Collecting Perfstat Data

Before you can analyze performance data, you need to collect it properly during the time when performance issues are occurring. The perfstat utility must be downloaded from NetApp’s support site and executed with the correct parameters to gather meaningful data.

Perfstat Collection Command

# Basic perfstat collection command
perfstat -f [hostname] -t 5 -i 1,6 -l [username]:[password] > C:\perfstat.out

# Example with actual values
perfstat -f nas01.company.com -t 5 -i 1,6 -l admin:password123 > C:\perfstat.out

This command collects six 5-minute perfstat samples with 1-minute intervals between each collection. The parameters ensure comprehensive data collection:

• -f [hostname]: Target NetApp filer hostname or IP address
• -t 5: 5-minute collection interval (recommended by NetApp support)
• -i 1,6: 1-minute pause between 6 iterations
• -l [credentials]: Username and password for authentication

Analyzing CPU Performance

CPU bottlenecks can significantly impact storage system performance. The CPU Statistics section in perfstat provides detailed information about processor utilization and can help you determine if CPU constraints are affecting your storage operations.

Locating CPU Statistics

To find CPU performance data in your perfstat file, search for “CPU Statistics” using your text editor’s search function (Ctrl+F in most editors). Once located, look for the timestamp to understand when this sample was collected.

Key CPU Metrics to Monitor

The most critical metric in the CPU Statistics section is the idle time percentage. This indicates what percentage of time the CPU spends waiting for work, which inversely shows CPU utilization:

• High idle time (90-95%): CPU utilization is low (5-10%), no CPU bottleneck
• Medium idle time (70-80%): Moderate CPU usage (20-30%), monitor closely
• Low idle time (below 50%): High CPU utilization (above 50%), potential bottleneck

Analyzing Multiple CPU Samples

Since our collection command gathered 6 iterations, you’ll find 6 separate CPU Statistics sections in your perfstat file. Don’t rely on a single sample—examine all iterations to identify patterns:

• Consistent low idle time across multiple samples indicates a sustained CPU bottleneck
• Intermittent spikes suggest periodic high-load operations
• Generally high idle time rules out CPU as the performance culprit

Network Performance Analysis

Network bottlenecks are common in storage environments, especially when dealing with high-throughput applications. The Network Interface Statistics section provides comprehensive data about network utilization, errors, and performance characteristics.

Network Statistics Column Headers

Search for “Network Interface Statistics” in your perfstat file. The data is presented in columns with these headers:

Column	Description	What to Monitor
iface	Network interface name	Identify which adapter is being monitored
side	Traffic direction (send/receive)	Understand data flow patterns
bytes	Bytes per second	Primary throughput metric
packets	Packets per second	Packet rate and efficiency
errors	Error count	Should always be zero
collisions	Network collisions	Should be minimal or zero
pkt drops	Dropped packets	Critical error indicator

Critical Warning Signs

• Errors or packet drops > 0: Indicates network hardware problems or configuration issues
• High collision rates: Suggests network congestion or duplex mismatches
• Bytes/sec approaching interface limits: Network saturation warning

Network Capacity Planning

Understanding your hardware capabilities is crucial for interpreting network statistics:

• 1 Gbps ports: Theoretical maximum ~134,217,728 bytes/second
• 10 Gbps ports: Theoretical maximum ~1,342,177,280 bytes/second
• Virtual interfaces (VIF): Capacity depends on configuration (failover vs. load-balanced)

Disk Performance Analysis

Disk bottlenecks are the most common cause of performance issues in storage systems. The Disk Statistics section provides detailed IOPS and utilization metrics that help identify storage subsystem constraints and guide capacity planning decisions.

Disk Statistics Layout

Search for “Disk Statistics” in your perfstat file. The data is organized with column headers followed by aggregate information. Key columns include:

disk ut% xfers ureads-chain-usecs writes-chain-usecs cpreads-chain-usecs greads-chain-usecs gwrites-chain-usecs

Critical Metrics to Monitor

Focus on these two primary metrics for quick performance assessment:

• ut% (Utilization Percentage): Time the disk spends busy vs. idle
• xfers (Transfers/IOPS): Input/output operations per second

Disk Type Performance Characteristics

Disk Type	IOPS Capacity	Performance Threshold	Utilization Warning
SATA 7200 RPM	~40 IOPS	Performance degrades above 40 IOPS	Monitor when ut% > 50%
SAS 10K RPM	~140 IOPS	Performance degrades above 140 IOPS	Monitor when ut% > 50%
FC 15K RPM	~300 IOPS	Performance degrades above 300 IOPS	Monitor when ut% > 50%
SSD	Varies widely	Typically thousands of IOPS	Monitor when ut% > 70%

Aggregate-Level Analysis

Don’t focus on individual disk performance—analyze the aggregate as a whole. Individual disks with high utilization are normal in a properly functioning RAID group. Instead:

• Calculate average utilization across all disks in the aggregate
• Look for consistently high utilization across multiple disks
• Compare IOPS against the expected capacity for your disk type
• Correlate high utilization with user-reported performance issues

Perfstat Analysis Best Practices

Effective perfstat analysis requires a systematic approach and understanding of how different metrics correlate. Here are proven strategies for getting the most value from your performance data:

Systematic Analysis Approach

• Start with disk statistics: Most performance issues stem from storage bottlenecks
• Check network utilization: Verify if network capacity matches your storage throughput
• Examine CPU as last resort: CPU bottlenecks are less common in storage systems
• Correlate timestamps: Match perfstat data with user-reported problem timeframes
• Analyze trends: Look at all 6 iterations to identify patterns vs. anomalies

Tools and Environment

• Use a capable text editor: TextPad or similar tools that handle large files efficiently
• Leverage search functionality: Quickly navigate between different statistics sections
• Document your findings: Note baseline performance for future comparisons
• Multiple controller analysis: If you have an HA pair, analyze both controllers

Common Performance Scenarios

• High disk utilization + low network usage: Storage bottleneck confirmed
• Low disk utilization + high network saturation: Network bottleneck
• Low CPU idle time + normal disk/network: CPU bottleneck (rare)
• Errors in network statistics: Hardware or configuration issues

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