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Monitoring tools for  ElasticSearch     SF Meetup     2013.03.06                  Sushant Shankar                  Shyam K...
• Why and how we use ElasticSearch• Monitoring  – Tools  – Index Building  – Query Performance
Who is asdfas• Social Sharing and Content Discovery platform   – We help >600,000 publishers with content distribution, us...
Data firehose of 30B monthly   events, 1.25B cookies                     - Interaction with web                     conten...
Production ElasticSearch clusterHardware6 nodes, 24GB RAM16GB for ES service4 cores3x 1.5TB driveIndex                  Bu...
System monitoring using Zabbix               Index Build
ElasticSearch specific monitoring                     using SPMScalable Performance Monitoring (http://sematext.com/spm/in...
Index Building Optimization using             Zabbix and SPMAmount bulk indexed                      Time taken           ...
in practice…
Debugging and Validating using SPM
Index Building: Learnings• 2 shards / CPU• 10,000 documents (users) per indexing  request• Bulk API for our use case• No r...
Query Performance: Learnings•   1-2 Replicas (and for reliability)•   Turn refresh on again (5s default)•   Warm up effect...
QUERIES?
Sushant Shankarsushant.shankar@33across.com     Shyam Kuttikkadshyam.kuttikkad@33across.com
Why we really need a search engine         Batch! Good for complicated tasks         (Machine Learning, Graph Algorithms, ...
Warm Up: load into memory and cache
Other cool features• Custom Scoring functions• Scripts – MVEL, Python• Facets•   Exploring:•   Real-time indexing•   Index...
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SF ElasticSearch Meetup 2013.04.06 - Monitoring

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Using monitoring tools Zabbix for systems-level monitoring of ElasticSearch and SPM (http://sematext.com/spm/elasticsearch-performance-monitoring/index.html) for ElasticSearch-specific monitoring. Using these tools was crucial was optimizing index building performance as well as query performance. Some general tips for index building and query performance.

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  • http://www.zabbix.com/ - ‘’Enterprise class monitoring solution for everyone’
  • http://www.zabbix.com/ - ‘’Enterprise class monitoring solution for everyone’
  • Collect information over 1B users internationally – text copied from over 600K publisher sites, images, searches, pages visitedDifferent slices of data – now!
  • Transcript of "SF ElasticSearch Meetup 2013.04.06 - Monitoring"

    1. 1. Monitoring tools for ElasticSearch SF Meetup 2013.03.06 Sushant Shankar Shyam Kuttikkad
    2. 2. • Why and how we use ElasticSearch• Monitoring – Tools – Index Building – Query Performance
    3. 3. Who is asdfas• Social Sharing and Content Discovery platform – We help >600,000 publishers with content distribution, user engagement, and advertising monetization – 450 Fortune 1000 brand marketers leverage our unique social signals to deliver impactful advertising• We develop Machine Learning algorithms operating on Big Data to: – Provide content sharing insights to Publishers – Build customized audience segments for advertising campaigns – Extract actionable insights out of social and interest datawww.33Across.comwww.tynt.com
    4. 4. Data firehose of 30B monthly events, 1.25B cookies - Interaction with web content - Shares – images, copies - Searches Build, understand, analyze Real-time view ElasticSearch! Social Audiences Behavior Context Knowledge
    5. 5. Production ElasticSearch clusterHardware6 nodes, 24GB RAM16GB for ES service4 cores3x 1.5TB driveIndex Build index>1TB/index using MR job(replicated) and Bulk API~300M documents~5KB / document~3 hours
    6. 6. System monitoring using Zabbix Index Build
    7. 7. ElasticSearch specific monitoring using SPMScalable Performance Monitoring (http://sematext.com/spm/index.html)• Index stats – Total/Refreshed/Merged documents• Shards – Total/Active/Relocating/Initializing• Search - Request rate and latency• Cache – {Filter, field} cache {count, evictions, size}• Machine – CPU, Memory, JVM, GC, Network, Disk
    8. 8. Index Building Optimization using Zabbix and SPMAmount bulk indexed Time taken CPU util. Mem util. Disk I/O Network # Shards
    9. 9. in practice…
    10. 10. Debugging and Validating using SPM
    11. 11. Index Building: Learnings• 2 shards / CPU• 10,000 documents (users) per indexing request• Bulk API for our use case• No replicas• Refresh off (index.refresh_interval = -1)
    12. 12. Query Performance: Learnings• 1-2 Replicas (and for reliability)• Turn refresh on again (5s default)• Warm up effect (Index Warm up API 0.20+)• Optimize API• Simulate multiple users
    13. 13. QUERIES?
    14. 14. Sushant Shankarsushant.shankar@33across.com Shyam Kuttikkadshyam.kuttikkad@33across.com
    15. 15. Why we really need a search engine Batch! Good for complicated tasks (Machine Learning, Graph Algorithms, etc.) … …
    16. 16. Warm Up: load into memory and cache
    17. 17. Other cool features• Custom Scoring functions• Scripts – MVEL, Python• Facets• Exploring:• Real-time indexing• Indexing images, files, etc.• Parent-child relationships
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