docs: update and re-record profile graphs in docs; closes #505

pcaps moved to 'pcaps' branch.
pull/564/head
David Wilson 5 years ago
parent 54835d4c9b
commit c279454502

@ -1168,35 +1168,96 @@ FreeNode IRC network.
Sample Profiles
---------------
Local VM connection
~~~~~~~~~~~~~~~~~~~
The summaries below may be reproduced using data and scripts maintained in the
`pcaps branch <https://github.com/dw/mitogen/tree/pcaps/>`_. Traces were
recorded using Ansible 2.5.14.
Trivial Loop: Local Host
~~~~~~~~~~~~~~~~~~~~~~~~
This demonstrates Mitogen vs. SSH pipelining to the local machine running
`bench/loop-100-items.yml
<https://github.com/dw/mitogen/blob/master/tests/ansible/bench/loop-100-items.yml>`_,
executing a simple command 100 times. Most Ansible controller overhead is
isolated, characterizing just module executor and connection layer performance.
Mitogen requires **63x less bandwidth, 5.9x less time, and 1.5x less CPU**.
.. image:: images/ansible/pcaps/loop-100-items-local.svg
Unlike in SSH pipelining where payloads are sent as a single compressed block,
by default Mitogen enables SSH compression for its uncompressed RPC data. In
many-host scenarios it may be desirable to disable compression. This has
negligible impact on footprint, since program code is separately compressed and
sent only once. Compression also benefits SSH pipelining, but the presence of
large precompressed per-task payloads may present a more significant CPU burden
during many-host runs.
File Transfer: UK to France
~~~~~~~~~~~~~~~~~~~~~~~~~~~
`This playbook
<https://github.com/dw/mitogen/blob/master/tests/ansible/regression/issue_140__thread_pileup.yml>`_
was used to compare file transfer performance over a ~26 ms link. It uses the
``with_filetree`` loop syntax to copy a directory of 1,000 0-byte files to the
target.
This demonstrates Mitogen vs. connection pipelining to a local VM executing
``bench/loop-100-items.yml``, which simply executes ``hostname`` 100 times.
Mitogen requires **43x less bandwidth and 6.5x less time**.
.. raw:: html
<style>
.nojunk td,
.nojunk th { padding: 4px; font-size: 90%; text-align: right !important; }
table.docutils col {
width: auto !important;
}
</style>
.. csv-table::
:header: , Secs, CPU Secs, Sent, Received, Roundtrips
:class: nojunk
:align: right
Mitogen, 98.54, 43.04, "815 KiB", "447 KiB", 3.79
SSH Pipelining, "1,483.54", 329.37, "99,539 KiB", "6,870 KiB", 57.01
*Roundtrips* represents the approximate number of network roundtrips required
to describe the runtime that was consumed. Due to Mitogen's built-in file
transfer support, continuous reinitialization of an external `scp`/`sftp`
client is avoided, permitting large ``with_filetree`` copies to become
practical without any special casing within the playbook or the Ansible
implementation.
DebOps: UK to India
~~~~~~~~~~~~~~~~~~~
.. image:: images/ansible/run_hostname_100_times_mito.svg
.. image:: images/ansible/run_hostname_100_times_plain.svg
This is an all-green run of 246 tasks from the `DebOps
<https://docs.debops.org/en/master/>`_ 0.7.2 `common.yml
<https://github.com/debops/debops-playbooks/blob/master/playbooks/common.yml>`_
playbook over a ~370 ms link between the UK and India. The playbook touches a
wide variety of modules, many featuring unavoidable waits for slow computation
on the target.
More tasks of a wider variety are featured than previously, placing strain on
Mitogen's module loading and in-memory caching. By running over a long-distance
connection, it highlights behaviour of the connection layer in the presence of
high latency.
Kathmandu to Paris
~~~~~~~~~~~~~~~~~~
Mitogen requires **14.5x less bandwidth, 4x less time, and 2.3x less CPU**.
This is a full Django application playbook over a ~180ms link between Kathmandu
and Paris. Aside from large pauses where the host performs useful work, the
high latency of this link means Mitogen only manages a 1.7x speedup.
.. image:: images/ansible/pcaps/debops-uk-india.svg
Many early roundtrips are due to inefficiencies in Mitogen's importer that will
be fixed over time, however the majority, comprising at least 10 seconds, are
due to idling while the host's previous result and next command are in-flight
on the network.
The initial extension lays groundwork for exciting structural changes to the
execution model: a future version will tackle latency head-on by delegating
some control flow to the target host, melding the performance and scalability
benefits of pull-based operation with the management simplicity of push-based
operation.
Django App: UK to India
~~~~~~~~~~~~~~~~~~~~~~~
.. image:: images/ansible/costapp.png
This short playbook features only 23 steps executed over the same ~370 ms link
as previously, with many steps running unavoidably expensive tasks like
building C++ code, and compiling static web site assets.
Despite the small margin for optimization, Mitogen still manages **6.2x less
bandwidth, 1.8x less time, and 2x less CPU**.
.. image:: images/ansible/pcaps/costapp-uk-india.svg

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*.pcapng filter=lfs diff=lfs merge=lfs -text
**pcap** filter=lfs diff=lfs merge=lfs -text
run_hostname_100_times_mito.pcap.gz filter=lfs diff=lfs merge=lfs -text
run_hostname_100_times_vanilla.pcap.gz filter=lfs diff=lfs merge=lfs -text

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import sys
# Add viewBox attr to SVGs lacking it, so IE scales properly.
import lxml.etree
import glob
for name in sys.argv[1:]: # glob.glob('*/*.svg'): #+ glob.glob('images/ansible/*.svg'):
doc = lxml.etree.parse(open(name))
svg = doc.getroot()
for elem in svg.cssselect('[stroke-width]'):
if elem.attrib['stroke-width'] < '2':
elem.attrib['stroke-width'] = '2'
open(name, 'w').write(lxml.etree.tostring(svg, xml_declaration=True, encoding='UTF-8'))

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