Hi Craig,
It sounds Robinhood v3 would perfectly match you need to manage these
multiple use-cases in a single robinhood instance. This is basically
what it is designed for. This major version is currently under
development, and it will likely be available in 2H2015. Not sure how it
fits in your planning...
Depending on your time requirement to setup these use-cases into full
production, you could get an early version of robinhood early 2015 that
do not implement all planned features of rbhv3, but at least implements
lhsm archiving and pool to pool migration in a single instance.
If you agree for such a early testing phase, just let us know.
I believe this answers to your question 1).
2) lhsm and tmpfs can run on the same client, as long as they are
registered as different changelog readers, and access distinct databases.
I'd be concerned about a fight between the 2 instances for realeasing
disk space in ost pools: one will want to run "lhsm release", and the
other "lfs migrate". However, I understood you just want to replicate
data with lhsm, but don't plan to "release" it. So will be OK.
3) A few recommandations:
- Keep your robinhood client as close to the MDS as possible: no
access through LNET routers that would introduce an extra latency for
Lustre RPCs.
- I'm not sure running the DB on a different host is a good idea because
it introduces a network latency for robinhood DB requests, whereas they
must fire at tens of thousands per seconde to sustain the filesystem
workload.
The robinhood daemon itself doesn't require much memory or CPU, so it
can perfectly live with a DB engine on the same host.
- It is not expected that the database size changes a lot between Lustre
1.8 and 2.5. Most of the space is consumed by namespace management and
storage of stripe information, that are about the same between the 2
versions. Only one or 2 more table fields for Lustre/HSM, so not a lot
of additionnal space.
- Tune your /etc/my.cnf (we can provide you examples).
- For the HW:
* It is nice to have most of the DB in memory: 1k/entry is a good
sizing (e.g. 128GB of memory for 128M entries). In the case you need to
run 2 robinhood DB on the same host, you'll have to double it.
* Of course, a fast DB backend like a SSD is better than a spinning
disk (some benchmarks here:
https://github.com/cea-hpc/robinhood/wiki/tmpfs_admin_guide#entry-processor-pipeline-options)
Regards,
Thomas
On 11/25/14 20:39, Prescott,Craig P wrote:
Hello,
A few months back we took a look at Robinhood Policy Engine on a
Lustre 2.5.x testbed with eyes toward accomplishing two main goals: a)
automatic migration between OST pools based upon atime without
changing the path, and b) replication of particular data to an
external file system. It seemed like current Robinhood software
releases could do this by running a tmpfs manager with a custom purge
command (lfs migrate) to handle the migration between pools, and an
lhsm manager for the replication.
With upgrade and expansion our production file system from 1.8.9 to
2.5 being planned for the new year (new system), we are considering
how to best bring the above two goals into production. We want have
the Robinhood components we need in place when the new system goes
into production, and we want to avoid ever having to rescan the file
system. So I have the following questions I hope I can get some input on:
1)At the time I was looking, the lhsm manager could not have a custom
purge command (appended). If it could, then we would only need to run
the lhsm manager, which would be ideal - it could handle both of our
use cases and we could have a single changelog reader and a single
database. Is this possible with current software releases?
2)If we need to run both lhsm and tmpfs managers, can they be run
simultaneously from the same client?
3)We intend to use a database running on a different node than the
Robinhood managers. I am not sure how to wisely choose HW for mysqld
to keep up with the changelogs. We can use stats from our current
1.8.9-based file system and cluster activity to size this, but I’m not
sure what to look at. Any pointers here?
Thanks,
Craig Prescott
UF Research Computing
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