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Linux Performance Tuning

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Suse performance tuning

Performance Monitoring sar
Linux Virtual Memory Subsystem Tuning Oracle kernel parameters tuning on Linux Linux Kernel Tuning Disk subsystem tuning TCP performance tuning Semaphore and Shared Segment Kernel Parameters NFS performance tuning
uptime command vmstat iostat procstat sar nfsstat  
mostat iptraf netstat nmon LAMP Stack Prioritizing Disk Access with ionice strace
ptree ps top free lsof pmap  

Troubleshooting Linux Performance

Linux performance bottlenecks

Linux Swap filesystem

VMware Virtualization Humor Etc

Introduction

You should be very careful in your optimization attempts, always measure the results "before" and "after" and the main criteria is "not do any harm" rather then "achieve spectacular improvements".   Make a full backup of the system before introducing any significant optimization-related change. 

You should be very careful in your optimization attempts, always measure the results "before" and "after" and the main criteria is "not do any harm" rather then "to achieve spectacular improvements".

Remember:

The best performance first of all means avoiding blunders in installation and configuration. In a way it comes from the unnecessary work you don't do.

Much depends on the level of qualification of a particular DBA or system administrator.

The higher the level qualification is the more probably that actions taken will have positive, not negative effect.  

Excessive zeal is another danger. The key to database tuning is ability to objectively measure the performance. Good ideas without measurement of performance in optimization space are often turn to be useless or even bad ideas.

There is no free lunch and the more optimized system is, the more specialized for a particular application it became; as a result any changes in application can disproportionally affect performance. We can  categorized the effects of performance tuning (aka optimization)  in two categories: 

 Three major areas of optimization

There are three major areas of optimization:

  1. Hardware optimization (there is a big difference is io performce of a local subsystem which uses 15K RPM disks and dual channel controller 1 GB RAM cache with battery backup and 7200RPM disks with primitive controller. The most basic optimization is selection of the system that has higher transaction benchmark (TCP, for example TCP-C). Solid state disks can make dramatic improvement if the database is mainly used for reading. SAN are necessary for large databases (not only from performance standpoint, but also backup and recovery standpoint). 
  2. Operating system based optimization (generally requires careful measurements, for example using D-trace on Solaris)
  3. Application level optimization . Here the most dramatic improvements are possible; that's why open source applications can generally beat closed-source application; but understanding the application on the level that makes possible its tuning is often limited by the brainpower available; this is especially true  for complex, off-the-shelf applications)

As we go down the list we generally can get  higher returns on the efforts. But risks also generally increase. Also not all application are open source so application level optimization if often limited to the contains of the particular implementation.

The level of optimization available to the organization usually are dependent of the qualification of the staff. The higher the qualification of staff the more levels of optimization are available and the more is the potential return.  

The best performance specialists are good at what they do for two basic reasons:

One of the simplest performance monitoring  packages for linux is Sysstat which includes sar

Here are major areas for tuning (adapted from Server Oriented System Tuning Info ):

I/O and File System Tuning

Some of the default kernel parameters for system performance are geared more towards workstation performance that file server/large disk I/O type of operations.  For example, for pure file server applications like web and samba servers, you probably want to disable the "atime" option on the most used filesystem. This disabled updating the "atime" value for the file, which indicates that the last time a file was accessed. Since this info isn't very useful in this situation, and causes extra disk hits, its typically disabled. To do this, just edit /etc/fstab and add "notime" as a mount option for the filesystem.

For example:

/dev/rd/c0d0p3          /test                    ext2    noatime        1 2

The disk i/o elevators is another kernel tuneable that can be tweaked for improved disk i/o in some cases.

  1. For fast disk subsystems, it is desirable to use large flushes of dirty memory pages.  

    The value stored in /proc/sys/vm/dirty_background_ratio defines at what percentage of main memory the pdflush daemon should write data out to the disk.

    If larger flushes are desired then increasing the default value of 10% to a larger value will cause less frequent flushes.

    As in the example above the value can be changed to 25 as shown in

     # sysctl -w vm.dirty_background_ratio=25
     

  2. Another related setting in the virtual memory subsystem is the ratio at which dirty pages created by application disk writes will be flushed out to disk.

    The default value 10 means that data will be written into system memory until the file system cache has a size of 10% of the server’s RAM.

    The ratio at which dirty pages are written to disk can be altered as follows to a setting of 20% of the system memory

    # sysctl -w vm.dirty_ratio=20

 

Network Interface Tuning

See also TCP Performance Tuning

Most benchmarks benefit heavily from making sure the NIC's that you use has a good chipset and is well supported, with a well written driver. Examples include Intel NIC cards and Broadcom NIC cards. 

Making sure the cards are running in full duplex mode is also very often critical to benchmark performance. Depending on the networking hardware used, some of the cards may not autosense properly and may not run full duplex by default.

Many cards include module options that among other things can be used to force the cards into full duplex mode. Some examples for common cards include

alias eth0 eepro100
options eepro100 full_duplex=1
alias eth1 tulip
options tulip full_duplex=1

Though full duplex gives the best overall performance, I've seen some circumstances where setting the cards to half duplex will actually increase thoughput, particularly in cases where the data flow is heavily one sided.

For all other parameters, even if you think that your in a situation that change will improve performance, I would suggest benchmarking the results.  Many such changes recommended in the literature does not give desired effect or worse decrease performance. 

For servers that are serving up huge numbers of concurrent sessions, there are some TCP options that should probably be enabled. With a large # of clients doing their best to kill the server, its probably not uncommon for the server to have 20000 or more open sockets.

In order to optimize TCP performance for this situation, I would suggest tuning the following parameters.

echo 1024 65000 > /proc/sys/net/ipv4/ip_local_port_range
Allows more local ports to be available. Generally not a issue, but in a benchmarking scenario you often need more ports available. A common example is clients running `ab` or `http_load` or similar software.

In the case of firewalls, or other servers doing NAT or masquerading, you may not be able to use the full port range this way, because of the need for high ports for use in NAT.

Increasing the amount of memory associated with socket buffers can often improve performance. Things like NFS in particular, or apache setups with large buffer configured can benefit from this.

echo 262143 > /proc/sys/net/core/rmem_max
echo 262143 > /proc/sys/net/core/rmem_default
This will increase the amount of memory available for socket input queues. The "wmem_*" values do the same for output queues.

Note: With 2.4.x kernels, these values are supposed to "autotune" fairly well, and some people suggest just instead changing the values in:

/proc/sys/net/ipv4/tcp_rmem
/proc/sys/net/ipv4/tcp_wmem
There are three values here, "min default max".

These reduce the amount of work the TCP stack has to do, so is often helpful in this situation.

echo 0 > /proc/sys/net/ipv4/tcp_sack
echo 0 > /proc/sys/net/ipv4/tcp_timestamps 

SCSI Tuning

SCSI tuning is highly dependent on the particular scsi cards and drives in questions. The most effective variable when it comes to SCSI card performance is tagged command queuing.

You probably want to check the driver documentation for your particular scsi modules for more info.

For example, the Adaptec aic7xxx series cards (2940's, 7890's, *160's, etc) this can be enabled with a module option like:

	aic7xx=tag_info:{{0,0,0,0,}}

This enabled the default tagged command queuing on the first device, on the first 4 scsi ids.

	options aic7xxxaic7xxx=tag_info:{{24.24.24.24.24.24}}
in /etc/modules.conf will set the TCQ depth to 24

NFS Tuning

See also  NFS performance tuning

But the basic tuning steps include:

Try using NFSv3 if you are currently using NFSv2. There can be very significant performance increases with this change.

Increasing the read write block size. This is done with the rsize and wsize mount options. They need to the mount options used by the NFS clients. Values of 4096 and 8192 reportedly increase performance. But see the notes in the HOWTO about experimenting and measuring the performance implications. The limits on these are 8192 for NFSv2 and 32768 for NFSv3

Another approach is to increase the number of nfsd threads running. This is normally controlled by the nfsd init script. On Red Hat Linux machines, the value "RPCNFSDCOUNT" in the nfs init script controls this value. The best way to determine if you need this is to experiment. The HOWTO mentions a way to determine thread usage, but that doesn't seem supported in all kernels.

Another good tool for getting some handle on NFS server performance is `nfsstat`. This util reads the info in /proc/net/rpc/nfs[d] and displays it in a somewhat readable format. Some info intended for tuning Solaris, but useful for it's description of the nfsstat format

See also the tcp tuning info

Apache configuration

Make sure you starting several initial daemons if you want good benchmark scores.

Something like:

#######
MinSpareServers 20
MaxSpareServers 80
StartServers 32

# this can be higher if apache is recompiled
MaxClients 256

MaxRequestsPerChild 10000
        
Note: Starting a massive amount of httpd processes is really a benchmark hack. In most real world cases, setting a high number for max servers, and a sane spare server setting will be more than adequate. It's just the instant on load that benchmarks typically generate that the StartServers helps with.

The MaxRequestPerChild should be bumped up if you are sure that your httpd processes do not leak memory. Setting this value to 0 will cause the processes to never reach a limit.

One of the best resources on tuning these values, especially for app servers, is the mod_perl performance tuning documentation.

Bumping the number of available httpd processes

Apache sets a maximum number of possible processes at compile time. It is set to 256 by default, but in this kind of scenario, can often be exceeded.

To change this, you will need to change the hardcoded limit in the apache source code, and recompile it. An example of the change is below:

--- apache_1.3.6/src/include/httpd.h.prezab     Fri Aug  6 20:11:14 1999
+++ apache_1.3.6/src/include/httpd.h    Fri Aug  6 20:12:50 1999
@@ -306,7 +306,7 @@
  * the overhead.
  */
 #ifndef HARD_SERVER_LIMIT
-#define HARD_SERVER_LIMIT 256
+#define HARD_SERVER_LIMIT 4000
 #endif

 /*

To make usage of this many apache's however, you will also need to boost the number of processes support, at least for 2.2 kernels. See the section on kernel process limits for info on increasing this.

The biggest scalability problem with apache, 1.3.x versions at least, is it's model of using one process per connection. In cases where there large amounts of concurrent connections, this can require a large amount resources. These resources can include RAM, scheduler slots, ability to grab locks, database connections, file descriptors, and others.

In cases where each connection takes a long time to complete, this is only compunded. Connections can be slow to complete because of large amounts of cpu or i/o usage in dynamic apps, large files being transferred, or just talking to clients on slow links.

There are several strategies to mitigate this. The basic idea being to free up heavyweight apache processes from having to handle slow to complete connections.

Static Content Servers

If the servers are serving lots of static files (images, videos, pdf's, etc), a common approach is to serve these files off a dedicated server. This could be a very light apache setup, or any many cases, something like thttpd, boa, khttpd, or TUX. In some cases it is possible to run the static server on the same server, addressed via a different hostname.

For purely static content, some of the other smaller more lightweight web servers can offer very good performance. They arent nearly as powerful or as flexible as apache, but for very specific performance crucial tasks, they can be a big win.

Boa: http://www.boa.org/
thttpd: http://www.acme.com/software/thttpd/
mathopd: http://mathop.diva.nl/
 

If you need even more ExtremeWebServerPerformance, you probabaly want to take a look at TUX, written by Ingo Molnar. This is the current world record holder for SpecWeb99. It probabaly owns the right to be called the worlds fastest web server.

Proxy Usage For servers that are serving dynamic content, or ssl content, a better approach is to employ a reverse-proxy. Typically, this would done with either apache's mod_proxy, or Squid. There can be several advantages from this type of configuration, including content caching, load balancing, and the prospect of moving slow connections to lighter weight servers.

The easiest approache is probabaly to use mod_proxy and the "ProxyPass" directive to pass content to another server. mod_proxy supports a degree of caching that can offer a significant performance boost. But another advantage is that since the proxy server and the web server are likely to have a very fast interconnect, the web server can quickly serve up large content, freeing up a apache process, why the proxy slowly feeds out the content to clients. This can be further enhanced by increasing the amount of socket buffer memory thats for the kernel. See the section on tcp tuning for info on this.

proxy links

ListenBacklog

One of the most frustrating thing for a user of a website, is to get "connection refused" error messages. With apache, the common cause of this is for the number of concurent connections to exceed the number of available httpd processes that are available to handle connections.

The apache ListenBacklog paramater lets you specify what backlog paramater is set to listen(). By default on linux, this can be as high as 128.

Increasing this allows a limited number of httpd's to handle a burst of attempted connections.

There are some experimental patches from SGI that accelerate apache. More info at:

http://oss.sgi.com/projects/apache/

I havent really had a chance to test the SGI patches yet, but I've been told they are pretty effective.

Samba Tuning

Depending on the type of tests, there are a number of tweaks you can do to samba to improve its performace over the default. The default is best for general purpose file sharing, but for extreme uses, there are a couple of tweaks.

The first one is to rebuild it with mmap support. In cases where you are serving up a large amount of small files, this seems to be particularly useful. You just need to add a "--with-mmap" to the configure line.

You also want to make sure the following options are enabled in the /etc/smb.conf file:

read raw = no
read prediction = true
level2 oplocks = true

One of the better resources for tuning samba is the "Using Samba" book from O'reily. The  chapter on performance tuning is available online.

Openldap tuning

The most important tuning aspect for OpenLDAP is deciding what attributes you want to build indexes on.

I use the values:

cachesize 10000
dbcachesize 100000
sizelimit 10000
loglevel 0
dbcacheNoWsync

index cn,uid
index uidnumber
index gid
index gidnumber
index mail

If you add the following parameters to /etc/openldap/slapd.conf before entering the info into the database, they will all get indexed and performance will increase.

 SysV shm

Some applications, databases in particular, sometimes need large amounts of SHM segments and semaphores. This tuning is well explained in Oracle documentation.

Benchmarks

Lies, damn lies, and statistics.

But aside from that, a good set of benchmarking utilities are often very helpful in doing system tuning work. It is impossible to duplicate "real world" situations, but that isnt really the goal of a good benchmark. A good benchmark typically tries to measure the performance of one particular thing very accurately. If you understand what the benchmarks are doing, they can be very useful tools.

Some of the common and useful benchmarks include:

General benchmark Sites

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NEWS CONTENTS

Old News ;-)

[Mar 08, 2013] SUSE Linux Enterprise Server System Analysis and Tuning Guide

Jun 25, 2012

Copyright © 2006–2012 Novell, Inc. and contributors. All rights reserved.

Over the past few years, Linux has made its way into the data centers of many corporations all over the globe. The Linux operating system has become accepted by both the scientific and enterprise user population. Today, Linux is by far the most versatile operating system. You can find Linux on embedded devices such as firewalls and cell phones and mainframes. Naturally, performance of the Linux operating system has become a hot topic for both scientific and enterprise users. However, calculating a global weather forecast and hosting a database impose different requirements on the operating system. Linux has to accommodate all possible usage scenarios with the most optimal performance. The consequence of this challenge is that most Linux distributions contain general tuning parameters to accommodate all users.

IBM® has embraced Linux, and it is recognized as an operating system suitable for enterprise-level applications running on IBM systems. Most enterprise applications are now available on Linux, including file and print servers, database servers, Web servers, and collaboration and mail servers.

With use of Linux in an enterprise-class server comes the need to monitor performance and, when necessary, tune the server to remove bottSUSE Linux Enterprise Server is used for a broad range of usage scenarios in enterprise and scientific data centers. SUSE has ensured SUSE Linux Enterprise Server is set up in a way that it accommodates different operation purposes with optimal performance. However, SUSE Linux Enterprise Server must meet very different demands when employed on a number crunching server compared to a file server, for example.

Generally it is not possible to ship a distribution that will by default be optimized for all kinds of workloads. Due to the simple fact that different workloads vary substantially in various aspects-most importantly I/O access patterns, memory access patterns, and process scheduling. A behavior that perfectly suits a certain workload might t reduce performance of a completely different workload (for example, I/O intensive databases usually have completely different requirements compared to CPU-intensive tasks, such as video encoding). The great versatility of Linux makes it possible to configure your system in a way that it brings out the best in each usage scenario.

This manual introduces you to means to monitor and analyze your system. It describes methods to manage system resources and to tune your system. This guide does not offer recipes for special scenarios, because each server has got its own different demands. It rather enables you to thoroughly analyze your servers and make the most out of them.

General Notes on System Tuning
Tuning a system requires a carefully planned proceeding. Learn which steps are necessary to successfully improve your system.

Part II, "System Monitoring"
Linux offers a large variety of tools to monitor almost every aspect of the system. Learn how to use these utilities and how to read and analyze the system log files.

Part III, "Kernel Monitoring"
The Linux kernel itself offers means to examine every nut, bolt and screw of the system. This part introduces you to SystemTap, a scripting language for writing kernel modules that can be used to analyze and filter data. Collect debugging information and find bottlenecks by using kernel probes and use perfmon2 to access the CPU's performance monitoring unit. Last, monitor applications with the help of Oprofile.

Part IV, "Resource Management"
Learn how to set up a tailor-made system fitting exactly the server's need. Get to know how to use power management while at the same time keeping the performance of a system at a level that matches the current requirements.

Part V, "Kernel Tuning"
The Linux kernel can be optimized either by using sysctl or via the /proc file system. This part covers tuning the I/O performance and optimizing the way how Linux schedules processes. It also describes basic principles of memory management and shows how memory management could be fine-tuned to suit needs of specific applications and usage patterns. Furthermore, it describes how to optimize network performance.

Part VI, "Handling System Dumps"
This part enables you to analyze and handle application or system crashes. It introduces tracing tools such as strace or ltrace and describes how to handle system crashes using Kexec and Kdump.
lenecks that affect users. This IBM Redpaper describes the methods you can use to tune Linux, tools that you can use to monitor and analyze server performance, and key tuning parameters for specific server applications. The purpose of this redpaper is to understand, analyze, and tune the Linux operating system to yield superior performance for any type of application you plan to run on these systems.

The tuning parameters, benchmark results, and monitoring tools used in our test environment were executed on Red Hat and Novell SUSE Linux kernel 2.6 systems running on IBM System x servers and IBM System z servers. However, the information in this redpaper should be helpful for all Linux hardware platforms.

[Aug 09, 2011] Creating a Linux ramdisk

While performing some testing a few weeks ago, I needed to create a ramdisk on one of my redhat AS 4.0 servers. I knew Solaris supported tmpfs, and after a bit of googling was surprised to find that Linux supported the tmpfs pseudo-file system as well. To create a ramdisk on a Linux host, you first need to find a suitable place to mount the tmpfs file system. For my tests, I used mkdir to create a directory valled /var/ramdisk:

$ mkdir /var/ramdisk

Once the mount point is identified, you can use the mount command to mount a tmpfs file system on top of that mount point:

$ mount -t tmpfs none /var/ramdisk -o size=28m

Now each time you access /var/ramdisk, your reads and writes will be coming directly from memory. Nice!

[Jun 23, 2011] likwid

freshmeat.net

Likwid is a set of easy to use command line tools for Linux. It supports programmers in developing high performance multi-threaded programs. "Likwid" stands for "Like I knew what I am doing". It contains the following tools: likwid-topology, which shows thread and cache topology; likwid-perfCtr, which measures hardware performance counters on Intel and AMD processors; likwid-features, which shows and toggles hardware prefetch control bits on Intel Core 2 processors; likwid-pin, which pins a threaded application without touching its code (it supports pthreads, Intel OpenMP, and gcc OpenMP), and likwid-bench, a low level benchmarking framework.

It works with any standard Linux kernel. Likwid is lightweight and adds no overhead during measurements.

[May 31, 2011] RHEL Tuning and Optimization for Oracle V11

The Completely Fair Queuing (CFQ) scheduler is the default algorithm in Red Hat Enterprise Linux 4 which is suitable for a wide variety of applications and provides a good compromise between throughput and latency. In comparison to the CFQ algorithm, the Deadline scheduler caps maximum latency per request and maintains a good disk throughput which is best for disk-intensive database applications.

Hence, the Deadline scheduler is recommended for database systems. Also, at the time of this writing there is a bug in the CFQ scheduler which affects heavy I/O, see Metalink Bug:5041764. Even though this bug report talks about OCFS2 testing, this bug can also happen during heavy IO access to raw or block devices and as a consequence could evict RAC nodes.

To switch to the Deadline scheduler, the boot parameter elevator=deadline must be passed to the kernel that is being used.

Edit the /etc/grub.conf file and add the following parameter to the kernel that is being used, in this example 2.4.21-32.0.1.ELhugemem:

title Red Hat Enterprise Linux Server (2.6.18-8.el5)
root (hd0,0)
kernel /vmlinuz-2.6.18-8.el5 ro root=/dev/sda2 elevator=deadline initrd /initrd-2.6.18-8.el5.img

This entry tells the 2.6.18-8.el5 kernel to use the Deadline scheduler. Make sure to reboot the system to activate the new scheduler.

Changing Network Adapter Settings

To check the speed and settings of network adapters, use the ethtool command which works now

for most network interface cards. To check the adapter settings of eth0 run:

# ethtool eth0

To force a speed change to 1000Mbps, full duplex mode, run:

# ethtool -s eth0 speed 1000 duplex full autoneg off

To make a speed change permanent for eth0, set or add the ETHTOOL_OPT environment variable in

/etc/sysconfig/network-scripts/ifcfg-eth0:

ETHTOOL_OPTS="speed 1000 duplex full autoneg off"

This environment variable is sourced in by the network scripts each time the network service is

started.

Changing Network Kernel Settings

Oracle now uses User Datagram Protocol (UDP) as the default protocol on Linux for interprocess

communication, such as cache fusion buffer transfers between the instances. However, starting with

Oracle 10g network settings should be adjusted for standalone databases as well.

Oracle recommends the default and maximum send buffer size (SO_SNDBUF socket option) and

receive buffer size (SO_RCVBUF socket option) to be set to 256 KB. The receive buffers are used

by TCP and UDP to hold received data until it is read by the application. The receive buffer cannot

overflow because the peer is not allowed to send data beyond the buffer size window. This means that

datagrams will be discarded if they do not fit in the socket receive buffer. This could cause the sender

to overwhelm the receiver.

The default and maximum window size can be changed in the proc file system without reboot:

The default setting in bytes of the socket receive buffer

# sysctl -w net.core.rmem_default=262144

The default setting in bytes of the socket send buffer

# sysctl -w net.core.wmem_default=262144

The maximum socket receive buffer size which may be set by using the SO_RCVBUF socket option

# sysctl -w net.core.rmem_max=262144

The maximum socket send buffer size which may be set by using the SO_SNDBUF socket option

# sysctl -w net.core.wmem_max=262144

To make the change permanent, add the following lines to the /etc/sysctl.conf file, which is used

during the boot process:

net.core.rmem_default=262144

net.core.wmem_default=262144

net.core.rmem_max=262144

net.core.wmem_max=262144

To improve fail over performance in a RAC cluster, consider changing the following IP kernel

parameters as well:

net.ipv4.tcp_keepalive_time

net.ipv4.tcp_keepalive_intvl

net.ipv4.tcp_retries2

net.ipv4.tcp_syn_retries

Changing these settings may be highly dependent on your system, network, and other applications.

For suggestions, see Metalink Note:249213.1 and Note:265194.1.

On Red Hat Enterprise Linux systems the default range of IP port numbers that are allowed for TCP

and UDP traffic on the server is too low for 9i and 10g systems. Oracle recommends the following port

range:

# sysctl -w net.ipv4.ip_local_port_range="1024 65000"

To make the change permanent, add the following line to the /etc/sysctl.conf file, which is used during

the boot process:

net.ipv4.ip_local_port_range=1024 65000

The first number is the first local port allowed for TCP and UDP traffic, and the second number is the last port number.

10.3. Flow Control for e1000 Network Interface Cards

The e1000 network interface card family do not have flow control enabled in the 2.6 kernel on Red Hat

Enterprise Linux 4 and 5. If you have heavy traffic, then the RAC interconnects may lose blocks, see

Metalink Bug:5058952. For more information on flow control, see Wikipedia Flow control1.

To enable Receive flow control for e1000 network interface cards, add the following line to the /etc/

modprobe.conf file:

options e1000 FlowControl=1

The e1000 module needs to be reloaded for the change to take effect. Once the module is loaded with

flow control, you should see e1000 flow control module messages in /var/log/messages.

Verifying Asynchronous I/O Usage

To verify whether $ORACLE_HOME/bin/oracle was linked with asynchronous I/O, you can use the

Linux commands ldd and nm.

In the following example, $ORACLE_HOME/bin/oracle was relinked with asynchronous I/O:

$ ldd $ORACLE_HOME/bin/oracle | grep libaio

libaio.so.1 => /usr/lib/libaio.so.1 (0x0093d000)

$ nm $ORACLE_HOME/bin/oracle | grep io_getevent

w io_getevents@@LIBAIO_0.1

$

In the following example, $ORACLE_HOME/bin/oracle has NOT been relinked with asynchronous I/

O:

$ ldd $ORACLE_HOME/bin/oracle | grep libaio

$ nm $ORACLE_HOME/bin/oracle | grep io_getevent

w io_getevents

$

If $ORACLE_HOME/bin/oracle is relinked with asynchronous I/O it does not necessarily mean that

Oracle is really using it. You also have to ensure that Oracle is configured to use asynchronous I/O

calls, see Enabling Asynchronous I/O Support.

To verify whether Oracle is making asynchronous I/O calls, you can take a look at the /proc/

slabinfo file assuming there are no other applications performing asynchronous I/O calls on the

system. This file shows kernel slab cache information in real time.

On a Red Hat Enterprise Linux 3 system where Oracle does not make asynchronous I/O calls, the

output looks like this:

$ egrep "kioctx|kiocb" /proc/slabinfo

kioctx 0 0 128 0 0 1 : 1008 252

kiocb 0 0 128 0 0 1 : 1008 252

$

Once Oracle makes asynchronous I/O calls, the output on a Red Hat Enterprise Linux 3 system will

look like this:

$ egrep "kioctx|kiocb" /proc/slabinfo

kioctx 690 690 128 23 23 1 : 1008 252

kiocb 58446 65160 128 1971 2172 1 : 1008 252

[Jan 26, 2011] Monitor Linux file system events with inotify

Use inotify when you need efficient, fine-grained, asynchronous monitoring of Linux file system events. Use it for user-space monitoring for security, performance, or other purposes. (On 10 September 2010, the downloadable sample code for this article was refreshed to correct a typo. - Ed.)

[Jan 26, 2011] Tuning LAMP systems, Part 1: Understanding the LAMP architecture

Applications using the LAMP (Linux, Apache, MySQL, PHP/Perl) architecture are constantly being developed and deployed. But often the server administrator has little control over the application itself because it's written by someone else. This series of three articles discusses many of the server configuration items that can make or break an application's performance. This first article covers the LAMP architecture, some measurement techniques, and some basic Linux kernel, disk, and file system tweaks. Successive articles investigate tuning the Apache, MySQL, and PHP components. Applications using the LAMP (Linux, Apache, MySQL, PHP/Perl) architecture are constantly being developed and deployed. But often the server administrator has little control over the application itself because it's written by someone else. This series of three articles discusses many of the server configuration items that can make or break an application's performance. This second article focuses on steps you can take to optimize Apache and PHP.

[Jan 26, 2011] Tuning LAMP systems, Part 3: Tuning your MySQL server

Applications using the LAMP (Linux, Apache, MySQL, PHP/Perl) architecture are constantly being developed and deployed. But often the server administrator has little control over the application itself because it's written by someone else. This series of three articles discusses many of the server configuration items that can make or break an application's performance. This third article, the last in the series, focuses on tuning the database layer for maximum efficiency.

[Jan 26, 2011] Five simple ways to tune your LAMP application by John Mertic, Software Engineer, SugarCRM

Summary: The Linux, Apache, MySQL, and PHP (LAMP) architecture is one of the most popular choices for web server architectures in use today. Author John Mertic examines five things every LAMP application should take advantage of for optimum performance.

[Nov 30, 2010] Life As A Sys Admin Best Networking Tweaks for Linux By Michael Adams

Nov 29, 2010 | Network World

A Linux system can be tweaked to a degree Windows users may envy (or fear) especially for networking. Tweaking a Linux box for networking is a bit more mundane than other platforms: there are specific driver settings one can work with but its best flexibility comes from a mix of OS-level modifications and adherence to different RFCs.

ifconfig (interface) txqueuelen #

Software buffers for network adapters on Linux start off at a conservative 1000 packets. Network researchers and scientists have mucked around with this, and figured out that we should be using 10,000 for anything decent on a LAN; more if you're running GB or 10GE stuff. Slow interfaces, such as modems and WAN links, can default to 0-100, but don't be afraid to bump it up towards 1000 and see if your performance improves. Bumping up this setting does use memory, so be careful if you're using an embedded router or something (I've used 10,000 on 16MB RAM OpenWRT units, no prob).

You can edit /etc/rc.local, add an "up" command to /etc/networking/interfaces, or whatever your distribution suggests and it's best to put a command like this at startup.

/etc/sysctl.conf

This file governs default behavior for many network and file operation settings on Linux and other *nix-based systems. If you deploy Ubuntu or Fedora systems, you'll notice they will add their own tweaks (usually security or file-oriented) to the file: don't delete those, unless you read up on them, or see any that are contradicted by the suggested additions here...

net.ipv4.tcp_rfc1337=1
net.ipv4.tcp_window_scaling=1
net.ipv4.tcp_workaround_signed_windows=1
net.ipv4.tcp_sack=1
net.ipv4.tcp_fack=1
net.ipv4.tcp_low_latency=1
net.ipv4.ip_no_pmtu_disc=0
net.ipv4.tcp_mtu_probing=1
net.ipv4.tcp_frto=2
net.ipv4.tcp_frto_response=2
net.ipv4.tcp_congestion_control=illinois

1. RFC 1337, TIME-WAIT Assassination Hazards in TCP, a fix written in 1992 for some theoretically-possible failure modes for TCP connections. To this day this RFC still has people confused if it negatively impacts performance or not or is supported by any decent router. Murphy's Law is that the only router that it would even have trouble with, is most likely your own.

2. TCP window scaling tries to avoid getting the network adapter saturated with incoming packets.

3. TCP SACK and FACK refer to options found in RFC 2018 and are also documented back to Linux Kernel 2.6.17 with an experimental "TCP-Peach" set of functions. These are meant to get you your data without excessive losses.

4. The latency setting is 1 if you prefer more packets vs bandwidth, or 0 if you prefer bandwidth. More packets are ideal for things like Remote Desktop and VOIP: less for bulk downloading.

5. I found RFC 2923, which is a good review of PMTU. IPv6 uses PMTU by default to avoid segmenting packets at the router level, but its optional for IPv4. PMTU is meant to inform routers of the best packet sizes to use between links, but its a common admin practice to block ICMP ports that allow pinging, thus breaking this mechanism. Linux tries to use it, and so do I: if you have problems, you have a problem router, and can change the "no" setting to 1. "MTU probing" is also a part of this: 1 means try, and 0 means don't.

6. FRTO is a mechanism in newer Linux kernels to optimize for wireless hosts: use it if you have them; delete the setting, or set to 0, if you don't.

For further study, there's a great IBM article regarding network optimizations: it was my source for some of these settings, as well as following numerous articles on tweaking Linux networking over the years (SpeedGuide has one from 2003).

TCP Congestion Controls

Windows Vista and newer gained Compound TCP as an alternative to standard TCP Reno. Linux Kernel 2.6 has had numerous mechanisms available to it for some time: 2.6.19 defaulted to CUBIC which was supposed to work well over "long links." My two personal favorites: TCP Westwood + and TCP Illinois. But you can dig in, look at different research papers online, and see what works best for your environment.

1. Make sure your kernel has the correct module: in my example, I use TCP Illinois, which has been compiled with any standard Ubuntu kernel since 2008, and is found as tcp_illinois.

2. Add said kernel module to /etc/modules

3. Change /etc/sysctl.conf to use the non "tcp_" part of your selection.

There you have it -- some of my favorite Linux tweaks for networking. I'm interested in hearing how these worked for you. If you have some of your own, please post a comment and share them with other readers.

[Aug 18, 2010] The Top 12 Native Linux System Monitoring Tools

htop might be a better top alternative, I would also add nmon?

thewebhostingdi

Pmap - - Process Memory Usage

The command pmap report memory map of a process. Use this command to find out causes of memory bottlenecks.

# pmap -d PID

Iptraf - Real-time Network Statistics

Features of Iptraf are

Network traffic statistics by TCP connection
IP traffic statistics by network interface
Network traffic statistics by protocol
Network traffic statistics by TCP/UDP port and by packet size
Network traffic statistics by Layer2 address

[Apr 07, 2010] nmon for Linux Main - HomePage

This is a tool that came from AIX courtesy of IBM. IMHO nothing special in comparison with vmstat and top. For the description see nmon performance- A free tool to analyze AIX and Linux ...

nmon is short for Nigel's performance MONitor for Linux

This systems administrator, tuner, benchmark tool gives you a huge amount of important performance information in one go. It can output the data in two ways

  1. On screen (console, telnet, VNC, putty or X Windows) using curses for low CPU impact which is updated once every two seconds. You hit single characters on you keyboard to enable/disable the various sorts of data.
    • You can display the CPU, memory, network, disks (mini graphs or numbers), file systems, NFS, top processes, resources (Linux version & processors) and on Power micro-partition information.
    • For lots of examples, see the "Screen shots" from the left menu.
    • As you can see on the left lmon12e now in colour
  2. Save the data to a comma separated file for analysis and longer term data capture.
    • Use this together with nmon Analyser Excel 2000 spreadsheet, which loads the nmon output file and automatically creates dozens of graphs ready for you to study or write performance reports.
    • Filter this data, add it to a rrd database (using an excellent freely available utility called rrdtool). This graphs the data to .gif or .png files plus generates the webpage .html file and you can then put the graphs directly on a website automatically on AIX with no need of a Windows based machine.
    • Directly put the data into a rrd database or other database for your own analysis

[Mar 14, 2010] UNIX Performance Management By Jaqui Lynch (Boston College)

The purpose of this paper is to introduce the performance analyst to some of the free tools available to monitor and manage performance on UNIX systems, and to provide a guideline on how to diagnose and fix performance problems in that environment. The paper is based on the authors experiences with AIX and will cover many of the tools available on that and other UNIX platforms. It will also provide some Rules of Thumb for analyzing the performance of UNIX systems.

As more mission critical work finds its way from the mainframe to distributed systems, performance management for those systems is becoming more important. The goal for systems management is not only to maximize system throughput, but also to reduce response time. In order to this it is necessary to not only work on the system resources, but also to work on profiling and tuning applications.

In UNIX there are 7 major resource types that need to be monitored and tuned - CPU, memory, disk space and arms, communications lines, I/O Time, Network Time and applications programs. There are also standard rules of thumb in most of these areas. From the users perspective the only one they see is total execution time so we will start by looking at that.

Total execution time from a users perspective consists of wall-clock time. At a process level this is measured by running the time command. This provides you with real time (wallclock), user code CPU and system code CPU. If user + sys > 80% then there is a good chance the system is CPU constrained. The components of total running time include:

1. User-state CPU - the actual amount of time the CPU spends running the users program in the user state. It includes time spent executing library calls, but does not include time spent in the kernel on its behalf. This value can be greatly affected by the use of optimization at compile time and by writing efficient code.

2. System-state CPU - this is the amount of time the CPU spends in the system state on behalf of this program. All I/O routines require kernel services. The programmer can affect this value by the use of blocking for I/O transfers.

3. I/O Time and Network Time - these are the amount of time spent moving data and servicing I/O requests.

4. Virtual Memory Performance - This includes context switching and swapping.

5. Time spent running other programs.

In order to measure these areas there are a multitude of tools available. The most useful are:

Other commands that will be useful include lsvg, lspv, lslv, lsps and lsdev. Each of these will be discussed below and then a general problem solving approach will be offered. It is important to note that the results and options for all of these commands may differ depending on the platform they are being run on. Most of the options discussed below are those for AIX and some of the tools are specific to AIX such as:

The first tool to be discussed is uptime. This provides the analyst with the System Load Average (SLA). It is important to note that the SLA can only be used as a rough indicator as it does not take into account scheduling priority and it counts as runnable all jobs waiting for disk I/O, including NFS I/O. However, uptime is a good place to start when trying to determine whether a bottleneck is CPU or I/O based.

When uptime is run it provides three load averages - the first is for the last minute, the second is for the last 5 minutes and the third is for the last 15 minutes. If the value is borderline but has been falling over the last 15 minutes, then it would be wise to just monitor the situation. However, a value between 4 and 7 is fairly heavy and means that performance is being negatively affected. Above 7 means the system needs serious review and below 3 means the workload is relatively light. If the system is a single user workstation then the load average should be less than 2. There is also a command called ruptime that allows you to request uptime information remotely.

The sar command provides a good alternative to uptime with the -q option. It provides statistics on the average length of the run queue, the percentage of time the run queue is occupied, the average length of the swap queue and the percentage of time the swap queue is occupied. The run queue lists jobs that are in memory and runnable, but does not include jobs that are waiting for I/O or sleeping. The run queue size should be less than 2. If the load is high and the runqocc=0 then the problem is most likely memory or I/O, not CPU. The swap queue lists jobs that are ready to run but have been swapped out.

The sar command deserves special mention as it is a very powerful command. The command is run by typing in:

sar -options int #samples

where valid options generally are:

After determining that the problem may well be CPU based it would then be necessary to move onto iostat to get more detail. Running iostat provides a great deal of information, but the values of concern here are the %user and %sys. If (%user + %sys) > 80% over a period of time then it is very likely the bottleneck is CPU. In particular it is necessary to watch for average CPU being greater than 70% with peaks above 90%. It is also possible to get similar information by running the ps -au or sar -u commands. Both of these provide information about CPU time. The sar -u command, in particular, breaks the time down into user, system, time waiting for blocked I/O (i.e. NFS, disk, ..) and idle time.

The ps -au command also provides information on the %physical memory the process is using and the current status for the process. Statuses shown are:

Status Meaning

The cron or at command can be used to automatically schedule execution of these commands to ensure snapshots are taken at the appropriate times. The atq command can be used to list what is in the at queue and the crontab -e command edits the cron table.

Once it has been determined that the problem is a CPU bottleneck there are several options. It is possible to limit the cputime a process can use by the limit command. If the problem relates to one process then it is also possible to model or profile that process using the prof, gprof or tprof command to find out whether it is possible to optimize the program code.

Prof and gprof are very similar and have several disadvantages when compared to tprof. Both prof and gprof require a recompile of the program using wither the -p or the -pg option and they impact performance of that program very badly. Tprof only needs to be recompiled in order to do source code level profiling (-qlist option). In particular tprof exhibits the following characteristics (AIX only):

So, the recommendation would be to use tprof if it is available on the chosen platform. It is also possible that the vendor will have their own equivalent to tprof.

Running the time or timex commands can also give a good indication of whether the process is CPU intensive. Compiler options have been proven to extensively affect the performance of CPU intensive programs as can be seen from the table below. It is well worth trying different options when compiling the program such as -O, -O2, -O3 and -Q (inline streams the code). Time/timex can give you an indication of how much benefit this will provide. Timex can also be run using the -s option which causes a full set of sar output to be generated for the duration of the programs execution. As can be seen from the table below, it is possible to see reductions in the order of 50% in CPU utilization by using optimization.

User CPU running Program phntest

Compiler Seconds % of CPU

Options for None

None 53.03 100%

-O 26.34 49.67%

-O -Q 25.11 47.35%

-O2 27.04 50.99%

-O2 -Q 24.92 46.99%

-O3 28.48 53.71%

-O3 -Q 26.13 49.27%

It is also possible to change the priority of the process so that other processes can gain control of the CPU ahead of it. This can be done by using the nice, renice or setpri commands. Renice is not available on all platforms. Before using these commands, it is useful to understand how the priority scheme works in UNIX.

Priorities range from 0-127 with 127 being the lowest priority. The actual priority of a task is set by the following calculation:

pri=nice+puser+(cpu/2)

Puser normally defaults to 40 and nice to 20 unless the nice or renice commands have been used against the process. On AIX a tick is 1/100th of a second and new priorities are calculated every tick as follows:

new-pri=(tick/2)+puser+nice

Every second tick is recalculated as tick=tick/2 and then new-pri is again recalculated.

Otherwise, a CPU upgrade may be the only solution if there is no other machine that the workload can be run on.

If the problem does not appear to be CPU then it becomes necessary to investigate memory and I/O as possible causes. Again, it is possible to use iostat or sar to get the information that is needed here. The iowait field shown in the iostat command is a good indicator of whether there are I/O problems. If iowait is greater than 40% then it becomes necessary to investigate the physical volumes to ensure that none of them are greater than 70% full. The lspv command can be used to determine utilization of the physical volume.

Iostat is a low overhead tool that can be automated and provides local counts for I/O data. Unlike sar, iostat does not provide timestamps in the output so it is important to make a note of start/stop times. However, iostat uses kernel data which makes it hardware specific with respect to the results obtained.

Iostat provides data on several important values for each physical disk. These include: %time the physical disk was busy, kilobytes per second to/from the disk, transfers per second to/from, kilobytes read and kilobytes written. This will help to determine if there is an imbalance of I/O amongst the physical volumes. If all appears to be normal here then the next step is to investigate which filesystems the I/O is directed at. If most of the I/O is directed at the page files then memory needs to be investigated.

Information on cylinder access and seek distances is available using the sadp command and cache statistics for disk are available using the sar -b command. Further information can be obtained by running filemon and looking to see what the most active filesystems are.

Filemon provides a list of the most active segments, the most active logical volumes and physical volumes, and detailed statistics for the busiest files as well as the segments, physical and logical volumes. Details include transfers, reads, read sizes, read times in msecs, logical seeks, write times, seek distances, throughput (kb/sec) and utilization percentages. However, it is important to note that filemon runs trace in the background which can affect performance. It is also possible to run fileplace which gives information on space efficiency and sequentiality.

This would be a good time to run lsvg, lslv and lspv to get a map of the layout of the physical and logical volumes on the system as well as the various volume groups. This will make it much simpler to get more indepth information. By running lsdev -C it is also possible to determine what kind of disk devices are installed and what size they are. By using a combination of the above commands a map can be produced for each physical volume of the filesystems and their placement on the disk. The lsattr -E -l sys0 command can be used to obtain information on system parameters such as cache sizes and other associated values.

If the bulk of the I/O (>30%) is going to a logical volume or filesystem that is not used for paging then the problem is most likely user I/O. This can be resolved by one of several options -checking fragmentation, reorganizing the filesystem, adding physical volumes or splitting the data in another manner. Adding memory may still help with the problem.

Other items to take into account when looking at I/O performance include the intra and inter policies, mirroring of disks, write verify and the scheduling policy for logical volumes. It is also important to remember that the SCSI card can only talk to one device at a time. Where multiple disks are behind one SCSI card, sequential readwrites are helped if they are spread across multiple adapters. Newer technologies such as SCSI-2, fast and wide and raid will also help improve performance. Some of the newer controllers also provide buffers for each disk and can perform two way searches.

If the bulk of the I/O is going to paging (i.e. the page LV is > 30%) then it becomes necessary to investigate further. The only options available to cure a paging problem are to write more memory efficient code, move the process to another system, add memory, reschedule the process so it doesn't contend with other memory intensive workloads, or add physical volumes or more page datasets. There are three commands that are used to investigate paging - lsps (or pstat), vmstat and svmon.

lsps -a will provide information on all of the page spaces available including physical volume and utilization. Vmstat is another low overhead tool and provides information on actual memory, free pages, processes on the I/O waitq, reclaims, pageins, pageouts, pages freed by the stealer per second, interrupts, system calls and CPU utilization. Like iostat, vmstat does not provide timestamps. Svmon -G provides similar information except it breaks memory down into work, persistent and client pages that are either in use or pinned. It is also possible to use the sar -w command.

When looking at paging it is important to note that the stealer will run whenever there are only ((2 x real) -8) pages left. So on a 32mb machine the stealer will run if there are only 56 pages left. The Rule of Thumb for page space versus real memory is generally in the order of Page = 2 x real. On some systems not all of the kernel processes are pinned so they can also be paged out. A pagein rate of >5/sec means that the system is memory constrained. Also, if fre is less than (.1(AVM)) then this may indicate that the system is real memory constrained. This depends on the way the VMM uses memory. For instance, AIX will use all memory for disk caching, etc before it reuses any so it is not unusual to see fre very low (110-120). Looking at pageins, pageouts, and the FR to SR ratio is a much more meaningful indicator for problems.

So, if at this point there is no problem with CPU and the system is not disk bound it becomes necessary to investigate the network to check whether it is remote file I/O bound. This is the last step before running the more resource heavy trace command to determine what is really happening. To look at network statistics there are three useful commands - netstat, netpmon and nfsstat.

Netstat -i shows the network interfaces along with input and output packets and errors. It also gives the number of collisions. The Mtu field shows the maximum ip packet size (transfer unit) and should be the same on all systems. In AIX it defaults to 1500. Both Oerrs (number of output errors since boot) and Ierrs (Input errors since boot) should be < 0.025. If Oerrs>0.025 then it is worth increasing the send queue size. Ierrs includes checksum errors and can also be an indicator of a hardware error such as a bad connector or terminator. The Collis field shows the number of collisions since boot and can be as high as 10%. If it is greater then it is necessary to reorganize the network as the network is obviously overloaded on that segment.

Netstat -m s used to analyze the use of mbufs in order to determine whether these are the bottleneck. The no -a command is used to see what the current values are. Values of interest are thewall, lowclust, lowmbuf and dogticks.

An mbuf is a kernel buffer that uses pinned memory and is used to service network communications. Mbufs come in two sizes - 256 bytes and 4096 bytes (clusters of 256 bytes). Thewall is the maximum memory that can be taken up for mbufs. Lowmbuf is the minimum number of mbufs to be kept free while lowclust is the minimum number of clusters to be kept free. Mb_cl_hiwat is the maximum number of free buffers to be kept in the free buffer pool and should be set to at least twice the value of lowclust to avoid thrashing.

Netstat -v is used to look at queues and other information. If Max packets on S/W transmit queue is >0 and is equal to current HW transmit queue length then the send queue size should be increased. If the No mbuf errors is large then the receive queue size needs to be increased.

Nfsstat is used to report on client and server NFS information, primarily at the daemon level. Nfsstat -c provides client information such as retrans and badxid. If badxid=retrans and retrans > 5% of calls the server is the problem, but if retrans > 5% of calls and badxid < retrans then the network is the problem. Also, if there are lots of timeouts then it is useful to increase the number of NFSDs and the qsize.

Netpmon is a further command that focuses on CPU, network adapters, remote nodes and LAN traffic. It is used to get a feeling for what is happening overall. By using a combination of the above commands it is possible to obtain a very clear view of what is happening at the network level.

At this point it is important to mention the UNIX kernel tables, as these can affect performance without any real indicators as to the cause. To find out what they are set to the pstat -T or sar -v commands can be used. Most of the values are calculated based on the value for maxusers so it is important to know what that is set to. It is often recommended that maxusers generally be determined by the following calculation:

Max Users = (2+ # users act + #NFS clients + .5 NFS exports )

In particular, attention should be paid to the following table sizes:

Process Table Size (NPROCS) - this is the maximum number of processes that can be in the system. On systems where Xwindows is heavily used this needs to be increased. If the table is full, then the process will fail to start.

Text Table Size (NTEXT) - This is the maximum number of executables that can be in the system at a time. If the table is full then the exe will not run.

Inode Table Size (NINODE) - This is a cache of the active inode entries. If this table fills up then performance slows down.

File Table Size (NFILE) - This is the maximum number of files that can be open at one time. If the table fills up the open will fail.

Callout Table Size (NCALLOUT) - This is the maximum number of timers that can be active at one time. Since timers are used heavily by device drivers to monitor I/O devices, the system will crash if this table fills up.

General Default Calculations (may be platform Specific)

Field Calculation

Nproc 20+(8*maxusers)

Ntext 36+maxusers

Ninode Nproc+80+(13*maxusers)

Nfile 16*(Nproc+16+maxusers)/10+64

Ncallout 16+Nproc

Other kernel settings that should be reviewed are the number of processes per user, maximum open files per user and maximum mounted filesystems. All of these can have unpredictable effects on performance.

If none of the above provides a reasonable clue to what is going on it is necessary to bring out the most powerful tool of all - trace. Trace will provide indepth information on everything that is going on in the system. However, it will definitely affect performance and thus, should be used judiciously.

As can be seen above there is a great deal of information that can be gleaned from the system for relatively minimal effort. Figure 1 contains some of the Rules of Thumb (ROT) that are useful along with what they apply to and the tool that best provides the information. These ROTs can then be used as follows to diagnose and fix performance problems in UNIX systems.

So to reiterate: first iostat, sar and uptime are run to determine whether it appears to be a CPU problem. If it is CPU then it is possible to try profiling, time/timex, optimization, priority changing or a CPU upgrade. If the problem is not CPU then it is necessary to investigate for possible I/O problems further using iostat, and then filemon, lsvg, lsdev, lsattr, lspv and lslv. I/O solutions include adding disk space and reorganizing filesystems.

If the I/O breakdown indicates the problem is with paging (page lv>30%) then svmon, lsps or pstat should be used. Possible solutions include adding memory or disk space. If the system does not appear to be disk bound then it is time to check for remote file I/O problems using nfsstat, netpmon and netstat. Finally, if none of these identify the problem it is time to resort to trace.

By taking such a structured approach to problem diagnosis it is possible to rapidly isolate the problem area. Taking these measurements when the system is behaving normally is also a useful option as this provides a baseline to compare future measurements with.

To do performance measurement properly it is helpful to automate the reporting process using a scripting language (such as perl) combined with scheduling commands such as at or cron. These languages can als be used to create graphical representations of the output from the tools.

By using the above mentioned tools and methodology, it is possible to diagnose performance problems on most UNIX systems, using non-proprietary tools that come standard with the system.

References:

1. System Performance Tuning, Mike Loukides, O'Reilly and Associates

2. SC23-2365, Performance Monitoring and Tuning Guide, IBM

[Mar 13, 2010] CertCities.com Column A System Monitoring Tool Primer

Here are a handful of helpful utilities for viewing and analyzing performance information for your Linux system.

3/11/2010 -- When you're the system administrator, you must keep an eye on how well your Linux system is performing by looking at information such as:

Linux comes with a number of utilities that can be used to monitor one or more of these performance parameters. The following sections introduce a few of these utilities and show how to understand the information presented by them.

Using the Top Utility

To view the top CPU processes - the ones that use most of the CPU time - you can use the text mode top utility. To start that utility, type top in a terminal window (or text console). The top utility then displays a text screen listing the current processes arranged in the order of CPU usage, along with various other information, such as memory and swap-space usage. The top utility updates the display every five seconds. If you keep top running in a window, you can continually monitor the status of your Linux system. To quit top, press Q, Ctrl+C or close the terminal window.

The first five lines of the output screen provide summary information about the system, arranged in the following order:

The table that appears below lists information about the current processes, arranged in decreasing order by amount of CPU time used. It also summarizes the meanings of the column headings in the table the top displays.
Meanings of Column Headings in top Utility's Output


Heading
Meaning
PID The process ID of the process
USER Username of the running process
PR Priority of the process
NI Nice value of the process - the value ranges from -20 (highest priority) to 19 (lowest priority) and the default is 0. (The nice value represents the relative priority of the process. The higher the value the lower the priority and the nicer the process - because it yields to other processes)
VIRT The total amount (in kilobytes) of virtual memory used by the process
RES Total physical memory used by a task (typically shown in kilobytes, with an m suffix indicating megabytes)
SHR Amount of shared memory used by process
S State of the process (S for sleeping, D for uninterruptible sleep, R for running, Z for zombies - processes that should be dead but are still running - or T for stopped)
%CPU Percentage of CPU time used since last screen update
%MEM Percentage of physical memory used by the process
TIME+ Total CPU time the process has used since it started
COMMAND Shortened form of the command that started the process

Using the Uptime Command
Use the uptime command to get a summary of the system's state by typing the following command:

uptime
It displays output similar to the following:
15:03:21 up 32 days, 57 min, 3 users, load average: 0.13, 0.23, 0.27
This output shows the current time, how long the system has been up, the number of users and (finally) the three load averages -- the average number of processes that were ready to run in the past 1, 5, and 15 minutes. Load averages greater than 1 imply that many processes are competing for CPU time simultaneously.

The load averages give you an indication of how busy the system is.

Using the Vmstat Utility
Receive summary information about the overall system usage with the vmstat utility. To view system usage information averaged over 5-second intervals, type the following command (the second argument indicates the total number of lines of output vmstat displays):

vmstat 5 8
Output similar to the following listing will be displayed:
procs -----------memory---------- ---swap-- -----io---- --system-- ----cpu----
 r  b   swpd   free   buff  cache   si   so    bi    bo   in    cs us sy id wa
 0  0  31324   4016  18568 136004    1    1    17    16    8   110 33  4 61  1
 0  1  31324   2520  15348 139692    0    0  7798   199 1157   377  8  8  6 78
 1  0  31324   1584  12936 141480    0   19  5784   105 1099   437 12  5  0 82
 2  0  31324   1928  13004 137136    7    0  1586   138 1104   561 43  6  0 51
 3  1  31324   1484  13148 132064    0    0  1260    51 1080   427 50  5  0 46
 0  0  31324   1804  13240 127976    0    0  1126    46 1082   782 19  5 47 30
 0  0  31324   1900  13240 127976    0    0     0     0 1010   211  3  1 96  0
 0  0  31324   1916  13248 127976    0    0     0    10 1015   224  3  2 95  0

The first line of output shows the averages since the last reboot. After that, vmstat displays the 5-second average data seven more times, covering the next 35 seconds. The tabular output is grouped as six categories of information, indicated by the fields in the first line of output. The second line shows further details for each of the six major fields. You can interpret these fields using the following table:

Meaning of Fields in the vmstat Utility's Output

Field Name Description
procs Number of processes and their types: r = processes waiting to run, b = processes in uninterruptible sleep, w = processes swapped out but ready to run
memory Information about physical memory and swap-space usage (all numbers in kilobytes): swpd = virtual memory used, free = free physical memory, buff = memory used as buffers, cache = virtual memory that's cached
swap Amount of swapping (the numbers are in kilobytes per second): si = amount of memory swapped in from disk, so = amount of memory swapped to disk
io Information about input and output. (The numbers are in blocks per second where the block size depends on the disk device.) bi = rate of blocks sent to disk, bo = rate of blocks received from disk
system Information about the system: in = number of interrupts per second (including clock interrupts), cs = number of context switches per second - - how many times the kernel changed which process was running
cpu Percentages of CPU time used: us = percentage of CPU time used by user processes, sy = percentage of CPU time used by system processes, id = percentage of time CPU is idle, wa = time spent waiting for input or output (I/O)

In the vmstat utility's output, high values in the si and so fields indicate too much swapping (the copying of information between physical memory and the virtual memory on the hard drive). High numbers in the bi and bo fields indicate too much disk activity.

[Mar 3, 2010] Five Tools for Measuring and Improving Linux System Performance Linux.com

Network Monitoring with Ifstat

The ifstat utility is to network interface activity what iostat is to device I/O and CPU activity. You can use it to display activity on one or more network interfaces. When you run ifstat without any arguments or options, it will display the traffic for your standard network interfaces. You can specify one or more interfaces, and add a few options to make the results easier to read and work with.

If you're running ifstat on a system that has unused or idle interfaces, use ifstat -z to hide interfaces that are idle (for example, a system with VMware that may not be using all the vmnet interfaces at the time).

To see all the bandwidth being pushed by a system, the -T option tells ifstat to display a total of all interfaces in addition to the individual tallies. To add a timestamp at the beginning of each line, use -t. By default the information is updated every second. If you want to crank this down a bit, you can specify a delay by adding a number at the end of the command. So, ifstat -Tt 3 will give you a display with the count updated every three seconds, and a total tally at the end of the display.

Finally, if you only want ifstat to run a few times, you can specify a second number to tell it to repeat that many times. To update 10 times, for example, you might use ifstat -tT 5 10 to get 10 updates five seconds apart. Generally speaking, ifstat is easy to use and get started with.

[Nov 11, 2009] FROSUG perf horrors

A couple of days before Halloween I gave a talk titled "Little Shop of Performance Horrors" at the Front Range OpenSolaris User Group (FROSUG), in Denver, Colorado. The title was suggested to me, which inspired me to talk about things going wrong in the field of system performance. We had a great turnout, despite the talk happening during one of the worst snow storms of the year.

For the talk, I listed different performance problems and gave an example or two of each, including many lessons that were learnt the hard way.

Horrific Topics:

The slides are here. I'll revisit the slides when I have a chance and add more content; as this was the first time I give this talk, several more topics sprung to mind during the actual talk which there aren't slides for.

Despite speaking for about 2.5 hours, the entire talk was videoed and has already been posted on Sun Video, which I've included below.

Part 1/3

Part 2/3

Part 3/3

[Feb 25, 2009] How to troubleshoot RHEL performance bottlenecks by Ken Milberg

09.30.2008

You've just had your first cup of coffee and have received that dreaded phone call. The system is slow. What are you going to do? This article will discuss performance bottlenecks and optimization in Red Hat Enterprise Linux (RHEL5).

Before getting into any monitoring or tuning specifics, you should always use some kind of tuning methodology. This is one which I've used successfully through the years:

1. Baseline – The first thing you must do is establish a baseline, which is a snapshot of how the system appears when it's performing well. This baseline should not only compile data, but also document your system's configuration (RAM, CPU and I/O). This is necessary because you need to know what a well-performing system looks like prior to fixing it.

2. Stress testing and monitoring – This is the part where you monitor and stress your systems at peak workloads. It's the monitoring which is key here – as you cannot effectively tune anything without some historic trending data.

3. Bottleneck identification – This is where you come up with the diagnosis for what is ailing your system. The primary objective of section 2 is to determine the bottleneck. I like to use several monitoring tools here. This allows me to cross-reference my data for accuracy.

4. Tune – Only after you've identified the bottleneck can you tune it.

5. Repeat – Once you've tuned it, you can start the cycle again – but this time start from step 2 (monitoring) – as you already have your baseline.

It's important to note that you should only make one change at a time. Otherwise, you'll never know exactly what impacted any changes which might have occurred. It is only by repeating your tests and consistently monitoring your systems that you can determine if your tuning is making an impact.

RHEL monitoring tools

Before we can begin to improve the performance of our system, we need to use the monitoring tools available to us to baseline. Here are some monitoring tools you should consider using:

Oprofile

This tool (made available in RHEL5) utilizes the processor to retrieve kernel system information about system executables. It allows one to collect samples of performance data every time a counter detects an interrupt. I like the tool also because it carries little overhead – which is very important because you don't want monitoring tools to be causing system bottlenecks. One important limitation is that the tool is very much geared towards finding problems with CPU limited processes. It does not identify processes which are sleeping or waiting on I/O.

The steps used to start up Oprofile include setting up the profiler, starting it and then dumping the data.

First we'll set up the profile. This option assumes that one wants to monitor the kernel.

# opcontrol --setup –vmlinux=/usr/lib/debug/lib/modules/'uname -r'/vmlinux

Then we can start it up.

# opcontrol --start

Finally, we'll dump the data.

# opcontrol --stop/--shutdown/--dump

SystemTap

This tool (introduced in RHEL5) collects data by analyzing the running kernel. It really helps one come up with a correct diagnosis of a performance problem and is tailor-made for developers. SystemTap eliminates the need for the developer to go through the recompile and reinstallation process to collect data.

Frysk

This is another tool which was introduced by Red Hat in RHEL5. What does it do for you? It allows both developers and system administrators to monitor running processes and threads. Frysk differs from Oprofile in that it uses 100% reliable information (similar to SystemTap) - not just a sampling of data. It also runs in user mode and does not require kernel modules or elevated privileges. Allowing one to stop or start running threads or processes is also a very useful feature.

Some more general Linux tools include top and vmstat. While these are considered more basic, often I find them much more useful than more complex tools. Certainly they are easier to use and can help provide information in a much quicker fashion.

Top provides a quick snapshot of what is going on in your system – in a friendly character-based display.

It also provides information on CPU, Memory and Swap Space.

Let's look at vmstat – one of the oldest but more important Unix/Linux tools ever created. Vmstat allows one to get a valuable snapshot of process, memory, sway I/O and overall CPU utilization.

Now let's define some of the fields:

Memory
swpd – The amount of virtual memory
free – The amount of free memory
buff – Amount of memory used for buffers
cache – Amount of memory used as page cache

Process
r – number of run-able processes
b – number or processes sleeping.
Make sure this number does not exceed the amount of run-able processes, because when this condition occurs it usually signifies that there are performance problems.

Swap
si – the amount of memory swapped in from disk
so – the amount of memory swapped out.

This is another important field you should be monitoring – if you are swapping out data, you will likely be having performance problems with virtual memory.

CPU
us – The % of time spent in user-level code.
It is preferable for you to have processes which spend more time in user code rather than system code. Time spent in system level code usually means that the process is tied up in the kernel rather than processing real data.
sy – the time spent in system level code
id – the amount of time the CPU is idle wa – The amount of time the system is spending waiting for I/O.

If your system is waiting on I/O – everything tends to come to a halt. I start to get worried when this is > 10.

There is also:

Free – This tool provides memory information, giving you data around the total amount of free and used physical and swap memory.

Now that we've analyzed our systems – lets look at what we can do to optimize and tune our systems.

CPU Overhead – Shutting Running Processes
Linux starts up all sorts of processes which are usually not required. This includes processes such as autofs, cups, xfs, nfslock and sendmail. As a general rule, shut down anything that isn't explicitly required. How do you do this? The best method is to use the chkconfig command.

Here's how we can shut these processes down.
[root ((Content component not found.)) _29_140_234 ~]# chkconfig --del xfs

You can also use the GUI - /usr/bin/system-config-services to shut down daemon process.

Tuning the kernel
To tune your kernel for optimal performance, start with:

sysctl – This is the command we use for changing kernel parameters. The parameters themselves are found in /proc/sys/kernel

Let's change some of the parameters. We'll start with the msgmax parameter. This parameter specifies the maximum allowable size of a single message in an IPC message queue. Let's view how it currently looks.

[root ((Content component not found.)) _29_139_52 ~]# sysctl kernel.msgmax
kernel.msgmax = 65536
[root ((Content component not found.)) _29_139_52 ~]#

There are three ways to make these kinds of kernel changes. One way is to change this using the echo command.

[root ((Content component not found.)) _29_139_52 ~]# echo 131072 >/proc/sys/kernel/msgmax
[root ((Content component not found.)) _29_139_52 ~]# sysctl kernel.msgmax
kernel.msgmax = 131072
[root ((Content component not found.)) _29_139_52 ~]#

Another parameter that is changed quite frequently is SHMMAX, which is used to define the maximum size (in bytes) for a shared memory segment. In Oracle this should be set large enough for the largest SGA size. Let's look at the default parameter:

# sysctl kernel.shmmax
kernel.shmmax = 268435456

This is in bytes – which translates to 256 MG. Let's change this to 512 MG, using the -w flag.

[root ((Content component not found.)) _29_139_52 ~]# sysctl -w kernel.shmmax=5368709132
kernel.shmmax = 5368709132
[root ((Content component not found.)) _29_139_52 ~]#

The final method for making changes is to use a text editor such as vi – directly editing the /etc/sysctl.conf file to manually make our changes.

To allow the parameter to take affect dynamically without a reboot, issue the sysctl command with the -p parameter.

Obviously, there is more to performance tuning and optimization than we can discuss in the context of this small article – entire books have been written on Linux performance tuning. For those of you first getting your hands dirty with tuning, I suggest you tread lightly and spend time working on development, test and/or sandbox environments prior to deploying any changes into production. Ensure that you monitor the effects of any changes that you make immediately; it's imperative to know the effect of your change. Be prepared for the possibility that fixing your bottleneck has created another one. This is actually not a bad thing in itself, as long as your overall performance has improved and you understand fully what is happening.

Performance monitoring and tuning is a dynamic process which does not stop after you have fixed a problem. All you've done is established a new baseline. Don't rest on your laurels, and understand that performance monitoring must be a routine part of your role as a systems administrator.

About the author: Ken Milberg is a systems consultant with two decades of experience working with Unix and Linux systems. He is a SearchEnterpriseLinux.com Ask the Experts advisor and columnist.

[Feb 23, 2009] Deployment_Guide/Gathering System Information

Before you learn how to configure your system, you should learn how to gather essential system> information. For example, you should know how to find the amount of free memory, the amount of available hard drive space, how your hard drive is partitioned, and what processes are running. This chapter discusses how to retrieve this type of information from your Red Hat Enterprise Linux system using simple commands and a few simple programs.

1. System Processes

The ps ax command displays a list of current system processes, including processes owned by other users. To display the owner alongside each process, use the ps aux command. This list is a static list; in other words, it is a snapshot of what was running when you invoked the command. If you want a constantly updated list of running processes, use top as described below. The ps output can be long. To prevent it from scrolling off the screen, you can pipe it through less:

ps aux | less

You can use the ps command in combination with the grep command to see if a process is running. For example, to determine if Emacs is running, use the following command:

ps ax | grep emacs

The top command displays currently running processes and important information about them including their memory and CPU usage. The list is both real-time and interactive. An example of output from the top command is provided as follows:

To exit top press the q key. Useful interactive commands that you can use:

For more information, refer to the
top(1) manual page.

[Feb 12, 2009] Choosing an I-O Scheduler for Red Hat Enterprise Linux 4 and the 2.6 Kernel

redhat.com

The short summary of our study indicates that there is no SINGLE answer to which I/O scheduler is best. The good news is that with Red Hat Enterprise Linux 4 an end-user can customize their scheduler with a simple boot option. Our data suggests the default Red Hat Enterprise Linux 4 I/O scheduler, CFQ, provides the most scalable algorithm for the widest range of systems, configurations, and commercial database users. However, we have also measured other workloads whereby the Deadline scheduler out-performed CFQ for large sequential read-mostly DSS queries. Other studies referenced in the section "References" explored using the AS scheduler to help interactive response times. In addition, noop has proven to free up CPU cycles and provide adequate I/O performance for systems with intelligent I/O controller which provide their own I/O ordering capabilities.

In conclusion, we recommend baselining an application with the default CFQ. Use this article and its references to match your application to one of the studies. Then adjust the I/O scheduler via the simple command line re-boot option if seeking additional performance. Make only one change at a time, and use performance tools to validate the results.

[Feb 11, 2009] What Is the Linux Kernel Parameter vm.swappiness

Articles - Kernel Tuning

vm.swappiness is a tunable kernel parameter that controls how much the kernel favors swap over RAM. At the source code level, it's also defined as the tendency to steal mapped memory. A high swappiness value means that the kernel will be more apt to unmap mapped pages. A low swappiness value means the opposite, the kernel will be less apt to unmap mapped pages. In other words, the higher the vm.swappiness value, the more the system will swap.

The default value I've seen on both enterprise level Red Hat and SLES servers is 60.

To find out what the default value is on a particular server, run:

sysctl vm.swappiness

The value is also located in /proc/sys/vm/swappiness.

What reason might there be to change the value of this parameter? Like all other tunable kernel parameters, there may not be a compelling reason to change the default value, but having a facility that allows one to manipulate how the linux kernel behaves without modifying source code is indispensable.

If there were reasons to change the vm.swappiness kernel parameter, one might be to decrease the parameter if swapping is undesirable. I've seen enterprise configurations where servers had a swap to RAM ratio of 1:125. It's evident in this case that there is no interest in ever using anything but physical memory so why not make the kernel privy to this information. Whether the vm.swappiness parameter is set to 0, 20, 40, or any other value, the owner of the server should perform due diligence to see what affect this has on the server and applications. For an under-the-cover look on the effect of changing the parameter, one only needs to look at the vmscan.c source file and the swap_tendency algorithm.

swap tendency = mapped_ratio / 2 + distress + vm_swappiness;


On the flip side, one may consider increasing the vm.swappiness parameter greater than the default if a particular system has physical memory contraints.

"Systems with memory constraints that run batch jobs (processes that sleep for long time) might benefit from an aggressive swapping behavior." http://unixfoo.blogspot.com/2007/11/linux-performance-tuning.html

Andrew Morton sets his workstation vm.swappiness parameter to 100. "My point is that decreasing the tendency of the kernel to swap stuff out is wrong. You really don't want hundreds of megabytes of BloatyApp's untouched memory floating about in the machine. Get it out on the disk, use the memory for something useful."

The following is an excerpt of a benchmark obtained using different vm.swappiness values while performing dd on a 2.6.5-7.97-default kernel (http://lwn.net/Articles/100978/):

vm.swappiness Total I/O Avg Swap
0 273.57 MB/s 0 MB
20 273.75 MB/s 0 MB
40 273.52 MB/s 0 MB
60 229.01 MB/s 23068 MB
80 195.63 MB/s 25587 MB
100 184.30 MB/s 26006 MB

To read more information on the vm.swappiness kernel tunable, you may find these links helpful.

swapping and the value of /proc/sys/vm/swappiness

Linux performance tuning - /proc/sys/vm/swappiness

[Oct 27, 2008] sysprof 1.0.11

About:
Sysprof is a sampling CPU profiler that uses a Linux kernel module to profile the entire system, not just a single application. It handles shared libraries, and applications do not need to be recompiled. It profiles all running processes, not just a single application, has a nice graphical interface, shows the time spent in each branch of the call tree, can load and save profiles, and is easy to use.

Release focus: Minor bugfixes

Changes:
This version compiles with recent kernels.

Author:
Sřren Sandmann [contact developer]

[Oct 9, 2008] .. so I got one of the new Intel SSD's

The kernel summit was two weeks ago, and at the end of that I got one of the new 80GB solid state disks from Intel. Since then, I've been wanting to talk to people about it because I'm so impressed with it, but at the same time I don't much like using the kernel mailing list as some kind of odd public publishing place that isn't really kernel-related, so since I'm testing this whole blogging thing, I might as well vent about it here.

That thing absolutely rocks.

I've been impressed by Intel before (Core 2), but they've had their share of total mistakes and idiotic screw-ups too (Itanic), but the things Intel tends to have done well are the things where they do incremental improvements. So it's a nice thing to be able to say that they can do new things very well too. And while I often tend to get early access to technology, seldom have I looked forward to it so much, and seldom have things lived up to my expectations so well.

In fact, I can't recall the last time that a new tech toy I got made such a dramatic difference in performance and just plain usability of a machine of mine.

So what's so special about that Intel SSD, you ask? Sure, it gets up to 250MB/s reads and 70MB/s writes, but fancy disk arrays can certainly do as well or better. Why am I not gushing about soem nice NAS box? I didn't even put the thing into a laptop, after all, it's actually in Tove's Mac Mini (running Linux, in case anybody was confused ;), so a RAID NAS box would certainly have been a lot bigger and probably have more features.

But no, forget about the throughput figures. Others can match - or at last come close - to the throughput, but what that Intel SSD does so well is random reads and writes. You can do small random accesses to it and still get great performance, and quite frankly, that's the whole point of not having some stupid mechanical latencies as far as I'm concerned.

And the sad part is that other SSD's generally absolutely suck when it comes to especially random write performance. And small random writes is what you get when you update various filesystem meta-data on any normal filesystem, so it really does matter. For example, a vendor who shall remain nameless has an SSD disk out there that they were also hawking at the Kernel Summit, and while they get fine throughput (something like 50+MB/s on big contiguous writes), they benchmark a pitiful 10 (yes, that's ten, as in "how many fingers do you have) small random writes per second. That is slower than a rotational disk.

In contrast, the Intel SSD does about 8,500 4kB random writes per second. Yeah, that's over eight thousand IOps on random write accesses with a relevant block size, rather than some silly and unrealistic contiguous write test. That's what I call solid-state media.

The whole thing just rocks. Everything performs well. You can put that disk in a machine, and suddenly you almost don't even need to care whether things were in your page cache or not. Firefox starts up pretty much as snappily in the cold-cache case as it does hot-cache. You can do package installation and big untars, and you don't even notice it, because your desktop doesn't get laggy or anything.

So here's the deal: right now, don't buy any other SSD than the Intel ones, because as far as I can tell, all the other ones are pretty much inferior to the much cheaper traditional disks, unless you never do any writes at all (and turn off 'atime', for that matter).

So people - ignore the manufacturer write throughput numbers. They don't mean squat. The fact that you may be able to push 50MB/s to the SSD is meaningless if that can only happen when you do big, aligned, writes.

If anybody knows of any reasonable SSDs that work as well as Intel's, let me know.

[Nov 6, 2007] freshmeat.net Project details for sarvant

sarvant analyzes files from the sysstat utility "sar" and produces graphs of the collected data using gnuplot. It supports user-defined data source collection, debugging, start and end times, interval counting, and output types (Postscript, PDF, and PNG). It's also capable of using gnuplot's graph smoothing capability to soften spiked line graphs. It can analyze performance data over both short and long periods of time.

[Nov 6, 2007] Stress-testing the Linux kernel

[Nov 6, 2007] Tutorial: Monitor a Linux System with Sysstat

[Nov 6, 2007] SYSSTAT tutorial

You will find here a tutorial describing a few use cases for some sysstat commands. The first section below concerns the sar and sadf commands. The second one concerns the pidstat command. Of course, you should really have a look at the manual pages to know all the features and how these commands can help you to monitor your system (follow the Documentation link above for that).

  1. Section 1: Using sar and sadf
  2. Section 2: Using pidstat

Section 1: Using sar and sadf

sar is the system activity reporter. By interpreting the reports that sar produces, you can locate system bottlenecks and suggest some possible solutions to those annoying performance problems.
The Linux kernel maintains internal counters that keep track of requests, completion times, I/O block counts, etc. From this and other information, sar calculates rates and ratios that give insight into where the bottlenecks are.

The key to understanding sar is that it reports on system activity over a period of time. You must take care to collect sar data at an appropriate time (not at lunch time or on weekends, for example). Here is one way to invoke sar:

sar -u -o datafile 2 3 
The -u option specifies our interest in the CPU subsystem. The -o option will create an output file that contains binary data. Finally, we will take 3 samples at two-second intervals. Upon completion of the sampling, sar will report the results to the screen. This provides us with a snapshot of current system activity.
The above example uses sar in interactive mode. You can also invoke sar from cron. In this case, cron would run the /usr/lib/sa/sa1 shell script and create a daily log file. The /usr/lib/sa/sa2 shell script is run to format the log into human-readable form. These scripts may be invoked by a crontab run by root (although I prefer to use adm). Here is the crontab, located in /etc/cron.d directory and using Vixie cron syntax, that makes this happen:

# Run system activity accounting tool every 10 minutes
*/10 * * * * root /usr/lib/sa/sa1 -d 1 1
# 0 * * * * root /usr/lib/sa/sa1 -d 600 6 &
# Generate a daily summary of process accounting at 23:53
53 23 * * * root /usr/lib/sa/sa2 -A

In reality, the sa1 script initiates a related utility called sadc. sa1 gives sadc several arguments to specify the amount of time to wait between samples, the number of samples, and the name of a file into which the binary results should be written.

A new file is created each day so that we can easily interpret daily results. The sa2 script calls sar, which formats the binary data into human-readable form.

Let's think of our system as being composed of three interdependent subsystems: CPU, disk and memory. Our goal is to find out which subsystem is responsible for any performance bottleneck. By analyzing sar's output, we can achieve that goal.

Listing below represents the report produced by initiating the sar -u command. Initiating sar in this manner produces a report from the daily log file produced by sadc.

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM CPU %user %nice %system %iowait %steal %idle
09:10:00 PM all 96.18 0.00 0.42 0.00 0.00 3.40
09:20:00 PM all 97.99 0.00 0.36 0.00 0.00 1.65
09:30:00 PM all 97.59 0.00 0.38 0.00 0.00 2.03
...

The %user and %system columns simply specify the amount of time the CPU spends in user and system mode. The %iowait and %idle columns are of interest to us when doing performance analysis. The %iowait column specifies the amount of time the CPU spends waiting for I/O requests to complete. The %idle column tells us how much useful work the CPU is doing. A %idle time near zero indicates a CPU bottleneck, while a high %iowait value indicates unsatisfactory disk performance.
Additional information can be obtained by the sar -q command, which displays the run queue length, total number of processes, and the load averages for the past one, five and fifteen minutes:

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM runq-sz plist-sz ldavg-1 ldavg-5 ldavg-15
09:10:00 PM 2 121 2.22 2.17 1.45
09:20:00 PM 6 137 2.79 2.48 1.73
09:30:00 PM 5 129 3.31 2.83 1.95
...

This example shows that the system is busy (since more than one process is runnable at any given time) and rather overloaded.
sar also lets you monitor memory utilization. Have a look at the following example produced by sar -r:

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM kbmemfree kbmemused %memused kbbuffers kbcached kbswpfree kbswpused %swpused kbswpcad
09:10:00 PM 591468 444388 42.90 19292 227412 1632920 0 0.00 0
09:20:00 PM 546860 488996 47.21 21844 243900 1632920 0 0.00 0
09:30:00 PM 538268 497588 48.04 25308 267228 1632920 0 0.00 0
...

This listing shows that the system has plenty of free memory. Swap space is not used. So memory is not a problem here. You can double-check this by using sar -W to get swapping statistics:

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM pswpin/s pswpout/s
09:10:00 PM 0.00 0.00
09:20:00 PM 0.00 0.00
09:30:00 PM 0.00 0.00
...

sar can also help you to monitor disk activity. sar -b displays I/O and transfer rate statistics grouped for all block devices:

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM tps rtps wtps bread/s bwrtn/s
09:10:00 PM 6.37 2.32 4.05 126.84 61.41
09:20:00 PM 4.03 0.74 3.29 54.49 46.04
09:30:00 PM 6.71 3.11 3.59 80.13 49.18
...

sar -d enables you to get more detailed information on a per device basis. It displays statistics data similar to those displayed by iostat:

Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 AM DEV tps rd_sec/s wr_sec/s avgrq-sz avgqu-sz await svctm %util
09:10:00 AM sda 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
09:10:00 AM sdb 18.09 0.00 160.80 8.89 0.01 0.67 0.19 0.35
09:20:00 AM sda 2.51 0.00 52.26 20.80 0.00 0.60 0.40 0.10
09:20:00 AM sdb 18.91 0.00 141.29 7.47 0.02 0.92 0.21 0.40
09:30:00 AM sda 26.87 11.94 291.54 11.30 0.12 4.33 1.07 2.89
09:30:00 AM sdb 7.00 0.00 54.00 7.71 0.00 0.50 0.14 0.10
...

sar has numerous other options that enable you to gather statistics for every part of your system. You will find useful information about them in the manual page.
OK. As a last example, let's show how the sadf command can help us to produce some graphs.
We use the command sar -B to display paging statistics from daily data file sa29 (see example below).

# sar -B -f /var/log/sa/sa29
Linux 2.6.8.1-27mdkcustom (localhost) 03/29/2006

09:00:00 PM pgpgin/s pgpgout/s fault/s majflt/s
09:10:00 PM 63.42 30.71 267.35 0.45
09:20:00 PM 27.25 23.02 281.88 0.26

09:30:00 PM 40.06 24.59 246.51 0.32

09:40:00 PM 43.58 26.11 265.25 0.34
09:50:00 PM 34.12 28.38 271.54 0.37
Average: 41.69 26.56 266.51 0.35
sadf -d extracts data in a format that can be easily ingested by a relational database:

# sadf -d /var/log/sa/sa29 -- -B
localhost;601;2006-03-29 19:10:00 UTC;63.42;30.71;267.35;0.45
localhost;00;2006-03-29 19:20:00 UTC;27.25;23.02;281.88;0.26
localhost;600;2006-03-29 19:30:00 UTC;40.06;24.59;246.51;0.32
localhost;600;2006-03-29 19:40:00 UTC;43.58;26.11;265.25;0.34
localhost;600;2006-03-29 19:50:00 UTC;34.12;28.38;271.54;0.37
If we saw this as a text file, both Excel and Open Office will allow us to specify a semicolon as a field delimiter. Then we can generate our performance report and graph.


Section 2: Using pidstat

The pidstat command is used to monitor processes and threads currently being managed by the Linux kernel. It can also monitor the children of those processes and threads.

With its -d option, pidstat can report I/O statistics, providing that you have a recent Linux kernel (2.6.20+) with the option CONFIG_TASK_IO_ACCOUNTING compiled in. So imagine that your system is undergoing heavy I/O and you want to know which tasks are generating them. You could then enter the following command:

$ pidstat -d 2
Linux 2.6.20 (localhost) 09/26/2007

10:13:31 AM PID kB_rd/s kB_wr/s kB_ccwr/s Command
10:13:31 AM 15625 1.98 16164.36 0.00 dd

10:13:33 AM PID kB_rd/s kB_wr/s kB_ccwr/s Command
10:13:33 AM 15625 4.00 20556.00 0.00 dd

10:13:35 AM PID kB_rd/s kB_wr/s kB_ccwr/s Command
10:13:35 AM 15625 0.00 10642.00 0.00 dd
...

This report tells us that there is only one task (a "dd" command with PID 15625) which is responsible for these I/O.

When no PID's are explicitly selected on the command line (as in the case above), the pidstat command examines all the tasks managed by the system but displays only those whose statistics are varying during the interval of time. But you can also indicate which tasks you want to monitor. The following example reports CPU statistics for PID 8197 and all its threads:

$ pidstat -t -p 8197 1 3
Linux 2.6.8.1-27mdkcustom (localhost) 09/26/2007

10:40:05 AM PID TID %user %system %CPU CPU Command
10:40:06 AM 8197 - 71.29 1.98 73.27 0 procthread
10:40:06 AM - 8197 71.29 1.98 73.27 0 |__procthread
10:40:06 AM - 8198 0.00 0.99 0.99 0 |__procthread

10:40:06 AM PID TID %user %system %CPU CPU Command
10:40:07 AM 8197 - 67.00 2.00 69.00 0 procthread
10:40:07 AM - 8197 67.00 2.00 69.00 0 |__procthread
10:40:07 AM - 8198 1.00 1.00 2.00 0 |__procthread

10:40:07 AM PID TID %user %system %CPU CPU Command
10:40:08 AM 8197 - 56.00 6.00 62.00 0 procthread
10:40:08 AM - 8197 56.00 6.00 62.00 0 |__procthread
10:40:08 AM - 8198 2.00 1.00 3.00 0 |__procthread

Average: PID TID %user %system %CPU CPU Command
Average: 8197 - 64.78 3.32 68.11 - procthread
Average: - 8197 64.78 3.32 68.11 - |__procthread
Average: - 8198 1.00 1.00 1.99 - |__procthread


As a last example, let me show you how pidstat helped me to detect a memory leak in the pidstat command itself. At that time I was testing the very first version of pidstat I wrote for sysstat 7.1.4 and fixing the last remaining bugs. Here is the command I entered on the command line and the output I got:

$ pidstat -r 2
Linux 2.6.8.1-27mdkcustom (localhost) 09/26/2007

10:59:03 AM PID minflt/s majflt/s VSZ RSS %MEM Command
10:59:05 AM 14364 113.66 0.00 2480 1540 0.15 pidstat

10:59:05 AM PID minflt/s majflt/s VSZ RSS %MEM Command
10:59:07 AM 7954 150.00 0.00 27416 19448 1.88 net_applet
10:59:07 AM 14364 120.00 0.00 3048 2052 0.20 pidstat

10:59:07 AM PID minflt/s majflt/s VSZ RSS %MEM Command
10:59:09 AM 14364 116.00 0.00 3488 2532 0.24 pidstat

10:59:09 AM PID minflt/s majflt/s VSZ RSS %MEM Command
10:59:11 AM 7947 0.50 0.00 27044 18356 1.77 mdkapplet
10:59:11 AM 14364 116.00 0.00 3928 3012 0.29 pidstat

10:59:11 AM PID minflt/s majflt/s VSZ RSS %MEM Command
10:59:13 AM 7954 155.50 0.00 27416 19448 1.88 net_applet
10:59:13 AM 14364 115.50 0.00 4496 3488 0.34 pidstat
...

I noticed that pidstat had a memory footprint (VSZ and RSS fields) that was constantly increasing as the time went by. I quickly found that I had forgotten to close a file descriptor in a function of my code and that was responsible for the memory leak...!

[Oct 23, 2011] Optimal Usage of SSDs Under Linux: Optimize Your I/O Subsystem
Werner Fischer, Thomas-Krenn.AG

Solid-state drives (SSDs) gain popularity, their prices are falling. They outperform conventional hard drives in both random and streaming access patterns and open new possibilities. SSDs work in Linux out-of-the-box, but their performance and endurance can be highly optimized through various tunings: File systems like Ext4, Btrfs or XFS allow online and batched discard to trim unused sectors and have special features like pre-discard on file system initialization. Over-provisioning a SSD compensates possible drawbacks when discard is not possible. Additional tweaks like using the noatime mount option, tmpfs for volatile data, native command queuing, and some more tunings finally provide altogether I/O never seen before. Attendees know how to manage device mapper, LVM, software RAID, and Ext4. They want to solve I/O bottlenecks on Linux servers or simply accelerate their Linux laptop by using SSDs in the best possible way.

Werner Fischer, Thomas-Krenn.AG Werner Fischer is a technology specialist at Thomas-Krenn.AG and chief editor of the Thomas Krenn Wiki. His current main focus is hardware-monitoring and I/O optimization, especially with Flash-based storage. Besides that Werner mainly deals with virtualization and high availability. He is a regular speaker about all these topics at many conferences, including LinuxTag, Open Source Data Center Conference, Profoss, Open Source Meets Business, Security Forum Hagenberg and other conferences (see www.wefi.net) and has written articles for the German ADMIN Magazin, Linux Technical Review, network Computing, and LANline Magazin. Before joining Thomas Krenn in 2005, Werner worked at IBM in Germany and Austria. Together with other IBMers he wrote two IBM Redbooks in the HA and storage area. Werner holds a graduate degree in computer and media security from the University of Applied Sciences of Upper Austria in Hagenberg.

LinuxCon Europe 2011 HDD H-O Caching With SSDs Linux Foundation Events

SSDs are becoming more and more common, but they are still restricted in size and in lifetime. This makes their useability as the main hard drive rather limited. So instead it would make more sense to use them for caching I/O accesses to a normal HDD. In this talk I will be presenting two approaches to this, 'flashcache' and 'ssdcache'. The first is an existing implementation currently in use at taobao (cf taobao.com). It's using an on-disk bitmap format to store the block references and implements both write-through and write-back caching. The second is a re-implementation from me using a different paradigm: - Metadata will not be stored on disk, but rather in a persistent memory region - latency is minimized, preferring fast I/O to expensive cache lookups. I'll be giving some results for both of them and will be discussing the pros and cons of both approaches.

Hans Reinecke, SUSE

Studied Physics with main focus image processing in Heidelberg from 1990 until 1997, followed by a PhD in Edinburgh 's Heriot-Watt University in 2000. Worked as sysadmin during the studies, mainly in the Mathematical Institute in Heidelberg. Linux addict since the earliest days (0.95); various patches to get Linux up and running. Now working for SUSE Linux Products GmbH as senior engineer with focus on storage and mainframe support. Main points of interest are all the nifty things you can do with storage: (i)SCSI, multipathing, FCoE and the like. And S/390, naturally. Plus occasionally maintaining the aic79xx driver.

Tuning Oracle Database 10g for ext3 file systems

redhat.com

Red Hat® Enterprise Linux® 4 enables Oracle® Database 10g file system applications to perform within 3% of raw I/O due to enhancements to the ext3 file system and through the support of both Direct and Asynchronous I/O. Since Red Hat Enterprise Linux 2.1, the use of Direct I/O (DIO) has been an important ext file system feature for large Oracle database applications where the database sizes greatly exceed the amount of physical memory available on the servers.

The Linux 2.6 kernel implemented in Red Hat Enterprise Linux 4 continues to support Direct I/O to ext file systems and also includes scalability changes for Asynchronous I/O (AIO), which allows the simultaneous use of AIO and DIO to ext3 files for database use. This combination allows ext3 files system databases to scale up to CPU counts previously only considered for raw I/O while providing the manageability of a file system to ease system administration task like copying or moving files, backup to tape, and file system and volume snap shots.

Traditional Oracle users setup raw devices and/or volume managers with raw devices for peak Oracle performance. Red Hat Enterprise Linux 4 supports this by using the raw command to single disks, md stripes, or LVM2 volumes. For example:

	raw /dev/raw/raw1 /dev/sda
	raw /dev/raw/raw2 /dev/md1
	raw /dev/raw/raw3 /dev/vol1	

Oracle Database 9i and Oracle Database 10g support a variety of file systems under Linux to offer improved manageability, exposing the database files to the operating system for easy manipulation of files (such as moving, copying, backing up and restoring files for archival purposes, or when altering or expanding underlying storage). In doing so, most file systems implement a page or file cache which caches file I/O in the systems memory. This works very well for frequently accessed data for problem sizes that fit within the memory size of the systems.

Oracle, by design, uses memory for its database cache. Large shared memory segments are allocated at database startup for Oracle's Shared Global Area (SGA). Oracle Database Administrators (DBAs) adjust and tune the SGA for optimal performance of their databases. For frequently accessed database files, Oracle is already caching file I/O and handling data coherency within the database architecture. If the file system is also caching I/O memory, performance can actually suffer by "double caching" file I/O. For large databases, which greatly exceed the total memory of a system or for data access patterns with very little data re-use, performance can suffer.

Red Hat Enterprise Linux 2.1 and higher support the use of Direct I/O to the ext3 file system by opening the file with the O_DIRECT flag, a POSIX-compliant specification. Oracle can disable this "double caching" by providing init.ora options for opening the file with direct access to storage using the O_DIRECT flag upon opening the file

	filesystemio_options="DirectIO"
	

Figure 1 shows the comparison of raw versus ext3 file system with and without the use of Direct I/O for a 40 GB OLTP database and for a 100 GB decision support query with Oracle Database 10g 10.0.1.3.

Oracle Performance Tuning, 2nd Edition Chapter 10. Diagnostic and Tuning Tools

In this chapter:
MONITOR: Monitoring System Activity Tables
SQL_TRACE: Writing a Trace File
TKPROF: Interpreting the Trace File
EXPLAIN PLAN: Explaining the Optimizer's Plan
ORADBX: Listing Events
ANALYZE: Validating and Computing Statistics
UTLBSTAT.sql and UTLESTAT.sql: Taking Snapshots
Other Oracle Scripts
Some Scripts of Our Own
Oracle Performance Manager

b10752 Oracle® Database Performance Tuning Guide 10g Release 1 (10.1) Part No. B10752-01

Tuning Oracle DatabaseOracle® Database Administrator's Reference 10g Release 2 (10.2) for UNIX-Based Operating Systems Part Number B15658-06

This chapter describes how to tune Oracle Database. It contains the following sections:

Oracle Database is a highly optimizable software product. Frequent tuning optimizes system performance and prevents data bottlenecks.

Before tuning the database, you must observe its normal behavior by using the tools described in the "Operating System Tools" section.

Several operating system tools are available to enable you to assess database performance and determine database requirements. In addition to providing statistics for Oracle processes, these tools provide statistics for CPU usage, interrupts, swapping, paging, context switching, and I/O for the entire system.

This section provides information about the following common tools:

Watching Hard Drive Activity With iotop On Ubuntu 8.10 And Debian Lenny HowtoForge - Linux Howtos and Tutorials

For Suse 11 Simply type "yum install iotop". Iotop is licensed under the terms of the GNU GPL. The latest version is Iotop 0.3.2 (NEWS), available here : iotop-0.3.2.tar.bz2 or iotop-0.3.2.tar.gz.

Freshmeat project page to stay informed: http://freshmeat.net/projects/iotop.

I-O usage per process on Linux

That's probably will work only for commercial Linuxes released in 2010. Doers not work for Suse SP2 and RHEL 5.4. See also Compiling a new kernel (2.6.30.5) in Linux CentOS 5.3 / Red Hat 5.3
September 11, 2009 | Levent Serinol's Blog

Linux kernel 2.6.20 and later supports per process I/O accounting. You can access every process/thread's I/O read/write values by using /proc filesystem. You can check if your kernel has built with I/O account by just simply checking /proc/self/io file. If it exists then you have I/O accounting built-in.

$ cat /proc/self/io
rchar: 3809
wchar: 0
syscr: 10
syscw: 0
read_bytes: 0
write_bytes: 0
cancelled_write_bytes: 0
Field Descriptions:

rchar  - bytes read
wchar  - byres written
syscr  - number of read syscalls
syscw  - number of write syscalls
read_bytes  - number of bytes caused by this process to  read
            from underlying storage
write_bytes - number of bytes caused by this process to written from
            underlying storage
As you know, ever process is presented by it's pid number under /proc directory. You can access any process's I/O accounting values by just looking /proc/#pid/io file. There is a utility called iotop which collects these values and shows you in like top utility. You see your processes I/O activity with iotop utility.

IBM Redbooks Linux Performance and Tuning Guidelines

Abstract Over the past few years, Linux has made its way into the data centers of many corporations all over the globe. The Linux operating system has become accepted by both the scientific and enterprise user population. Today, Linux is by far the most versatile operating system. You can find Linux on embedded devices such as firewalls and cell phones and mainframes. Naturally, performance of the Linux operating system has become a hot topic for both scientific and enterprise users. However, calculating a global weather forecast and hosting a database impose different requirements on the operating system. Linux has to accommodate all possible usage scenarios with the most optimal performance. The consequence of this challenge is that most Linux distributions contain general tuning parameters to accommodate all users.

IBM® has embraced Linux, and it is recognized as an operating system suitable for enterprise-level applications running on IBM systems. Most enterprise applications are now available on Linux, including file and print servers, database servers, Web servers, and collaboration and mail servers.

With use of Linux in an enterprise-class server comes the need to monitor performance and, when necessary, tune the server to remove bottlenecks that affect users. This IBM Redpaper describes the methods you can use to tune Linux, tools that you can use to monitor and analyze server performance, and key tuning parameters for specific server applications. The purpose of this redpaper is to understand, analyze, and tune the Linux operating system to yield superior performance for any type of application you plan to run on these systems.

The tuning parameters, benchmark results, and monitoring tools used in our test environment were executed on Red Hat and Novell SUSE Linux kernel 2.6 systems running on IBM System x servers and IBM System z servers. However, the information in this redpaper should be helpful for all Linux hardware platforms.

Update 4/2008: Typos corrected

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SUSE Linux Enterprise Server System Analysis and Tuning Guide

Jun 25, 2012

Copyright © 2006–2012 Novell, Inc. and contributors. All rights reserved.

Over the past few years, Linux has made its way into the data centers of many corporations all over the globe. The Linux operating system has become accepted by both the scientific and enterprise user population. Today, Linux is by far the most versatile operating system. You can find Linux on embedded devices such as firewalls and cell phones and mainframes. Naturally, performance of the Linux operating system has become a hot topic for both scientific and enterprise users. However, calculating a global weather forecast and hosting a database impose different requirements on the operating system. Linux has to accommodate all possible usage scenarios with the most optimal performance. The consequence of this challenge is that most Linux distributions contain general tuning parameters to accommodate all users.

Linux Performance and Tuning Guidelines

June 05, 2007 | IBM Redbooks
Over the past few years, Linux has made its way into the data centers of many corporations all over the globe. The Linux operating system has become accepted by both the scientific and enterprise user population. Today, Linux is by far the most versatile operating system. You can find Linux on embedded devices such as firewalls and cell phones and mainframes. Naturally, performance of the Linux operating system has become a hot topic for both scientific and enterprise users. However, calculating a global weather forecast and hosting a database impose different requirements on the operating system. Linux has to accommodate all possible usage scenarios with the most optimal performance. The consequence of this challenge is that most Linux distributions contain general tuning parameters to accommodate all users.

IBM® has embraced Linux, and it is recognized as an operating system suitable for enterprise-level applications running on IBM systems. Most enterprise applications are now available on Linux, including file and print servers, database servers, Web servers, and collaboration and mail servers.

With use of Linux in an enterprise-class server comes the need to monitor performance and, when necessary, tune the server to remove bottlenecks that affect users. This IBM Redpaper describes the methods you can use to tune Linux, tools that you can use to monitor and analyze server performance, and key tuning parameters for specific server applications. The purpose of this redpaper is to understand, analyze, and tune the Linux operating system to yield superior performance for any type of application you plan to run on these systems.

The tuning parameters, benchmark results, and monitoring tools used in our test environment were executed on Red Hat and Novell SUSE Linux kernel 2.6 systems running on IBM System x servers and IBM System z servers. However, the information in this redpaper should be helpful for all Linux hardware platforms.

Update 4/2008: Typos corrected.

dkftpbench

http://www.kegel.com/

http://linuxperf.nl.linux.org/

http://www.citi.umich.edu/projects/citi-netscape/

NFS Performance Tunging

http://home.att.net/~jageorge/performance.html

http://www.linux.com/tuneup/

http://www.psc.edu/networking/perf_tune.html#Linux

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