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Performance Tuning on the Fly at CMP.LY

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Performance Tuning on the Fly at CMP.LY

  1. 1. 1JUNE 2014 Performance Tuning on the Fly at CMP.LY Michael De Lorenzo CTO, CMP.LY Inc. michael@cmp.ly @mikedelorenzo
  2. 2. 2JUNE 2014 Agenda • CMP.LY and CommandPost • What is MongoDB Management Service? • Performance Tuning • MongoDB Issues we’ve faced • Slow response times and delayed writes • Unindexed queries • Increased Replication Lag and Plummeting oplog Window • Keep your deployment healthy with MMS • Using MMS Alerts • Using MMS Backups
  3. 3. 3JUNE 2014 A venture-funded NYC startup that offers proprietary social media, monitoring, measurement, insight and compliance solutions for Fortune 100 A Monitoring, Measurement & Insights (MMI) tool for managed social communications.
  4. 4. 4JUNE 2014 Use CommandPost to: • Track and measure cross-platform in real-time • Identify and attribute high-value engagement • Analyze and segment engaged audience • Optimize content and engagement strategies • Address compliance needs
  5. 5. 5JUNE 2014 What is MongoDB Management Service?
  6. 6. 6JUNE 2014 MongoDB Management Service • Free MongoDB Monitoring • MongoDB Backup in the Cloud • Free Cloud service or Available to run On-Prem for Standard or Enterprise Subscriptions • Automation coming soon—FTW! Ops Makes MongoDB easier to use and manage
  7. 7. 7JUNE 2014 Who Is MMS for? • Developers • Ops Team • MongoDB Technical Service Team
  8. 8. 8JUNE 2014 Performance Tuning
  9. 9. 9JUNE 2014 How To Do Performance Tuning? • Assess the problem and establish acceptable behavior. • Measure the performance before modification. • Identify the bottleneck. • Remove the bottleneck. • Measure performance after modification to confirm. • Keep it or revert it and repeat. Adapted from [http://en.wikipedia.org/wiki/Performance_tuning]
  10. 10. 10JUNE 2014 What We’ve Faced
  11. 11. 11JUNE 2014 Issues We’ve Faced • Concurrency Issues • Slow response times and delayed writes • Querying without indexes • Slow reads, timeouts • Increasing Replication Lag + Plummeting oplog Window
  12. 12. 12JUNE 2014 Concurrency Slow responses and delayed writes
  13. 13. 13JUNE 2014 Concurrency • What is it? • How did it affect us? • How did MMS help identify it? • How did we diagnose the issue in our app and fix it? • Today
  14. 14. 14JUNE 2014 Concurrency in MongoDB • MongoDB uses a readers-writer lock • Many read operations can use a read lock • If a write lock exists, a single write lock holds the lock exclusively • No other read or write operations can share the lock • Locks are “writer-greedy”
  15. 15. 15JUNE 2014 How Did This Affect Us? • Slow API response times due to slow database operations • Delayed writes • Backed up queues
  16. 16. 16JUNE 2014 MMS: Identify Concurrency Issues
  17. 17. 17JUNE 2014 Lock % Greater than 100%?!?!? • time spent in write lock state; sum of global lock + hottest database at that time, can make value > 100% • Global lock percentage is a derived metric: % of time in global lock (small number) + % of time locked by hottest (“most locked”) database • Data is sampled and combined, it is possible to see values over 100%.
  18. 18. 18JUNE 2014 Diagnosis • Identified the write-heavy collections in our applications • Used application logs to identify slow API responses • Analyzed MongoDB logs to identify slow database queries
  19. 19. 19JUNE 2014 Our Remedies • Schema changes • Message queues • Multiple databases • Sharding
  20. 20. 20JUNE 2014 Schema Changes • Denormalized our schema • Allowed for atomic updates • Customized documents’ _id attribute • Leveraged existing index on _id attribute
  21. 21. 21JUNE 2014 Modeling for Atomic Operations Document { _id: 123456789, title: "MongoDB: The Definitive Guide", author: [ "Kristina Chodorow", "Mike Dirolf" ], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher_id: "oreilly", available: 3, checkout: [ { by: "joe", date: ISODate("2012-10-15") } ] } Update Operation db.books.update ( { _id: 123456789, available: { $gt: 0 } }, { $inc: { available: -1 }, $push: { checkout: { by: "abc", date: new Date() } } } ) Result WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
  22. 22. 22JUNE 2014 Message Queues • Controlled writes to specific collections using Pub/Sub • We chose Amazon SQS • Other options include Redis, Beanstalkd, IronMQ or any other message queue • Created consistent flow of writes versus bursts • Reduced length and frequency of write locks by controlling flow/speed of writes
  23. 23. 23JUNE 2014 Using Multiple Databases • As of version 2.2, MongoDB implements locks at a per database granularity for most read and write operations • Planned to be at the document level in version 2.8 • Moved write-heavy collections to new (separate) databases
  24. 24. 24JUNE 2014 Using Sharding • Improves concurrency by distributing databases across multiple mongod instances • Locks are per-mongod instance
  25. 25. 25JUNE 2014 Lock %: Today
  26. 26. 26JUNE 2014 Queries without Indexes Slow responses and timeouts
  27. 27. 27JUNE 2014 Indexing • What is it? • How did it affect us? • How did MMS help identify it? • How did we diagnose the issue in our app and fix it? • Today
  28. 28. 28JUNE 2014 Indexing with MongoDB • Support for efficient execution of queries • Without indexes, MongoDB must scan every document • Example Wed Jul 17 13:40:14 [conn28600] query x.y [snip] ntoreturn:16 ntoskip:0 nscanned:16779 scanAndOrder:1 keyUpdates:0 numYields: 906 locks(micros) r:46877422 nreturned:16 reslen:6948 38172ms 38 seconds! Scanned 17k documents, returned 16 • Create indexes to cover all queries, especially support common and user-facing • Collection scans can push entire working set out of RAM
  29. 29. 29JUNE 2014 How Did this Affect Us? • Our web apps became slow • Queries began to timeout • Longer operations mean longer lock times
  30. 30. 30JUNE 2014 MMS: Identifying Indexing Issues Page Faults • The number of times that MongoDB requires data not located in physical memory, and must read from virtual memory.
  31. 31. 31JUNE 2014 Diagnosis • Log Analysis • Use mtools to analyze MongoDB logs • mlogfilter • filter logs for slow queries, collection scans, etc. • mplotqueries • graph query response times and volumes • https://github.com/rueckstiess/mtools
  32. 32. 32JUNE 2014 Diagnosis • Monitoring application logs • Enabling ‘notablescan’ option in development and testing versions of apps • MongoDB profiling
  33. 33. 33JUNE 2014 The MongoDB Profiler • Collects fine grained data about MongoDB write operations, cursors, database commands on a running mongod instance. • Default slowOpThreshold value is 100ms, can be changed from the Mongo shell
  34. 34. 34JUNE 2014 Our Remedies • Add indexes! • Make sure queries are covered • Utilize the projection specification to limit fields (data) returned
  35. 35. 35JUNE 2014 Adding Indexes • Improved performance for common queries • Alleviates the need to go to disk for many operations
  36. 36. 36JUNE 2014 Projection Specification Controls the amount of data that needs to be (de-)serialized for use in your app • We used it to limit data returned in embedded documents and arrays db.inventory.find( { type: 'food' }, { item: 1, qty: 1 } )
  37. 37. 37JUNE 2014 Page Faults: Today
  38. 38. 38JUNE 2014 Increasing Replication Lag + Plummeting oplog Window
  39. 39. 39JUNE 2014 Replication • What is it? • How did it affect us? • How did MMS help identify it? • How did we diagnose the issue in our app? • How did we fix it? • Today
  40. 40. 40JUNE 2014 What is Replication? • A replica set is a group of mongod processes that maintain the same data set. • Replica sets provide redundancy and high availability, and are the basis for all production deployments
  41. 41. 41JUNE 2014 What Is the Oplog? • A special capped collection that keeps a rolling record of all operations that modify the data stored in your databases. • Operations are first applied on the primary and then recorded to its oplog. • Secondary members then copy and apply these operations in an asynchronous process.
  42. 42. 42JUNE 2014 What is Replication Lag? • A delay between an operation on the primary and the application of that operation from the oplog to the secondary. • Effects of excessive lag • “Lagged” members ineligible to quickly become primary • Increases the possibility that distributed read operations will be inconsistent.
  43. 43. 43JUNE 2014 How did this affect us? • Degraded overall health of our production deployment. • Distributed reads are no longer eventually consistent. • Unable to bring new secondary members online. • Caused MMS Backups to do full re-syncs.
  44. 44. 44JUNE 2014 Identifying Replication Lag Issues with MMS The Replication Lag chart displays the lag for your deployment
  45. 45. 45JUNE 2014 Diagnosis • Possible causes of replication lag include network latency, disk throughput, concurrency and/or appropriate write concern • Size of operations to be replicated • Confirmed Non-Issues for us • Network latency • Disk throughput • Possible Issues for us • Concurrency/write concern • Size of op is an issue because entire document is written to oplog
  46. 46. 46JUNE 2014 Concurrency/Write Concern • Our applications apply many updates very quickly • All operations need to be replicated to secondary members • We use the default write concern—Acknowledge • The mongod confirms receipt of the write operation • Allows clients to catch network, duplicate key and other errors
  47. 47. 47JUNE 2014 Concurrency Wasn’t the Issue Lock Percentage
  48. 48. 48JUNE 2014 Operation Size Was the Issue Collection A (most active) Total Updates: 3,373 Total Size of updates: 6.5 GB Activity accounted for nearly 87% of total traffic Collection B (next most active) Total Updates: 85,423 Total Size of updates: 740 MB
  49. 49. 49JUNE 2014 Fast Growing oplog causes issues Replication oplog Window – approximate hours available in the primary’s oplog
  50. 50. 50JUNE 2014 How We Fixed It • Changed our schema • Changed the types of updates that were made to documents • Both allowed us to utilize atomic operations • Led to smaller updates • Smaller updates == less oplog space used
  51. 51. 51JUNE 2014 Replication Lag: Today
  52. 52. 52JUNE 2014 oplog Window: Today
  53. 53. 53JUNE 2014 Keeping Your Deployment Healthy
  54. 54. 54JUNE 2014 MMS Alerts
  55. 55. 55JUNE 2014 Watch for Warnings • Be warned if you are • Running outdated versions • Have startup warnings • If a mongod is publicly visible • Pay attention to these warnings
  56. 56. 56JUNE 2014 MMS Backups • Engineered by MongoDB • Continuous backup with point-in-time recovery • Fully managed backups
  57. 57. 57JUNE 2014 Using MMS Backups • Seeding new secondaries • Repairing replica set members • Development and testing databases • Restores are free!
  58. 58. 58JUNE 2014 Summary • Know what’s expected and “normal” in your systems • Know when and what changes in your systems • Utilize MMS alerts, visualizations and warnings to keep things running smoothly
  59. 59. 59JUNE 2014 Questions? Michael De Lorenzo CTO, CMP.LY Inc. michael@cmp.ly @mikedelorenzo

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