Deployment Strategy
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The document provides guidance on deploying MongoDB in production environments. It discusses sizing hardware requirements for memory, CPU, and disk I/O. It also covers installing and upgrading MongoDB, considerations for cloud platforms like EC2, security, backups, durability, scaling out, and monitoring. The focus is on performance optimization and ensuring data integrity and high availability.
Deployment Strategy
- 1. Thoughts on Deployment [email protected] @rogerb
- 2. Congratulations ! Development done ? Great ! Ready to Deploy :-)
- 3. some points to consider
- 4. Agenda • A word on performance • Sizing Your Hardware • memory / cpu / disk io • Software • os / filesystem • Installing MongoDB / Upgrades • EC2 Notes • Security • Backup • Durability • Upgrading • Monitoring • Scaling out
- 5. A Word on Performance • Ensure your queries are being executed correctly • Enable profiling • db.setProfilingLevel(n) • n=1: slow operations, n=2: all operations • Viewing profile information • db.system.profile.find({info: /test.foo/}) •http://www.mongodb.org/display/DOCS/Database+Profiler • Query execution plan: •db.xx.find({..}).explain() •http://www.mongodb.org/display/DOCS/Optimization • Make sure your Queries are properly indexed.
- 6. Sizing Hardware: Memory • Working set should be as much in memory as possible, but • your whole data set doesn’t have to •Memory Mapped files • Maps Files on Filesystem to Virtual Memory • Not Physical RAM • Page Faults - not in memory - from disk - expensive • Indices • Part of the regular DB files • Consider Warm Starting your Database
- 7. Sizing Hardware: CPU • MongoDB uses multiple cores • For working-set queries, CPU usage is minimal • Generally, faster CPU are better • Aggregation, Full Tablescans •Makes heavy use of CPU / Disk •Instead of counting / computing: • cache / precompute • Map Reduce • Currently Single threaded •Can be run in parallel across shards. • This restriction may be eliminated, investigating options
- 8. Sizing Hardware: I/O • Disk I/O determines performance of non-working set queries • More Disks = Better • Improved throughput, Reduced Seek times • Raid 0 - Striping: improved write performance • Raid 1 - Mirroring: survive single disk failure • Raid 10 - both • Consider Flash ? • Expensive, getting cheaper • Significantly reduced seek time, increased IO throughput • Network • It’s easy to saturate your network • (Average doc size * number of document writes, reads) / sec
- 9. MongoStat • Tool that comes with MongoDB • Shows • counters for I/O, time spent in write lock, ...
- 10. IOStat iostat ‐x 2 iostat ‐w 1 disk0 disk1 disk2 cpu load average KB/t tps MB/s KB/t tps MB/s KB/t tps MB/s us sy id 1m 5m 15m 12.83 3 0.04 2.01 0 0.00 12.26 2 0.02 11 5 83 0.35 0.26 0.25 11.12 75 0.81 0.00 0 0.00 0.00 0 0.00 60 24 16 0.68 0.34 0.28 4.00 3 0.01 0.00 0 0.00 0.00 0 0.00 60 23 17 0.68 0.34 0.28 avg-cpu: %user %nice %system %iowait %steal %idle 0.00 0.00 7.96 29.85 0.50 61.69 Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s avgrq-sz avgqu-sz await svctm %util sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.50 4761.19 6.47 837.31 75.62 43681.59 51.86 38.38 42.33 0.46 38.41 Monitor disk transfers : > 200 ‐ 300 Mb/s on XL EC2, but your mileage may vary CPU usage > 30 % during normal operations
- 11. OS • For production: Use a 64bit OS • 32bit has 2G limit • Clients can be 32 bit • MongoDB supports (little endian only): • Linux, FreeBSD, OS X • Windows • Solaris (joyent)
- 12. Filesystem • All data, namespace files stored in data directory • Possible to create links • Better to aggregrate IO across disks •File Allocation
- 13. Filesystem • Logfiles: • --logpath <file> • Rotate: • db.runCommand(“logRotate”) • kill -SIGUSR1 <mongod pid> •Does not work for ./mongod > <file> • MongoDB is filesystem-neutral: • ext3, ext4 and XFS are most used • ext4 / XFS preferred (posix_allocate()) • improved performance for file allocation • Support for NTFS for windows
- 14. MongoDB Version Policy • Production: run even numbers • 1.4.x, 1.6.x, 1.8.x •Development •1.5.x, 1.7.x • Critical bugs are back ported to even versions
- 15. Installing MongoDB • Installing from Source • Requires Scons, C++ compiler, Boost libraries, SpiderMonkey, PCRE • Installing from Binaries (easiest) • curl -O http://downloads.mongodb.org/_os_/_version_ • Upgrading database • Install new version of MongoDB • Stop previous version • Start new version •In case of database file changes, •mongodump / mongorestore
- 16. EC2 Notes • Default storage instance is EXT3 • For best performance, reformat to EXT4 / XFS • Use recent version of EXT4 • Use Striping (using MDADM or LVM) aggregates I/O •This is a good thing • EC2 can experience spikes in latency • 400-600mS •This is a bad thing
- 17. More EC2 Notes • EBS snapshots can be used for backups • EBS can disappear • S3 can be used for longer term backups • Use Amazon availability zones • High Availability • Disaster Recovery
- 18. Security • Mongo supports basic security • We encourage to run mongoDB in a safe environment • Authenticates a User on a per Database basis • Start database with --auth • Admin user stored in the admin database use admin db.addUser("administrator", "password") db.auth(“administrator”, “password”) • Regular users stored in other databases use personnel db.addUser("joe", "password") db.addUser(“fred”, “password”, true)
- 19. Backup • Typically backups are driven from a slave • Eliminates impact to client / application traffic to master
- 20. Backup •Two main Strategies • mongodump / mongorestore • Filesystem backup / snapshot • Filelock + fsync
- 21. mongodump • binary, compact object dump • each consistent object is written • not necessarily consistent from start to finish • unless you lock database: • db.runCommand({fsync:1,lock:1}) • mongorestore to restore database • database does not have to be up to restore
- 22. Filesystem Backup • MUST • fsync - flushes buffers to disk • lock - blocks writes db.runCommand({fsync:1,lock:1}) • Use file-system / LVM / storage snapshot • unlock db.$cmd.sys.unlock.findOne();
- 23. Database Maintenance • When doing a lot of updates or deletes • occasional database compaction might be needed • indices and datafiles • db.repair() • With replica sets • Rolling: start up node with --repair param
- 24. Durability What failures do you need to recover from? • Loss of a single database node? • Loss of a group of nodes?
- 25. Durability - Master only • Write acknowledged when in memory on master only
- 26. Durability - Master + Slaves • W=2 • Write acknowledged when in memory on master + slave • Will survive failure of a single node
- 27. Durability - Master + Slaves + fsync • W=n • Write acknowledged when in memory on master + slaves • Pick a “majority” of nodes • fsync in batches (since it blocking)
- 28. Slave delay • Protection against app faults • Protection against administration mistakes • Slave runs X amount of time behind
- 29. Scale out read shard1 shard2 shard3 mongos / rep_a1 rep_a2 rep_a3 config server mongos / rep_b1 rep_b2 rep_b3 config server mongos / rep_c2 rep_c2 rep_c3 config server write
- 30. Monitoring • We like Munin .. • ... but other frameworks work as well • Primary function: • Measure stats over time • Tells you what is going on with your system
- 31. Thank You :-) @rogerb
- 32. download at mongodb.org conferences, appearances, and meetups http://www.10gen.com/events Facebook | Twitter | LinkedIn http://bit.ly/mongoN @mongodb http://linkd.in/joinmongo