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TeamQuest Model
Accurately predict IT service performance with capacity planning software
TeamQuest Model is a capacity planning package that accurately predicts the resources required to support consistent service delivery at appropriate risk levels. TeamQuest Model is used to:
- Predict the resources required to meet service levels as demand increases
- Identify which components will negatively impact response time
- Find the least expensive way to accommodate workload increases
- Predict the performance impact of migrating from one operating system/hardware platform to another
As a member of the overall TeamQuest suite, TeamQuest Model can, of course, create baseline models using data collected by TeamQuest Performance Software. TeamQuest Model can also create baseline models using data collected by HP OpenView Performance Agents or HP OpenView Reporter. See our page regarding TeamQuest and HP for more information.
TeamQuest Model can utilize baseline performance data gathered by TeamQuest data collectors on these platforms:
- AIX on POWER
- HP-UX on Itanium and PA-RISC
- Red Hat Enterprise Linux on POWER, x86, x64, Itanium, zSeries
- Solaris on SPARC, x86 and x64
- SuSE Linux Enterprise Server on POWER, x86, x64, Itanium, zSeries
- Windows on x86, x64 and Itanium
- VMware ESX Server on x64 and x86
- z/OS on zSeries and i5/OS iSeries
In addition, TeamQuest Model can also use data gathered by HP OpenView Performance Agent.
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- CPU utilization
- I/O usage
- Workloads
- Hardware configurations
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TeamQuest Model uses analytic modeling capabilities to quickly and accurately predict the impact of changes without requiring you to configure any hardware or apply artificial loads. You can experiment with configuration changes, consolidation options, and demand levels to be sure you are allocating the right resources to meet business priorities.
You can predict response time from different components in a multi-tiered environment. TeamQuest Model also supports virtualized environments, including support for micro-partitioning and shared processor pools. Multithreaded environments that TeamQuest Model supports include:
- POWER5
- POWER6
- UltraSPARC T1
- UltraSPARC T2
- SPARC64 VI
- Intel Xeon and Pentium 4 platforms running Windows or Linux
- Itanium running HP-UX
You can identify underutilized resources for redeployment and meet service level agreements without wasting resources.
You can mitigate the risks of stacking applications on a single server by understanding the impact on services before you consolidate.
Product Features
Model a single system or multi-tiered applications
- Analyze your Web server, application server and database server all together
- See various systems as components of overall response time
- Focus on systems that are causing performance problems
- Define workloads that span multiple systems
- Experiment with adding servers to a tier for horizontal scaling
- Determine the effects of changes to memory, I/O devices, network bandwidth, and size or number of CPUs
- Predict the behavior of multithreaded environments and various partitioning configuration options
See the components of response time
- Analyze response time by business workload
- Uncover which devices are responsible for the largest portion of response time
- Determine what percentage of time is spent in the CPU or waiting for I/O devices
- Meet service-level objectives
Find and utilize wasted capacity
- Identify underutilized resources and redeploy for other services
- Get more out of existing resources
- Improve return on existing IT investments
Be ready for changes in demand
- Know in advance how systems will respond to unexpected bursts of activity
- Make sure systems are adequately configured for new applications
- Avoid outages and performance problems by planning ahead
- Understand which IT components are likely to be your weakest links
- Understand non-linear behavior that is missed by simpler trend analysis capacity planning techniques
Make informed capacity planning decisions
- Consolidate servers with confidence
- Manage the impact on servers for mergers and acquisitions
- Predict the impact of workload changes
- Upgrade just-in-time
- Objectively justify upgrades to management
- Predict the performance of various multithreaded environments
- Predict the performance impact of migrating from one operating system/hardware platform to another
- Ensure selected configurations will satisfy service levels while meeting cost and power consumption limitations
Predict performance by answering what-if questions
- What if I move this database file to a different disk subsystem?
- What if I upgrade my CPU? What if I lose one?
- What if one of my workloads increases by 10% a year over the next 5 years?
- What if we migrate to a different platform?
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