Downloaded 39 times
!["hits": {
"total": 123456789,
"hits": [ ... ]
}
"hits": {
"total": {
"value": 10000,
"relation": "gte"
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Weak-AND](https://image.slidesharecdn.com/elasticontourstacksep2019final1-191004161700/85/Elastic-Stack-roadmap-deep-dive-68-320.jpg)
![Templated Alerts
when [CPU] > [90%]
then alert
[alerts@me.com]](https://image.slidesharecdn.com/elasticontourstacksep2019final1-191004161700/85/Elastic-Stack-roadmap-deep-dive-113-320.jpg)
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Elastic Stack roadmap deep dive
- Elastic provides a search and analytics platform called the Elastic Stack that includes the Elastic Stack, Beats data shippers, and Kibana analytics and visualization tools. - The presentation discussed updates to Elastic's products including performance improvements to search, new features for distributed search across data centers, and enhanced security options for authentication and authorization. - Elastic aims to provide customizable and extensible solutions for users to ingest, store, search, analyze and visualize large volumes of data from various sources.
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Elastic Stack roadmap deep dive
- 1. Shay Banon |Founder & CEO Aaron Katz | CRO Janesh Moorjani | CFO Elastic Overview Elastic Stack Updates and Roadmap Alex Francoeur
- 5.
- 7.
- 8.
- 9.
- 10.
- 11.
- 12. Ingest Node: Enrichment Processor source.ip=> is_known_botnet? geo.location => city/region/country
- 13.
- 15. • What technology?(eg. Nginx) • What to monitor? (eg. logs, metrics, packets) • Where is it? (eg. paths to logfiles) Integrations Manager
- 18. • Beats config •Ingest node config • Index template • First index • Index alias • Index lifecycle management policy • Snapshot lifecycle management policy • Index patterns • Kibana dashboards • Canvas workpads • Machine learning jobs • Alerts Automatically Setup
- 19. • Beats config •Ingest node config • Index template • First index • Index alias • Index lifecycle management policy • Snapshot lifecycle management policy • Index patterns • Kibana dashboards • Canvas workpads • Machine learning jobs • Alerts Automatically Setup
- 20.
- 21. • Single configlanguage • Installs required Beats • Upgrades Beats • Upgrades itself Beats Agent
- 22. Fleet • Centralized ConfigDeployment • Centralized Beats Monitoring • Centralized Upgrade Management
- 23.
- 24.
- 25. Heap File systemcache Disk
- 26. Heap File systemcache Disk
- 27.
- 28.
- 29. 1 2 3 1 2 3 Hot Nodes ColdNodesWarm Nodes
- 30. 1 2 3 1 2 3 HotNodes Cold NodesWarm Nodes
- 31. 231 2 3 Hot Nodes ColdNodesWarm Nodes 1
- 32. 1 Hot Nodes ColdNodesWarm Nodes 1 2 3
- 33. 1 Hot Nodes ColdNodesWarm Nodes 1 2 3
- 34. Hot Nodes ColdNodesWarm Nodes 1 2 3
- 35. Hot Nodes ColdNodesWarm Nodes 1 2 3
- 36. (coming soon toX-Pack)
- 37.
- 38. • Periodic scheduledbackups • Retention polices for automatic deletion Snapshot Management
- 41.
- 42.
- 43. Page views perminute? Clickstream Data
- 44.
- 45.
- 46. How long wassession 1? Clickstream Data
- 47. How long wassession 1? Clickstream Data
- 48.
- 49.
- 50. Average number ofpages per session? Session Data
- 51. Most frequent exitpage per session? Session Data
- 52.
- 53. How frequently dousers visit the site? Session Data
- 54. How frequently dousers visit the site? User Data
- 55. • Pivot • PatternMatching Data Transformation
- 56.
- 58. • Outlier detection •Supervised model training for regression & classification • Ingest Prediction Processor Advanced ML Analytics
- 59.
- 60.
- 61. Query Before AfterImprovement Fuzzy 46 qps Phrase 4 qps Bool AND 9.3 qps Bool OR 3.3 qps Term 33 qps
- 62. Query Before AfterImprovement Fuzzy 46 qps 59 qps 28% Phrase 4 qps 7 qps 87% Bool AND 9.3 qps 23.5 qps 247% Bool OR 3.3 qps 9.8 qps 292% Term 33 qps 1,160 qps 3,700%
- 63.
- 64. "query" : "elasticsearchand lucene" max_score(and) == 1 max_score(lucene) == 5 max_score(elasticsearch) == 3 Weak-AND
- 65. Min top-10 scoreand (1) elasticsearch (3) lucene (5) <=1 ✓ ✓ ✓ > 1 and <= 4 ✗ ✓ ✓ > 4 and <= 9 ✗ ✗ ✓ > 9 ✗ ✗ ✗ Weak-AND
- 66.
- 67. Weak-AND "aggs": { ...} "track_total_hits": true
- 68. "hits": { "total": 123456789, "hits":[ ... ] } "hits": { "total": { "value": 10000, "relation": "gte" }, "hits": [ ... ] } Weak-AND
- 69. Search as youtype
- 70. index_prefixes: qu, qui, quic,quick br, bro, brow, brown fo, fox, foxe, foxes
- 71.
- 72.
- 73.
- 74. rank_feature: Advanced Scoring • StarRatings • PageRank • Popularity
- 75. score = BM25(Text)+ PageRank rank_feature: Advanced Scoring • Star Ratings • PageRank • Popularity
- 76. score = BM25(Text)+ Saturation(PageRank) rank_feature: Advanced Scoring • Star Ratings • PageRank • Popularity
- 77. distance_feature: rank_feature: Advanced Scoring • Date •Geopoint • Numeric • Star Ratings • PageRank • Popularity
- 78. script_score: • Customscoring, including vectors distance_feature: • Date • Geopoint • Numeric rank_feature: Advanced Scoring • Star Ratings • PageRank • Popularity
- 79. Work with WAND script_score: • Customscoring, including vectors distance_feature: rank_feature: Advanced Scoring • Star Ratings • PageRank • Popularity • Date • Geopoint • Numeric
- 80.
- 82.
- 83. • v2.3: 1dim, for numbers and dates • v5.0: 2 dim, for geopoints • v5.2: 2 dim, for number & date ranges • v6.7: 7 dim, for geoshapes BKD Trees
- 84.
- 85. • Accurate to1cm, vs 50m • Index is 60% smaller • Indexing 60% faster • Queries 50% faster • Plus BKD GeoPoints 80% faster indexing BKD Geoshapes
- 86.
- 87.
- 88.
- 89.
- 90.
- 91.
- 92.
- 93.
- 94. New York LondonTokyo
- 95. v5.6 v6.7 v7.x ThreeMajor Versions
- 96.
- 97. New York LondonTokyo ldn_sales ldn_sales
- 98. New York LondonTokyo tk_salesny_sales
- 99. New York LondonTokyo tk_salesny_sales ldn_sales ldn_sales
- 101.
- 102.
- 105.
- 106.
- 108.
- 109.
- 110.
- 111. SIEM Stack Monitoring MachineLearning Observability
- 112.
- 113. Templated Alerts when [CPU]> [90%] then alert [alerts@me.com]
- 114.
- 115.
- 116.
- 118.
- 120.