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Merge "Add some tuning documentation"

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Zuul 1 week ago
committed by Gerrit Code Review
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doc/source/admin/drivers/ipa.rst View File

@ -44,6 +44,8 @@ Requirements
Using IPA requires it to be present and configured on the deploy ramdisk, see
:ref:`deploy-ramdisk`
.. _ipa-proxies:
Using proxies for image download
================================


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@ -53,6 +53,7 @@ Advanced Topics
Agent Token <agent-token>
Deploying without BMC Credentials <agent-power>
Layer 3 or DHCP-less Ramdisk Booting <dhcp-less>
Tuning Ironic <tuning>
.. toctree::
:hidden:


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=============
Tuning Ironic
=============
Memory Utilization
==================
Memory utilization is a difficult thing to tune in Ironic as largely we may
be asked by API consumers to perform work for which the underlying tools
require large amounts of memory.
The biggest example of this is image conversion. Images not in a raw format
need to be written out to disk (local files or remote in iscsi deploy) which
requires the conversion process to generate an in-memory map to re-assemble
the image contents into a coherent stream of data. This entire process also
stresses the kernel buffers and cache.
This ultimately comes down to a trade-off of Memory versus Performance,
similar to the trade-off of Performance versus Cost.
On a plus side, an idle Ironic deployment does not need much in the way
of memory. On the down side, a highly bursty environment where a large
number of concurrent deployments may be requested should consider two
aspects:
* How is the ironic-api service/process set up? Will more
processes be launched automatically?
* Are images prioritized for storage size on disk? Or are they compressed and
require format conversion?
API
===
Ironic's API should have a fairly stable memory footprint with activity,
however depending on how the webserver is running the API, additional
processes can be launched.
Under normal conditions, as of Ironic 15.1, the ``ironic-api`` service/process
consumes approximately 270MB of memory per worker. Depending on how the
process is being launched, the number of workers and maximum request threads
per worker may differ. Naturally there are configuration and performance
trade-offs.
* Directly as a native python process, i.e. execute ``ironic-api``
processes. Each single worker allows for multiple requests to be handled
and threaded at the same time which can allow high levels of request
concurrency. As of the Victoria cycle, a direct invocation of the
``ironic-api`` program will only launch a maximum of four workers.
* Launched via a wrapper such as Apache+uWSGI may allow for multiple distinct
worker processes, but these workers typically limit the number of request
processing threads that are permitted to execute. This means requests can
stack up in the front-end webserver and be released to the ``ironic-api``
as prior requests complete. In environments with long running synchronous
calls, such as use of the vendor passthru interface, this can be very
problematic.
When the webserver is launched by the API process directly, the default is
based upon the number of CPU sockets in your machine.
When launching using uwsgi, this will entirely vary upon your configuration,
but balancing workers/threads based upon your load and needs is highly
advisable. Each worker process is unique and consumes far more memory than
a comparable number of worker threads. At the same time, the scheduler will
focus on worker processes as the threads are greenthreads.
.. note::
Host operating systems featuring in-memory de-duplication should see
an improvement in the overall memory footprint with multiple processes,
but this is not something the development team has measured and will vary
based upon multiple factors.
One important item to note: each Ironic API service/process *does* keep a
copy of the hash ring as generated from the database *in-memory*. This is
done to help allocate load across a cluster in-line with how individual nodes
and their responsible conductors are allocated across the cluster.
In other words, your amount of memory WILL increase corresponding to
the number of nodes managed by each ironic conductor. It is important
to understand that features such as `conductor groups <./conductor-groups.rst>`_
means that only matching portions of nodes will be considered for the
hash ring if needed.
Conductor
=========
A conductor process will launch a number of other processes, as required,
in order to complete the requested work. Ultimately this means it can quickly
consume large amounts of memory because it was asked to complete a substantial
amount of work all at once.
The ``ironic-conductor`` from ironic 15.1 consumes by default about 340MB of
RAM in an idle configuration. This process, by default, operates as a single
process. Additional processes can be launched, but they must have unique
resolvable hostnames and addresses for JSON-RPC or use a central
oslo.messaging supported message bus in order for Webserver API to Conductor
API communication to be functional.
Typically, the most memory intensive operation that can be triggered is a
image conversion for deployment, which is limited to 1GB of RAM per conversion
process.
Most deployments, by default, do have a concurrency limit depending on their
Compute (See `nova.conf <https://docs.openstack.org/nova/latest/configuration/sample-config.html>`_
setting ``max_concurrent_builds``) configuration. However, this is only per
``nova-compute`` worker, so naturally this concurrency will scale with
additional workers.
Stand-alone users can easily request deployments exceeding the Compute service
default maximum concurrent builds. As such, if your environment is used this
way, you may wish to carefully consider your deployment architecture.
With a single nova-compute process talking to a single conductor, asked to
perform ten concurrent deployments of images requiring conversion, the memory
needed may exceed 10GB. This does however, entirely depend upon image block
structure and layout, and what deploy interface is being used.
What can I do?
==============
Previously in this document, we've already suggested some architectural
constraints and limitations, but there are some things that can be done
to maximize performance. Again, this will vary greatly depending on your
use.
* Use the ``direct`` deploy interface. This offloads any final image
conversion to the host running the ``ironic-python-agent``. Additionally,
if Swift or other object storage such as RadosGW is used, downloads can
be completely separated from the host running the ``ironic-conductor``.
* Use small/compact "raw" images. Qcow2 files are generally compressed
and require substantial amounts of memory to decompress and stream.
* Tune the internal memory limit for the conductor using the
``[DEFAULT]memory_required_minimum`` setting. This will help the conductor
throttle back memory intensive operations. The default should prevent
Out-of-Memory operations, but under extreme memory pressure this may
still be sub-optimal. Before changing this setting, it is highly advised
to consult with your resident "Unix wizard" or even the Ironic
development team in upstream IRC. This feature was added in the Wallaby
development cycle.
* If network bandwidth is the problem you are seeking to solve for, you may
wish to explore a mix of the ``direct`` deploy interface and caching
proxies. Such a configuration can be highly beneficial in wide area
deployments. See :ref:`Using proxies for image download <ipa-proxies>`.

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