File: guestfs-performance.pod

package info (click to toggle)
libguestfs 1%3A1.54.1-2
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 98,892 kB
  • sloc: ansic: 379,443; ml: 38,771; sh: 10,329; java: 9,631; cs: 6,377; haskell: 5,729; makefile: 5,178; python: 3,821; perl: 2,467; erlang: 2,461; ruby: 349; xml: 275; pascal: 257; javascript: 157; cpp: 10
file content (519 lines) | stat: -rw-r--r-- 18,043 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
=head1 NAME

guestfs-performance - engineering libguestfs for greatest performance

=head1 DESCRIPTION

This page documents how to get the greatest performance out of
libguestfs, especially when you expect to use libguestfs to manipulate
thousands of virtual machines or disk images.

Three main areas are covered. Libguestfs runs an appliance (a small
Linux distribution) inside qemu/KVM.  The first two areas are:
minimizing the time taken to start this appliance, and the number of
times the appliance has to be started.  The third area is shortening
the time taken for inspection of VMs.

=head1 BASELINE MEASUREMENTS

Before making changes to how you use libguestfs, take baseline
measurements.

=head2 Baseline: Starting the appliance

On an unloaded machine, time how long it takes to start up the
appliance:

 time guestfish -a /dev/null run

Run this command several times in a row and discard the first few
runs, so that you are measuring a typical "hot cache" case.

I<Side note for developers:> There is a program called
F<boot-benchmark> in
L<https://github.com/libguestfs/libguestfs-analysis-tools> which does
the same thing, but performs multiple runs and prints the mean and
standard deviation.

=head3 Explanation

The guestfish command above starts up the libguestfs appliance on a
null disk, and then immediately shuts it down.  The first time you run
the command, it will create an appliance and cache it (usually under
F</var/tmp/.guestfs-*>).  Subsequent runs should reuse the cached
appliance.

=head3 Expected results

You should expect to be getting times under 6 seconds.  If the times
you see on an unloaded machine are above this, then see the section
L</TROUBLESHOOTING POOR PERFORMANCE> below.

=head2 Baseline: Performing inspection of a guest

For this test you will need an unloaded machine and at least one real
guest or disk image.  If you are planning to use libguestfs against
only X guests (eg. X = Windows), then using an X guest here would be
most appropriate.  If you are planning to run libguestfs against a mix
of guests, then use a mix of guests for testing here.

Time how long it takes to perform inspection and mount the disks of
the guest.  Use the first command if you will be using disk images,
and the second command if you will be using libvirt.

 time guestfish --ro -a disk.img -i exit

 time guestfish --ro -d GuestName -i exit

Run the command several times in a row and discard the first few runs,
so that you are measuring a typical "hot cache" case.

=head3 Explanation

This command starts up the libguestfs appliance on the named disk
image or libvirt guest, performs libguestfs inspection on it (see
L<guestfs(3)/INSPECTION>), mounts the guest’s disks, then discards all
these results and shuts down.

The first time you run the command, it will create an appliance and
cache it (usually under F</var/tmp/.guestfs-*>).  Subsequent runs
should reuse the cached appliance.

=head3 Expected results

You should expect times which are E<le> 5 seconds greater than
measured in the first baseline test above.  (For example, if the first
baseline test ran in 5 seconds, then this test should run in E<le> 10
seconds).

=head1 UNDERSTANDING THE APPLIANCE AND WHEN IT IS BUILT/CACHED

The first time you use libguestfs, it will build and cache an
appliance.  This is usually in F</var/tmp/.guestfs-*>, unless you have
set C<$TMPDIR> or C<$LIBGUESTFS_CACHEDIR> in which case it will be
under that temporary directory.

For more information about how the appliance is constructed, see
L<supermin(1)/SUPERMIN APPLIANCES>.

Every time libguestfs runs it will check that no host files used by
the appliance have changed.  If any have, then the appliance is
rebuilt.  This usually happens when a package is installed or updated
on the host (eg. using programs like C<yum> or C<apt-get>).  The
reason for reconstructing the appliance is security: the new program
that has been installed might contain a security fix, and so we want
to include the fixed program in the appliance automatically.

These are the performance implications:

=over 4

=item *

The process of building (or rebuilding) the cached appliance is slow,
and you can avoid this happening by using a fixed appliance (see
below).

=item *

If not using a fixed appliance, be aware that updating software on the
host will cause a one time rebuild of the appliance.

=item *

F</var/tmp> (or C<$TMPDIR>, C<$LIBGUESTFS_CACHEDIR>) should be on a
fast disk, and have plenty of space for the appliance.

=back

=head1 USING A FIXED APPLIANCE

To fully control when the appliance is built, you can build a fixed
appliance.  This appliance should be stored on a fast local disk.

To build the appliance, run the command:

 libguestfs-make-fixed-appliance <directory>

replacing C<E<lt>directoryE<gt>> with the name of a directory where
the appliance will be stored (normally you would name a subdirectory,
for example: F</usr/local/lib/guestfs/appliance> or
F</dev/shm/appliance>).

Then set C<$LIBGUESTFS_PATH> (and ensure this environment variable is
set in your libguestfs program), or modify your program so it calls
C<guestfs_set_path>.  For example:

 export LIBGUESTFS_PATH=/usr/local/lib/guestfs/appliance

Now you can run libguestfs programs, virt tools, guestfish etc. as
normal.  The programs will use your fixed appliance, and will not ever
build, rebuild, or cache their own appliance.

(For detailed information on this subject, see:
L<libguestfs-make-fixed-appliance(1)>).

=head2 Performance of the fixed appliance

In our testing we did not find that using a fixed appliance gave any
measurable performance benefit, even when the appliance was located in
memory (ie. on F</dev/shm>).  However there are two points to
consider:

=over 4

=item 1.

Using a fixed appliance stops libguestfs from ever rebuilding the
appliance, meaning that libguestfs will have more predictable start-up
times.

=item 2.

The appliance is loaded on demand.  A simple test such as:

 time guestfish -a /dev/null run

does not load very much of the appliance.  A real libguestfs program
using complicated API calls would demand-load a lot more of the
appliance.  Being able to store the appliance in a specified location
makes the performance more predictable.

=back

=head1 REDUCING THE NUMBER OF TIMES THE APPLIANCE IS LAUNCHED

By far the most effective, though not always the simplest way to get
good performance is to ensure that the appliance is launched the
minimum number of times.  This will probably involve changing your
libguestfs application.

Try to call C<guestfs_launch> at most once per target virtual machine
or disk image.

Instead of using a separate instance of L<guestfish(1)> to make a
series of changes to the same guest, use a single instance of
guestfish and/or use the guestfish I<--listen> option.

Consider writing your program as a daemon which holds a guest open
while making a series of changes.  Or marshal all the operations you
want to perform before opening the guest.

You can also try adding disks from multiple guests to a single
appliance.  Before trying this, note the following points:

=over 4

=item 1.

Adding multiple guests to one appliance is a security problem because
it may allow one guest to interfere with the disks of another guest.
Only do it if you trust all the guests, or if you can group guests by
trust.

=item 2.

There is a hard limit to the number of disks you can add to a single
appliance.  Call L<guestfs(3)/guestfs_max_disks> to get this limit.
For further information see L<guestfs(3)/LIMITS>.

=item 3.

Using libguestfs this way is complicated.  Disks can have unexpected
interactions: for example, if two guests use the same UUID for a
filesystem (because they were cloned), or have volume groups with the
same name (but see C<guestfs_lvm_set_filter>).

=back

L<virt-df(1)> adds multiple disks by default, so the source code for
this program would be a good place to start.

=head1 SHORTENING THE TIME TAKEN FOR INSPECTION OF VMs

The main advice is obvious: Do not perform inspection (which is
expensive) unless you need the results.

If you previously performed inspection on the guest, then it may be
safe to cache and reuse the results from last time.

Some disks don’t need to be inspected at all: for example, if you are
creating a disk image, or if the disk image is not a VM, or if the
disk image has a known layout.

Even when basic inspection (C<guestfs_inspect_os>) is required,
auxiliary inspection operations may be avoided:

=over 4

=item *

Mounting disks is only necessary to get further filesystem
information.

=item *

Listing applications (C<guestfs_inspect_list_applications>) is an
expensive operation on Linux, but almost free on Windows.

=item *

Generating a guest icon (C<guestfs_inspect_get_icon>) is cheap on
Linux but expensive on Windows.

=back

=head1 PARALLEL APPLIANCES

Libguestfs appliances are mostly I/O bound and you can launch multiple
appliances in parallel.  Provided there is enough free memory, there
should be little difference in launching 1 appliance vs N appliances
in parallel.

On a 2-core (4-thread) laptop with 16 GB of RAM, using the (not
especially realistic) test Perl script below, the following plot shows
excellent scalability when running between 1 and 20 appliances in
parallel:

  12 ++---+----+----+----+-----+----+----+----+----+---++
     +    +    +    +    +     +    +    +    +    +    *
     |                                                  |
     |                                               *  |
  11 ++                                                ++
     |                                                  |
     |                                                  |
     |                                          *  *    |
  10 ++                                                ++
     |                                        *         |
     |                                                  |
 s   |                                                  |
   9 ++                                                ++
 e   |                                                  |
     |                                     *            |
 c   |                                                  |
   8 ++                                  *             ++
 o   |                                *                 |
     |                                                  |
 n 7 ++                                                ++
     |                              *                   |
 d   |                           *                      |
     |                                                  |
 s 6 ++                                                ++
     |                      *  *                        |
     |                   *                              |
     |                                                  |
   5 ++                                                ++
     |                                                  |
     |                 *                                |
     |            * *                                   |
   4 ++                                                ++
     |                                                  |
     |                                                  |
     +    *  * *    +    +     +    +    +    +    +    +
   3 ++-*-+----+----+----+-----+----+----+----+----+---++
     0    2    4    6    8     10   12   14   16   18   20
               number of parallel appliances

It is possible to run many more than 20 appliances in parallel, but if
you are using the libvirt backend then you should be aware that out of
the box libvirt limits the number of client connections to 20.

The simple Perl script below was used to collect the data for the plot
above, but there is much more information on this subject, including
more advanced test scripts and graphs, available in the following blog
postings:

L<http://rwmj.wordpress.com/2013/02/25/multiple-libguestfs-appliances-in-parallel-part-1/>
L<http://rwmj.wordpress.com/2013/02/25/multiple-libguestfs-appliances-in-parallel-part-2/>
L<http://rwmj.wordpress.com/2013/02/25/multiple-libguestfs-appliances-in-parallel-part-3/>
L<http://rwmj.wordpress.com/2013/02/25/multiple-libguestfs-appliances-in-parallel-part-4/>

 #!/usr/bin/env perl
 
 use strict;
 use threads;
 use warnings;
 use Sys::Guestfs;
 use Time::HiRes qw(time);
 
 sub test {
     my $g = Sys::Guestfs->new;
     $g->add_drive_ro ("/dev/null");
     $g->launch ();
     
     # You could add some work for libguestfs to do here.
     
     $g->close ();
 }
 
 # Get everything into cache.
 test (); test (); test ();
 
 for my $nr_threads (1..20) {
     my $start_t = time ();
     my @threads;
     foreach (1..$nr_threads) {
         push @threads, threads->create (\&test)
     }
     foreach (@threads) {
         $_->join ();
         if (my $err = $_->error ()) {
             die "launch failed with $nr_threads threads: $err"
         }
     }
     my $end_t = time ();
     printf ("%d %.2f\n", $nr_threads, $end_t - $start_t);
 }

=head1 TROUBLESHOOTING POOR PERFORMANCE

=head2 Ensure hardware virtualization is available

Use F</proc/cpuinfo> to ensure that hardware virtualization is
available.  Note that you may need to enable it in your BIOS.

Hardware virt is not usually available inside VMs, and libguestfs will
run slowly inside another virtual machine whatever you do.  Nested
virtualization does not work well in our experience, and is certainly
no substitute for running libguestfs on baremetal.

=head2 Ensure KVM is available

Ensure that KVM is enabled and available to the user that will run
libguestfs.  It should be safe to set 0666 permissions on F</dev/kvm>
and most distributions now do this.

=head2 Processors to avoid

Avoid processors that don’t have hardware virtualization, and some
processors which are simply very slow (AMD Geode being a great
example).

=head2 Xen dom0

In Xen, dom0 is a virtual machine, and so hardware virtualization is
not available.

=head2 Use libguestfs E<ge> 1.34 and qemu E<ge> 2.7

During the libguestfs 1.33 development cycle, we spent a large amount
of time concentrating on boot performance, and added some patches to
libguestfs, qemu and Linux which in some cases can reduce boot times
to well under 1 second.  You may therefore get much better performance
by moving to the versions of libguestfs or qemu mentioned in the
heading.

=head1 DETAILED ANALYSIS

=head2 Boot analysis

In L<https://github.com/libguestfs/libguestfs-analysis-tools> is a
program called C<boot-analysis>.  This program is able to produce a
very detailed breakdown of the boot steps (eg. qemu, BIOS, kernel,
libguestfs init script), and can measure how long it takes to perform
each step.

=head2 Detailed timings using ts

Use the L<ts(1)> command (from moreutils) to show detailed
timings:

 $ guestfish -a /dev/null run -v |& ts -i '%.s'
 0.000022 libguestfs: launch: program=guestfish
 0.000134 libguestfs: launch: version=1.29.31fedora=23,release=2.fc23,libvirt
 0.000044 libguestfs: launch: backend registered: unix
 0.000035 libguestfs: launch: backend registered: uml
 0.000035 libguestfs: launch: backend registered: libvirt
 0.000032 libguestfs: launch: backend registered: direct
 0.000030 libguestfs: launch: backend=libvirt
 0.000031 libguestfs: launch: tmpdir=/tmp/libguestfsw18rBQ
 0.000029 libguestfs: launch: umask=0002
 0.000031 libguestfs: launch: euid=1000
 0.000030 libguestfs: libvirt version = 1002012 (1.2.12)
 [etc]

The timestamps are seconds (incrementally since the previous line).

=head2 Detailed debugging using gdb

You can attach to the appliance BIOS/kernel using gdb.  If you know
what you're doing, this can be a useful way to diagnose boot
regressions.

Firstly, you have to change qemu so it runs with the C<-S> and C<-s>
options.  These options cause qemu to pause at boot and allow you to
attach a debugger.  Read L<qemu(1)> for further information.
Libguestfs invokes qemu several times (to scan the help output and so
on) and you only want the final invocation of qemu to use these
options, so use a qemu wrapper script like this:

 #!/bin/bash -
 
 # Set this to point to the real qemu binary.
 qemu=/usr/bin/qemu-kvm
 
 if [ "$1" != "-global" ]; then
     # Scanning help output etc.
     exec $qemu "$@"
 else 
     # Really running qemu.
     exec $qemu -S -s "$@"
 fi

Now run guestfish or another libguestfs tool with the qemu wrapper
(see L<guestfs(3)/QEMU WRAPPERS> to understand what this is doing):

 LIBGUESTFS_HV=/path/to/qemu-wrapper guestfish -a /dev/null -v run

This should pause just after qemu launches.  In another window, attach
to qemu using gdb:

 $ gdb
 (gdb) set architecture i8086
 The target architecture is assumed to be i8086
 (gdb) target remote :1234
 Remote debugging using :1234
 0x0000fff0 in ?? ()
 (gdb) cont

At this point you can use standard gdb techniques, eg. hitting C<^C>
to interrupt the boot and C<bt> get a stack trace, setting
breakpoints, etc.  Note that when you are past the BIOS and into the
Linux kernel, you'll want to change the architecture back to 32 or 64
bit.

=head1 PERFORMANCE REGRESSIONS IN OTHER PROGRAMS

Sometimes performance regressions happen in other programs (eg. qemu,
the kernel) that cause problems for libguestfs.

In L<https://github.com/libguestfs/libguestfs-analysis-tools>
F<boot-benchmark/boot-benchmark-range.pl> is a script which can
be used to benchmark libguestfs across a range of git commits in
another project to find out if any commit is causing a slowdown (or
speedup).

To find out how to use this script, consult the manual:

 ./boot-benchmark/boot-benchmark-range.pl --man

=head1 SEE ALSO

L<supermin(1)>,
L<guestfish(1)>,
L<guestfs(3)>,
L<guestfs-examples(3)>,
L<guestfs-internals(1)>,
L<libguestfs-make-fixed-appliance(1)>,
L<stap(1)>,
L<qemu(1)>,
L<gdb(1)>,
L<http://libguestfs.org/>.

=head1 AUTHORS

Richard W.M. Jones (C<rjones at redhat dot com>)

=head1 COPYRIGHT

Copyright (C) 2012-2023 Red Hat Inc.