Pablowe

Nagios Checks For MMM

I’ve written some new Nagios checks for MMM (MMM on Google Code … MMM on Launchpad). check_mmm is a part of http://code.google.com/p/check-mysql-all/, and is meant to be called locally on the MMM Monitor server (usually via NRPE). Feedback is welcome, usage is as follows:

Usage:
     check_mmm --cluster C# 

     Options:
       --cluster=    The MMM Cluster to check
       -c, --critical=
    The level at which a critical alarm is raised.
       -h, --help                Display this message and exit
       -v, --verbose             Increase verbosity level
       -V, --version             Display version information and exit
       -w, --warning             The level at which a warning is raised.

     Defaults are:

     ATTRIBUTE                  VALUE
     -------------------------- ------------------
     cluster                    No default value
     critical                   HARD_OFFLINE,REPLICATION_FAIL
     help                       FALSE
     verbose                    1 (out of 3)
     version                    FALSE
     warning                    ADMIN_OFFLINE,AWAITING_RECOVERY,REPLICATION_DELAY

Nagios MySQL Plug-Ins

There currently exist many plugins for MySQL to use with Nagios. Many of them, however, are not version-independent, leaving organizations that use multiple versions of MySQL to either install multiple plugins or not monitor specific versions of MySQL. As such, I’ve compiled what I consider to be the most useful checks into a single plugin: check_mysql

Usage:
     check_mysql check_name [options]

     Options:
       --args|a     Optional arguments.  Comma-separated.  Check-specific.
       --critical|c The level at which a critical alarm is raised.  Check-specific.
       --database   The database to use (defaults to mysql)
       --help|?     Display this message and exit
       --hostname|H     The target MySQL server host (defaults to localhost)
       --password|p The password of the MySQL user
       --port       The port MySQL is listening on (defaults to 3306)
       --user|u     The MySQL user used to connect
       --version|V  Display version information and exit
       --warning|w  The level at which a warning is raised.  Check-specific.

     defaults are:

     ATTRIBUTE                  VALUE
     -------------------------- ------------------
     args                       No default value
     critical                   Check-specific
     database                   mysql
     help                       FALSE
     host                       localhost
     password                   No default value
     port                       3306
     timeout                    10 seconds
     user                       No default value
     verbose                    1 (out of 3)
     version                    FALSE
     warning                    Check-specific

Current Checks Supported:

* connect – Check to see whether or not one can connect to MySQL (USAGE)
* repl_io – Check to see whether on not the IO Replication thread is running (REPLICATION CLIENT)
* repl_sql – Check to see whether or not the SQL Replication thread is running (REPLICATION CLIENT)
* repl_sbm – Check how many seconds behind the master the slave is (REPLICATION CLIENT)
* mysql_query – Run a given query, test if it executes properly (SELECT)
* connections – Test if the percentage of used connections is over a given threshold (PROCESS)

I am open to requests for additional checks etc.

The Awkward Stage of Scaling

A lot of my clients are in a position where their database performance is deteriorating but they are not “big enough” (or not willing/able to) explore sharding all of their data structures. They’re too big for the solution to be adding another read slave, but too small to justify the resources for re-designing their architecture. They’ve often implemented memcache, re-factored schema, and tried other ways to improve database performance but are looking for quick wins without the hassles & risks of full-fledged sharding. As such, I find myself regularly recommending that customers explore basic functional partitioning and “mini sharding”. It is a great way to stave off that inevitable day when you have to re-architect the entire application:)

If you are lucky enough to have built-in debug code and know which module is taking the most time, by all means ignore this list and separate that module from the core architecture if possible. If not, read on.

Registration

Your user table probably has a column like the following:

`status` enum('PENDING','ACTIVE','DELETED') NOT NULL default 'PENDING'

Where a user is ‘PENDING’ until they complete email verification. If you do a:

SELECT `status`, COUNT(*) FROM `user` GROUP BY `status`;

(go ahead and do it … I’ll wait)

You will probably notice that a lot of your users are ‘PENDING’ (my guess is ~20% … am I right?). If, upon registration, user records are placed in a pending_user until successfully completing email verification, the following benefits can be realized:

1) The number of records in the main user table is smaller. It is common for as many as 15-25% of new registrations to never complete email verification. Keeping them out of the main user table will slow the data/index size growth rate.
2) Queries against the user table will not be invalidated as often. Because of the way the MySQL query cache works, inserts into a table invalidate queries against the target table. By not inserting as many records into the table (see benefit #1), the queries do not get invalidated as often.
3) Queries using “WHERE `status` != ‘PENDING’” now don’t have to use that where clause. Conversely, queries looking only for records where `status` = ‘PENDING’ can query the pending_user table directly and not interfere with the *real* tables.

The same goes for *anything* that goes through an approval process (media, posts, etc). Put it in a pending table so that queries don’t have to have that extra WHERE clause.

Archive server(s)

The logical extension of separating PENDING records is to do the same for DELETED records. If deleted records (whether users or posts) are only used in specific queries, consider setting up archive_user or archive_post tables. This way, they can easily be moved to separate nodes and not waste storage/index space on your primary database servers.

Search

If search isn’t killing your database now, it probably will in the future. This is one of the easiest modules to detach from the primary database servers (it should simply involve changing your Search.class). Check out Sphinx, Lucene, or Solr. Because search tends to be widely used, this should free up the database to serve a higher volume of other queries.

Click-Tracking

Everybody wants to record what their users do, and when they do it. This can be the backbone of providing recommendations, UX research, and user profiling. It is important. But it is also write-heavy and can cause replication lag. With a little bit of work, the raw data can be separated from the core database server and written to different nodes. Some general thoughts on how to approach this:

- Log the clicks directly from http logs (set up a lightweight daemon on a dedicated node)
- Log clicks to a file and then periodically write to a database that is separate from your application (consider using LOAD DATA INFILE)
- Group the raw data by day/week/month/year and use partitioning
- Move data that is not actively used to another node (usually one with larger, slower disks)

The above recommendations are all relatively easy to implement and can provide tremendous benefit to your application. 64993021DF5E7E3652226B74779DCB92

Managing MySQL Configuration Files

It is good practice to manage changes to MySQL configuration files (/etc/my.cnf) by using a version control system. I usually use a home-brewed (not brewed by me!) svn+cfengine application to propagate my.cnf (and other configuration file) changes to defined classes of machines (classes are based on application role, replication role, etc).

When managing hundreds of different database servers with dozens of roles, templating my.cnf becomes a necessity! If I have to change a variable for a given class, that can mean editing a dozen my.cnf files on as many servers. Not a productive use of time!!! Usually, the only parameters that differ between database hosts in the same class are the replication options. As such, I find it useful to have a base template for each class of machine and use the !include startup option to specify host-specific startup options.

Here is a sample of what I would have as a base my.cnf for billing-class MySQL Replication Slaves:

And then I would store host-specific replication options in a smaller file:

To re-iterate, templating MySQL configuration files can help ensure consistency between servers of the same class as well as making it easier to push changes to all relevant hosts instead of doing it individually.

MySQL’s PAGER

Baron Schwartz wrote a neat article on MySQL’s pager command yesterday. As a followup, I thought I would post what I use as my default PAGER environmental variable. It simply substitutes mk-visual-explain for MySQL’s EXPLAIN command and uses less if the output is taller than your current terminal window (note, this currently renders \G non-functional):

#!/usr/bin/perl

use strict;
use warnings FATAL => ‘all’;
use English qw ( -no_match_vars );
use Term::ReadKey;

my $out;

while ( my $line = <STDIN>) {
$out .= $line;
}

# Log current result to a file (always useful)
open (PAGER_LOG, ‘>/tmp/mysql_pager.log’);
print PAGER_LOG “$out\n”;
close (PAGER_LOG);

# See if it is an EXPLAIN
eval {
local $SIG{’__WARN__’};
system(’/usr/local/bin/mk-visual-explain /tmp/mysql_pager.log 2> /dev/null’);
};

if ($?) {
# Use less if the output is taller than your terminal
my ( $cols, $lines ) = GetTerminalSize();
my @out_array = split("\n", $out);
if ( scalar ( @out_array ) > $lines ) {
system('less /tmp/mysql_pager.log');
} else {
print $out;
}
}

An up-to-date version will always be kept here

Using Nagios as a MySQL Performance Profiler

Everybody knows than Nagios can be used as a service monitor to monitor things like Load Averages, MySQL Replication Status, RAID Array States, etc… Fewer know that there are plug-ins to monitor MySQL Performance Status, such as check_mysql_perf. Fewer still utilize Nagios’ built-in triggering mechanism to execute an additional script on the event of a critical alert.

It is not uncommon to experience a load spike in the middle of the night, only to discover that it immediately cleared itself. Many times, retroactive log analysis will not reveal anything out of the ordinary. In order to get an immediate snapshot of what is going on at the time of a Nagios alert, simply call a script via the event handler similar to this one:

#!/usr/local/bin/bash

Usage() {
echo 1>&2 "Usage: $0 -h <hostname> -u <username> -p <password> -s <state> -t <state_type>"
exit 1
}

MYSQL="/usr/local/bin/mysql"
MAIL="/usr/bin/mail"
RECIPS="dba@domain.com"
PERL="/usr/bin/perl"
[ $# -ne 10 ] && Usage

while getopts "h:u:p:s:t:" option; do
case $option in
h ) HOSTNAME="$OPTARG";;
u ) USERNAME="$OPTARG";;
p ) PASSWORD="$OPTARG";;
s ) STATE="$OPTARG";;
t ) STATE_TYPE="$OPTARG";;
* ) Usage;; # DEFAULT
esac
done

[ $STATE = "CRITICAL" -a $STATE_TYPE = "HARD" ] || exit 0
$MYSQL -h$HOSTNAME -u$USERNAME -p$PASSWORD --connect_timeout=10 -ss -e'SHOW FULL PROCESSLIST' | $PERL -pe 's/\\n/\n/g' | $MAIL -s"$HOSTNAME post-alert processlist" $RECIPS
exit 0

This will email dba@domain.com with the output of SHOW FULL PROCESSLIST;

This type of profiling is especially useful because it can easily be turned on and off without affecting your production site (and it is very inexpensive to execute). Don’t forget to grant your Nagios user the PROCESS privilege!