Key Metrics for Effective Storage Performance and

Capacity Reporting

Abstract

Doing capacity management for storage can be difficult with the many complex and varied technologies being used. Given all of the options available for data storage strategy, a clear understanding of the architecture is important in identifying performance and capacity concerns. A technician looking at metrics on a server is often seeing only the tip of a storage iceberg. Knowing which metrics are important will depend on your objectives and storage architecture, but response and space utilization will always be key to effectively managing storage.

Contents

• Storage Architecture

• Two distinct aspects of storage capacity

• Virtualization

• Key metrics from the host and backend storage view

• Reporting on what is most important

Space Capacity - History

Growth can result in increasing cost and complexity

Two Distinct Aspects of Storage Capacity and Performance

Storage Space

Storage Throughput

Response, IOPS

Space Capacity – Space Utilization

What does storage ‘Utilization’ mean in your environment?

Factors include: RAID/DR, Raw/Configured, Host/SAN, Backups, Compression, Etc...

Space Capacity – Proactive Visibility

Alarm on key metric trends instead of current threshold breaches to get in front of problems before they happen.

Trending, forecasting, and exceptions.

Space Capacity – Trending

Understand the limitations of linear regression when trending and forecasting data.

Chart above has high correlation

Chart below has low correlation

Space Capacity – Showing Different Viewpoints

Business, Application, Host, Storage Array, Billing Tier

Space Capacity – Host Metrics

Metrics are typically available at the file system, volume and logical disk views.

Key metrics for space capacity from the host perspective are typically:

• Storage allocated to system (disks)• Allocated but not configured (volumes)• Space used or free (file systems)

Space Capacity – Array Metrics

Storage arrays can have many space related metrics at different levels

NetApp Aggregate

Key metrics for space capacity from the array perspective depends on the technology and how it is being used. However, like the host view, total capacity and space available are key metrics:

• Storage installed in arrays (disks)• Configured but not allocated (aggregates)• Space used or free (volumes)

Virtual Environments and Clusters

• Thin provisioning

• Storage viewed at many levels

• Could be different tiers allocated to the same cluster

• Overhead at various points

Managing storage in clustered and/or virtual environment can be challenging because it is shared among all hosts and virtual machines running on it.

Image Source: VMware.com

Storage Virtualization

• Can be a centralized source for collecting data

Pooling physical storage from multiple sources into logical groupings

Wide variety of techniques for virtualizing storage, be aware of the implications for data collection and reporting

http://www.networkmagazineindia.com/200207/vendor.shtml

Performance Capacity – Response Impacts

SAN or storage array performance problems can be identified at the host or backend storage environment.

Response is the key metric for performance evaluation

• Host I/O response• Fabric or Network response• Virtualization device response• Array response

High response is typically caused by insufficient throughput capacity

Performance Capacity – Host Metrics

Understand the limitations of certain host metrics

• Measured response is the best metric for identifying trouble.

• Host utilization only shows busy time, it doesn’t give capacity for SAN.

• Physical I/O rate is an important measure of throughput, all disks have their limitation.

• Queue Length is a good indicator that a limitation has been reached somewhere.

Performance Capacity – Host Metrics

100% host disk utilization can indicate high throughput, but ample backend capacity might still be available, as was the case here.

Performance Capacity – Host Metrics

Queue lengths from the previous high utilization chart indicates that it may not currently be impacting response, but headroom is unknown.

Performance Capacity – Host Metrics

I/O generated from the previous high utilization chart is shown here, where combined throughput peaks are very high.

Performance Capacity – Host Metrics

Spikes in throughput typically correlate with queues and response for simple disk configurations, as seen in the chart, but most disk configurations are not simple anymore, which means these metrics often do not correlate.

Performance Capacity – Array Architecture

• Front End Processors

• Shared Cache

• Back End Processors

• Disk Storage

Performance Capacity – Array Metrics

Front end processors are typically the first to bottleneck. This chart shows acceptable utilization.

Performance Capacity – Array Metrics

05000100001500020000250003000035000400004500010/19/201210/20/201210/21/201210/22/2012EMC-000EMC-001EMC-002EMC-003EMC-004Intellimagic EMC Volume IO/secEMC-All Array IOPs

Find arrays doing the most work with throughput metrics.

Performance Capacity – Array Metrics

050001000015000200002500030000Least square fitMax IOPsIO/secIO/sec for EMC-000between: 20/10/2012 and 22/10/2012extrapolated until: 27/10/2012, 72 Raw Data pointsEMC-Array Total IOPs Trend

Aggregating and trending key metrics can be useful as shown here.

Performance Capacity – Array Metrics

0200040006000800010000120001400010/19/201210/20/201210/21/201210/22/2012EMC-000,rnk-0001,vol-00304EMC-000,rnk-0001,vol-00321EMC-001,rnk-0018,vol-03614EMC-001,rnk-0020,vol-03437EMC-001,rnk-0020,vol-04389EMC-003,rnk-0033,vol-08738EMC-003,rnk-0033,vol-08739EMC-003,rnk-0033,vol-08744EMC-004,rnk-0051,vol-10396EMC-004,rnk-0051,vol-10409Intellimagic EMC Volume IO/secEMC-Top 10 Volumes for All Array IOPs

Knowing what is generating the IOPS can also be important

Performance Capacity – Storage Virtualization Metrics

0500100015002000250030003500rnk-0217,vol-00926rnk-0218,vol-00678rnk-0218,vol-00691rnk-0218,vol-00974rnk-0229,vol-00451rnk-0229,vol-00578rnk-0229,vol-00648rnk-0229,vol-00757rnk-0229,vol-00910rnk-0229,vol-01082Intellimagic Volume,SVC-006 Total op/secIBM SVC Top 10 Volumes

Key metrics are also available from virtualization devices. This chart shows the top 10 IBM SVC volumes for throughput.

Performance Capacity – Storage Virtualization Metrics

010002000300040005000600070008000900010000Least square fit90% upper conf. limit90% lower conf. limitAlarmTotal op/secTotal op/sec for SVC-006,rnk-0229,vol-00451between: 18/10/2011 and 19/10/2011extrapolated until: 21/10/2011y = 2010x + 914, 97 Raw Data pointsIBM SVC Volume IOPs Trend

This is another example of aggregating and trending, although this particular SVC data sample is not a good real world example.

Performance Capacity – Storage Virtualization Metrics

Storage devices can have many performance metrics at different levels

Key metric for performance evaluation is response.

Other metrics are important too, but are typically used to avoid or troubleshoot high response times.

Performance Capacity – Array Metrics

NetApp

EMC

Response

Performance Capacity – Component Breakdown

Service time versus response time – different metrics

The bar chart shows service times as blue and green, with queue time represented as red and yellow.

Response is the combination of service and queue time.

IO Response

Performance Capacity – Workload Profiles

Application type is important in estimating performance risk

Performance Capacity – Scorecards and Exceptions

Performance Capacity – Dashboards

At a glance view of important metrics for critical resources

Storage Key Metrics – Conclusions

• Knowledge of your storage architecture is critical

• Understand both storage space and throughput

• Consider all factors that affect storage space utilization

• Be aware of virtualization and clustering complexities

• Know key metrics and their limitations

• Start with key report types and areas that are most important

Key Metrics for Effective Storage Performance and Capacity Reporting

Thank you for attending

The End