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1 . MongoDB Monitoring and Performance
for The Savvy DBA
Key metrics to focus on for day-to-day MongoDB operations
Bimal Kharel
Senior Technical Services Engineer
Percona Webinar
2017-05-23
1 © 2017 Percona
2 .What I’ll cover
• Key commands to get the metrics
• Key metrics to graph and alert on
• Distinguish between MMAPv1 and WiredTiger storage
engine metrics wherever appropriate
• Show examples from our own PMM (free, open-source
monitoring tool from Percona)
2 © 2017 Percona
3 .Starting with key commands
In order of usefulness in day-to-day management
▪ db.serverStatus()
▪ rs.status()
▪ db.printReplicationInfo()
▪ sh.status()
▪ db.stats()
3 © 2017 Percona
4 .Operating system monitoring
OS level metrics you should set up alerts on and graph for
easy trend identification
▪ disk utilization
▪ load average and CPU queue
▪ memory and possibly swapping
▪ I/O utilization or a combination of load and latency
4 © 2017 Percona
5 .Data and operations growth - 1
sum up the collection sizes
db.getMongo().getDBNames().forEach(function(d) {
var curr_db = db.getSiblingDB(d);
var total_size = 0;
curr_db.getCollectionNames().forEach(function(coll) {
var coll_size =
curr_db.getCollection(coll).stats().storageSize;
total_size = total_size + coll_size;
});
print(d + ": " + total_size/(1024*1024));
});;
▪ Run the above against the admin database
5 © 2017 Percona
6 .Data and operations growth - 2
Keep track of operations and alert if they reach N times
your normal
▪ db.serverStatus()
- opcounters
- metrics.document
- metrics.commands
6 © 2017 Percona
7 .example (some output trimmed)
replset:PRIMARY> replset:PRIMARY>
db.serverStatus().opcounters db.serverStatus().metrics.commands
{ {
"insert" : 99992, ...
"query" : 10, "insert" : {
... "failed" : NumberLong(0),
} "total" : NumberLong(50046)
...
replset:PRIMARY> "serverStatus" : {
db.serverStatus().metrics.document "failed" : NumberLong(0),
{
"deleted" : NumberLong(0), "total" : NumberLong(5)
"inserted" : NumberLong(99992), },
"returned" : NumberLong(362720), ...
"updated" : NumberLong(0) }
}
7 © 2017 Percona
8 .Journaling
Journaling is on by default and should be left on. It is a
write-ahead log that persists writes to disk faster than
committing to the database
▪ For MMAP it will let the node recover data lost within 60s of a crash
▪ In WiredTiger it occurs every 50ms (100ms prior to 3.2) so it narrows
the window of data loss even further as checkpoints are taken every
60s.
8 © 2017 Percona
9 .flushing from memory to disk
For MMAP
▪ db.serverStatus()
- backgroundFlushing
For WiredTiger
▪ db.serverStatus()
- wiredTiger.transaction
9 © 2017 Percona
10 .Memory to disk operations
For MMAP
▪ db.serverStatus()
- extra_info.page_faults
For WiredTiger
▪ db.serverStatus()
- wiredtiger.cache
10 © 2017 Percona
11 .locking and tickets - 1
For MMAP
▪ db.serverStatus()
- globalLock
- locks
▪ locks
timeAcquiringMicros
and
acquireWaitCount
can help you spot trends
in average lock times
11 © 2017 Percona
12 .locking and tickets - 2
For WiredTiger
▪ db.serverStatus()
- wiredTiger.concurrentTransactions
12 © 2017 Percona
13 .connections, cursors and sessions - 1
▪ Badly designed apps will create a new connection for every query
▪ Each connection has a 1MB overhead so this can add up quickly
▪ All major drivers provide connection pooling
▪ db.serverStatus()
- globalLock.activeClients
- connections
- metrics.cursor
13 © 2017 Percona
14 .connections, cursors and sessions - 2
For WiredTiger in PMM we monitor sessions
db.serverStatus()
- wiredTiger.session
14 © 2017 Percona
15 .Replication metrics
Get information about the operations log (oplog)
▪ db.getReplicationInfo()
- logSizeMB
- usedMB
- timeDiffHours
15 © 2017 Percona
16 .replication lag and headroom -1
Lag is a derived value
▪ rs.status() replication lag
- members[].optimeDate
▪ it is the difference of between the
Primary and the Secondary nodes replication headroom
SECONDARY OPLOG
Headroom is also a derived value
▪ db.getReplicationInfo() PRIMARY OPLOG
- (timeDiffHours - lag time
(converted to hours))
16 © 2017 Percona
17 .replication lag and headroom -2
Replication lag and headroom graphs taken from PMM
17 © 2017 Percona
18 .sharding metrics - 1
Run against a mongos instance
▪ sh.status()
This returns a report rather than JSON so you may have to do
additional parsing or opt for
>use config
and run queries against the chunks, collections and shards
collections to access the metrics you want
Balancer commands
▪ - sh.getBalancerState()
- sh.isBalancerRunning()
18 © 2017 Percona
19 .sharding metrics - 2
Some sharding metrics from PMM
19 © 2017 Percona
20 .Time for questions and links
PMM - Percona Monitoring and Management
▪ https://www.percona.com/software/database-tools/percona-
monitoring-and-management
About me:
▪ Bimal Kharel
▪ bimal.kharel@percona.com
▪ 1-737-346-2418
20 © 2017 Percona
21 .About Percona
Solutions for your success with MySQL and MongoDB
Support, Managed Services, Software
Our Software is 100% Open Source
Support Broad Ecosystem – MySQL, MariaDB, Amazon RDS
In Business for 10 years
More than 3000 customers, including top Internet companies and
enterprises
21 © 2017 Percona
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