Lustre Monitoring and Statistics Guide: Difference between revisions

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Here are some basic steps for working with the Lustre statistics.  
Here are some basic steps for working with the Lustre statistics.  
# *Gather* the data on hosts you are monitoring. Deal with the syntax, extract what you want
# '''Gather''' the data on hosts you are monitoring. Deal with the syntax, extract what you want
# *Collect* the data centrally - either pull or push it to your server, or collection of monitoring servers.
# '''Collect''' the data centrally - either pull or push it to your server, or collection of monitoring servers.
# *Process* the data - this may be optional or minimal.
# '''Process''' the data - this may be optional or minimal.
# *Alert* on the data - optional but often useful.
# '''Alert''' on the data - optional but often useful.
# *Present* the data - allow for visualization, analysis, etc.
# '''Present''' the data - allow for visualization, analysis, etc.
 


collectl / ganglia
collectl / ganglia

Revision as of 13:35, 5 November 2014

DRAFT IN PROGRESS

Introduction

There are a variety of useful statistics and counters available on Lustre servers and clients. This is an attempt to detail some of these statistics and methods.

This does not include Lustre log analysis.

The presumed audience for this is system administrators attempting to better understand and monitor their Lustre file systems.

Lustre Versions

This information is based on working mostly with Lustre 2.4 and 2.5.

Reading /proc vs lctl

'cat /proc/fs/lustre...' vs 'lctl get_param' With newer Lustre versions, 'lctl get_pram' is the standard and recommended way to get these stats. This is to insure portability. I will use this method in all examples, a bonus is it can be often be a little shorter syntax.

Data Formats

Format of the various statistics type files varies (and I'm not sure if there is any reason for this). The format names here are entirely *my invention*, this isn't a standard for Lustre or anything.

It is useful to know the various formats of these files so you can parse the data and collect for use in other tools.

Stats

What I consider a "standard" stats files include for example each OST or MDT as a multi-line record, and then just the data.

Example:

obdfilter.scratch-OST0001.stats=
snapshot_time             1409777887.590578 secs.usecs
read_bytes                27846475 samples [bytes] 4096 1048576 14421705314304
write_bytes               16230483 samples [bytes] 1 1048576 14761109479164
get_info                  3735777 samples [reqs]

snapshot_time = when the stats were written

For read_bytes and write_bytes: First number = number of times (samples) the OST has handled a read or write. Second number = the minimum read/write size Third number = maximum read/write size Fourth = sum of all the read/write requests in bytes, the quantity of data read/written.

Jobstats

Jobstats are slightly more complex multi-line records. Each OST or MDT also has an entry for each jobid (or procname_uid perhaps), and then the data.

Example:

obdfilter.scratch-OST0000.job_stats=job_stats:
- job_id:          56744
  snapshot_time:   1409778251
  read:            { samples:       18722, unit: bytes, min:    4096, max: 1048576, sum:     17105657856 }
  write:           { samples:         478, unit: bytes, min:    1238, max: 1048576, sum:       412545938 }
  setattr:         { samples:           0, unit:  reqs }  punch:           { samples:          95, unit:  reqs }
- job_id: . . . ETC

Notice this is very similar to 'stats' above. But there's a lot of extra: { bling: }! Why? Just because it got coded that way?

Single

These really boil down to just a single number in a file. But if you use "lctl get_param" you get an output that is nice for parsing. For example:

[COMMAND LINE]# lctl get_param osd-ldiskfs.*OST*.kbytesavail


osd-ldiskfs.scratch-OST0000.kbytesavail=10563714384
osd-ldiskfs.scratch-OST0001.kbytesavail=10457322540
osd-ldiskfs.scratch-OST0002.kbytesavail=10585374532

Histogram

Some stats are histograms, these types aren't covered here. Typically they're useful on their own without further parsing(?)


  • brw_stats
  • extent_stats


Interesting Statistics Files

This is a collection of various stats files that I have found useful. It is *not* complete or exhaustive. For example, you will noticed these are mostly server stats. There are a wealth of client stats too not detailed here. Additions or corrections are welcome.

  • Host Type = MDS, OSS, client
  • Target = "lctl get_param target"
  • Format = data format discussed above
Host Type Target Format Discussion
MDS mdt.*MDT*.num_exports single number of exports per MDT - these are clients, including other lustre servers
MDS mdt.*.job_stats jobstats Metadata jobstats. Note that with lustre DNE you may have more than one MDT, so even if you don't it may be wise to design any tools with that assumption.
OSS obdfilter.*.job_stats jobstats the per OST jobstats.
MDS mdt.*.md_stats stats Overall metadata stats per MDT
MDS mdt.*MDT*.exports.*@*.stats stats Per-export metadata stats. Exports are clients, this also includes other lustre servers. The exports are named by interfaces, which can be unweildy. See "lltop" for an example of a script that used this data well. The sum of all the export stats should provide the same data as md_stats, but it is still very convenient to have md_stats, "ltop" uses them for example.
OSS obdfilter.*.stats stats Operations per OST. Read and write data is particularly interesting
OSS obdfilter.*OST*.exports.*@*.stats stats per-export OSS statistics
MDS osd-*.*MDT*.filesfree or filestotal single available or total inodes
MDS osd-*.*MDT*.kbytesfree or kbytestotal single available or total disk space
OSS obdfilter.*OST*.kbytesfree or kbytestotal, filesfree, filestotal single inodes and disk space as in MDS version
OSS ldlm.namespaces.filter-*.pool.stats stats lustre distributed lock manager (ldlm) stats. I do not fully understand all of these stats. It also appears that these same stats are duplicated a single stats. Perhaps this is just a convenience.
OSS ldlm.namespaces.filter-*.lock_count single lustre distributed lock manager (ldlm) locks
OSS ldlm.namespaces.filter-*.pool.granted single lustre distributed lock manager (ldlm) granted locks - normally this matches lock_count. I am not sure of what the differences are, or what it means when they don't match.
OSS ldlm.namespaces.filter-*.pool.grant_rate single ldlm lock grant rate aka 'GR'
OSS ldlm.namespaces.filter-*.pool.grant_speed single ldlm lock grant speed = grant_rate - cancel_rate. You can use this to derive cancel_rate 'CR'. Or you can just get 'CR' from the stats file I assume.

Working With the Data

Packages, tools, and techniques for working with Lustre statistics.

Open Source Monitoring Packages

  • LMT
  • lltop and xltop

Commercial Monitoring Packages

  • Terascala 'teraos'
  • DDN datablarker
  • Intel Enterprise Edition for Linux Managerator

Build it Yourself

Here are some basic steps for working with the Lustre statistics.

  1. Gather the data on hosts you are monitoring. Deal with the syntax, extract what you want
  2. Collect the data centrally - either pull or push it to your server, or collection of monitoring servers.
  3. Process the data - this may be optional or minimal.
  4. Alert on the data - optional but often useful.
  5. Present the data - allow for visualization, analysis, etc.


collectl / ganglia -note recent changes

NCI mysterious project

Analyze, Visualize, Present data

logstash as collector - Brock Palen http://www.failureasaservice.com/2014/10/lustre-stats-with-graphite-and-logstash.html



References and Links