hours on both sides Ignore all data points below the median within above range Find the Standard Deviation of the remainder Find the maximum for the previous day for the selected hour –Maximum greater than mean + 2 * SD ‘Capacity Number’ = mean + 2 * SD –Maximum less than mean – 2 * SD ‘Capacity Number’ = mean - 2 * SD –Maximum within range ‘Capacity Number’ = Maximum

Data Retained Server_id Host_id – host the server was on during the period Range_min – minimum based on allocated engines activity Capacity_Number – based on allocated engines activity Range_max – maximum based on allocated engines activity Engines – configured for server CPU – for the host Allocated_engines – total allocated engines for all servers Total_min – minimum based on all CPU activity Total_Capacity_Number – based on all CPU acitivity Total_max – maximum based on all CPU activity

Host/Servers combination that in the past has exceeded max capacity

Optimistic Capacity (Engines < CPUs)

Pessimistic Capacity (Engines < CPUs)

Optimistic Capacity (Engines >= CPUs)

Pessimistic Capacity (Engines >= CPUs)

Things that Effect the Server When Comparing Capacity Number on 2 Different Host  Memory – Server memory static straight comparison  IO – Not considered to be significantly different  Network – Not considered to be significantly different  Number of CPU – Significant impact on performance Capacity number must be adjusted by a ratio based on the difference in number of CPUs  Processor speed – Significant impact on performance Each host is assigned a comparative factor based on processor speed Capacity number must be adjusted by a ratio based on the difference in comparative factors.

Calculating the ‘Relativity Index’ for a Server  Calculate the adjustment for CPU numbers. Number CPU on source / Number CPU on destination –Host a -> Host b 6 / 12 =.5 –Host b -> Host a 12 / 6 = 2  Calculate the adjustment for Processor Speed Comparison factor source / Comparison factor destination –Host a -> Host b.45 / 1.2 =.375 –Host b -> Host a 1.2 /.45 = 2.67  ‘Relativity Index’ for the two host CPU ratio * Speed Ratio –Host a -> Host b.5 *.45 =.1875 –Host b -> Host a 2 * 2.67 = 5.34

Predicting the Capacity when Rehosting Servers  Select a time period to be used a for comparison  Select destination host  Select servers that will be running on host  Select ‘Capacity Number’ data for selected servers  Calculate a ‘Relativity Index’ for each host pair (source, destination)  Adjust ‘Capacity Number’ by the ‘Relativity Index’ calculated for each server  Plot results

Using ‘Capacity Number’ and ‘Relativity Index’

Predicated Host Utilization

Optimistic Prediction

Host Utilization with Optimistic Prediction

Pessimistic Prediction

Host Utilization with Pessimistic Prediction