Running High Performance and Fault Tolerant Elasticsearch Clusters on Docker
•Transferir como PPT, PDF•
86 gostaram•38,216 visualizações
Sematext engineer Rafal Kuc (@kucrafal) walks through the details of running high-performance, fault tolerant Elasticsearch clusters on Docker. Topics include: Containers vs. Virtual Machines, running the official Elasticsearch container, container constraints, good network practices, dealing with storage, data-only Docker volumes, scaling, time-based data, multiple tiers and tenants, indexing with and without routing, querying with and without routing, routing vs. no routing, and monitoring. Talk was delivered at DevOps Days Warsaw 2015.
Recomendados
Recomendados
Mais conteúdo relacionado
Mais procurados
Mais procurados (20)
Semelhante a Running High Performance and Fault Tolerant Elasticsearch Clusters on Docker
Semelhante a Running High Performance and Fault Tolerant Elasticsearch Clusters on Docker (20)
Mais de Sematext Group, Inc.
Mais de Sematext Group, Inc. (20)
Último
Último (20)
Running High Performance and Fault Tolerant Elasticsearch Clusters on Docker
- 1. Elasticsearch & Docker Rafał Kuć – Sematext Group, Inc. @kucrafal @sematext sematext.com Running High Performance Fault Tolerant Elasticsearch Clusters On Docker
- 2. About me… Sematext consultant & engineer Solr.pl co-founder Father and husband :)
- 4. You Are Probably Familiar With This Development
- 5. You Are Probably Familiar With This Development Test
- 6. You Are Probably Familiar With This Development Test QA
- 7. You Are Probably Familiar With This Development Test QA Production environment
- 8. And The Problems That Come With It Resources not utilized
- 9. And The Problems That Come With It Resources not utilized Overprovisioned Servers
- 10. And The Problems That Come With It Resources not utilized Overprovisioned Servers ≠ ≠
- 11. The solution Development Test QA Production
- 13. What is Docker? Lightweight Based on Open Standards Secure
- 14. Containers vs Virtual Machines Hardware Traditional Virtual Machine
- 15. Containers vs Virtual Machines Hardware Host Operating System Traditional Virtual Machine
- 16. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Traditional Virtual Machine
- 17. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Traditional Virtual Machine
- 18. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Libraries Libraries Traditional Virtual Machine
- 19. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Libraries Libraries Application 1 Application 2 Traditional Virtual Machine
- 20. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Libraries Libraries Application 1 Application 2 Hardware Host Operating System Traditional Virtual MachineContainer
- 21. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Libraries Libraries Application 1 Application 2 Hardware Host Operating System Docker Engine Traditional Virtual MachineContainer
- 22. Containers vs Virtual Machines Hardware Host Operating System Hypervisor Guest OS Guest OS Libraries Libraries Application 1 Application 2 Hardware Host Operating System Docker Engine Libraries Libraries Application 1 Application 2 Traditional Virtual MachineContainer
- 23. What is Elasticsearch? Reasonable defaults { JSON } Distributed by design http://www.dailypets.co.uk/2007/06/17/kittens-rest-at-half-time/
- 24. Running Official Elasticsearch Container $ docker run -d elasticsearch
- 25. Running Official Elasticsearch Container $ docker run -d elasticsearch == docker run -d elasticsearch:latest
- 26. Running Official Elasticsearch Container $ docker run -d elasticsearch:1.7 $ docker run -d elasticsearch == docker run -d elasticsearch:latest
- 27. Running Official Elasticsearch Container $ docker run -d elasticsearch == docker run -d elasticsearch:latest $ docker run --name es_1 -h es_master_1 elasticsearch $ docker run -d elasticsearch:1.7
- 28. Running Official Elasticsearch Container $ docker run -d elasticsearch == docker run -d elasticsearch:latest $ docker run --name es_1 -h es_master_1 elasticsearch $ docker run -d elasticsearch:1.7
- 29. Container Constraints $ docker run -d -m 2G elasticsearch http://docs.docker.com/engine/reference/run/
- 30. Container Constraints $ docker run -d -m 2G elasticsearch $ docker run -d -m 2G --memory-swappiness=0 elasticsearch http://docs.docker.com/engine/reference/run/
- 31. Container Constraints $ docker run -d -m 2G elasticsearch $ docker run -d -m 2G --memory-swappiness=0 elasticsearch $ docker run -d --cpuset-cpus="1,3" elasticsearch http://docs.docker.com/engine/reference/run/
- 32. Container Constraints $ docker run -d -m 2G elasticsearch $ docker run -d -m 2G --memory-swappiness=0 elasticsearch $ docker run -d --cpuset-cpus="1,3" elasticsearch http://docs.docker.com/engine/reference/run/ $ docker run -d --cpu-period=50000 --cpu-quota=25000 elasticsearch
- 33. Creating Optimized Image Dockerfile: FROM elasticsearch ADD ./elasticsearch.yml /usr/share/elasticsearch/config/
- 34. Creating Optimized Image Dockerfile: FROM elasticsearch ADD ./elasticsearch.yml /usr/share/elasticsearch/config/ $ docker build -t devops/example .
- 35. Creating Optimized Image Dockerfile: FROM elasticsearch ADD ./elasticsearch.yml /usr/share/elasticsearch/config/ $ docker build -t devops/example . Sending build context to Docker daemon 3.072 kB Step 1 : FROM elasticsearch ---> 8112755253f1 Step 2 : ADD ./elasticsearch.yml /usr/share/elasticsearch/config/ ---> Using cache ---> c9ca48a22e58 Successfully built c9ca48a22e58
- 36. Dealing With Network $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch
- 37. Dealing With Network $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch $ docker run -d elasticsearch -Dnetwork.publish_host=192.168.1.1
- 38. Dealing With Network $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch $ docker run -d elasticsearch -Dnetwork.publish_host=192.168.1.1 $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch -Dnetwork.publish_host=192.168.1.1
- 39. Dealing With Network $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch $ docker run -d elasticsearch -Dnetwork.publish_host=192.168.1.1 $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch -Dnetwork.publish_host=192.168.1.1 $ docker run -d -p 9200:9200 -p 9300:9300 elasticsearch -Dnetwork.publish_host=0.0.0.0
- 40. Network - Good Practices Separate network for Elasticsearch cluster
- 41. Network - Good Practices Separate network for Elasticsearch cluster Common host names for containers $ docker run -d -h es_node_1 elasticsearch
- 42. Network - Good Practices Separate network for Elasticsearch cluster Common host names for containers $ docker run -d -h es_node_1 elasticsearch Expose 9200 & 9300 ports only for client nodes
- 43. Network - Good Practices Separate network for Elasticsearch cluster Common host names for containers $ docker run -d -h es_node_1 elasticsearch Expose 9200 & 9300 ports only for client nodes Elasticsearch data & client nodes point to masters only
- 44. Dealing With Storage By default in /usr/share/elasticsearch/data
- 45. Dealing With Storage By default in /usr/share/elasticsearch/data By default not persisted
- 46. Dealing With Storage By default in /usr/share/elasticsearch/data By default not persisted $ docker run -d -v /opt/elasticsearch/data:/usr/share/elasticsearch/data elasticsearch
- 47. Dealing With Storage $ docker run -d -v /opt/elasticsearch/data:/usr/share/elasticsearch/data elasticsearch By default in /usr/share/elasticsearch/data By default not persisted Use data only containers Permissions
- 48. Data-Only Docker Volumes Bypasses Union File System
- 49. Data-Only Docker Volumes Bypasses Union File System Can be shared between containers
- 50. Data-Only Docker Volumes Bypasses Union File System Can be shared between containers Data volumes persist if the container itself is deleted
- 51. Data-Only Docker Volumes Bypasses Union File System Can be shared between containers Data volumes persist if the container itself is deleted $ docker create -v /mnt/es/data:/usr/share/elasticsearch/data --name esdata elasticsearch Permissions
- 52. Data-Only Docker Volumes Bypasses Union File System Can be shared between containers Data volumes persist if the container itself is deleted $ docker create -v /mnt/es/data:/usr/share/elasticsearch/data --name esdata elasticsearch $ docker run --volumes-from esdata elasticsearch
- 53. Highly Available Cluster Master only Master only Master only Data only Data only Data only Data only Data only Data only Client only Client only
- 54. Highly Available Cluster Master only Master only Master only Data only Data only Data only Data only Data only Data only Client only Client only minimum_master_nodes = N/2 + 1
- 55. Highly Available Cluster Master only Master only Master only Data only Data only Data only Data only Data only Data only Client only Client only minimum_master_nodes = N/2 + 1 recovery.after.nodes recovery.expected.nodes cluster.routing.allocation.node_concurrent_ recoveries index.unassigned.node_left.delayed_timeout index.priority
- 56. Master Nodes & Docker $ docker run -d elasticsearch -Dnode.master=true -Dnode.data=false -Dnode.client=false
- 57. Client Nodes & Docker $ docker run -d elasticsearch -Dnode.master=false -Dnode.data=false -Dnode.client=true
- 58. Data Nodes & Docker $ docker run -d elasticsearch -Dnode.master=false -Dnode.data=true -Dnode.client=false
- 59. Scaling Elasticsearch Node Elasticsearch Node Elasticsearch Node Elasticsearch Node
- 60. Scaling curl -XPUT 'http://localhost:9200/devops/' -d '{ "settings" : { "index" : { "number_of_shards" : 4, "number_of_replicas" : 0 } } }'
- 61. Scaling P P P P
- 62. Scaling curl -XPUT 'http://localhost:9200/devops/_settings' -d '{ "index.number_of_replicas" : 1 }'
- 63. Scaling P P P P R R R R
- 64. Scaling curl -XPUT 'http://localhost:9200/devops/_settings' -d '{ "index.number_of_replicas" : 2 }'
- 65. Scaling P P P P R R R R R R R R
- 66. Scaling curl -XPUT 'http://localhost:9200/devops/_settings' -d '{ "index.number_of_replicas" : 1 }'
- 67. Scaling P P P P R R R R
- 68. Scaling P P P P R R R R
- 70. RAM Buffer indices.memory.index_buffer_size: 10% indices.memory.min_index_buffer_size: 48mb indices.memory.max_index_buffer_size (unbounded) indices.memory.min_shard_index_buffer_size: 4mb
- 71. RAM Buffer indices.memory.index_buffer_size: 10% indices.memory.min_index_buffer_size: 48mb indices.memory.max_index_buffer_size (unbounded) indices.memory.min_shard_index_buffer_size: 4mb Higher Indexing Throughput Lower Indexing Throughput defaults ><
- 73. Time-Based Data? curl -XPOST 'http://localhost:9200/_aliases' -d '{ "actions" : [ { "add" : {"index":"2015-11-23","alias":"today"} }, { "add" : {"index":"2015-11-23","alias":"week"} } ]}'
- 75. Time-Based Data? 2015-11-23 2015-11-24 2014-11-25 TODAY WEEK
- 76. Multiple Tiers node.tag=hot node.tag=cold node.tag=cold
- 77. Multiple Tiers curl -XPUT 'localhost:9200/data_2015-11-23' -d '{ "settings": { "index.routing.allocation.include.tag" : "hot" } }'
- 78. Multiple Tiers node.tag=hot node.tag=cold node.tag=cold data_2015-11-23 data_2015-11-23
- 79. Multiple Tiers curl -XPUT 'localhost:9200/data_2015-11-23/_settings' -d '{ "settings": { "index.routing.allocation.exclude.tag" : "hot", "index.routing.allocation.include.tag" : "cold", } }'
- 80. Multiple Tiers node.tag=hot node.tag=cold node.tag=cold data_2015-11-23 data_2015-11-23
- 81. Multiple Tiers node.tag=hot node.tag=cold node.tag=cold data_2015-11-23 data_2015-11-23 data_2015-11-24 data_2015-11-24
- 82. Multiple Tiers node.tag=hot node.tag=cold node.tag=cold data_2015-11-23 data_2015-11-23 data_2015-11-25 data_2015-11-25 data_2015-11-24 data_2015-11-24
- 83. Multiple Tenants
- 86. Indexing Without Routing Shard 1 Shard 2 Shard 3 Shard 4 Shard 5 Shard 6 Shard 7 Shard 8 Elasticsearch Application userA userA userA userA userAuserA userA userA
- 87. Indexing With Routing Shard 1 Shard 2 Shard 3 Shard 4 Shard 5 Shard 6 Shard 7 Shard 8 Elasticsearch Application
- 88. Querying Without Routing Shard 1 Shard 2 Shard 3 Shard 4 Shard 5 Shard 6 Shard 7 Shard 8 Elasticsearch Application
- 89. Querying With Routing Shard 1 Shard 2 Shard 3 Shard 4 Shard 5 Shard 6 Shard 7 Shard 8 Elasticsearch Application
- 90. Routing vs No Routing Queries without routing (200 shards, 1 replica) #threads Avg response time Throughput 90% line Median CPU Utilization 1 3169ms 19,0/min 5214ms 2692ms 95 – 99%
- 91. Routing vs No Routing Queries without routing (200 shards, 1 replica) #threads Avg response time Throughput 90% line Median CPU Utilization 1 3169ms 19,0/min 5214ms 2692ms 95 – 99% Queries with routing (200 shards, 1 replica) #threads Avg response time Throughput 90% line Median CPU Utilization 10 196ms 50,6/sec 642ms 29ms 25 – 40% 20 218ms 91,2/sec 718ms 11ms 10 – 15%
- 94. We Are Hiring! Dig Search? Dig Analytics? Dig Big Data? Dig Performance? Dig Logging? Dig working with, and in, open–source? We’re hiring worldwide! http://sematext.com/about/jobs.html
Notas do Editor
- Problems with standard deployment like: Resources not utilized Need to provision machines before deployment Differences between development, test, QA and production environments Hard to scale automatically
- Problems with standard deployment like: Resources not utilized Need to provision machines before deployment Differences between development, test, QA and production environments Hard to scale automatically
- Problems with standard deployment like: Resources not utilized Need to provision machines before deployment Differences between development, test, QA and production environments Hard to scale automatically
- Amazon EC2 container service Spoonium Kubernetes RKT
- Shards and Replicas
- Shards and Replicas
- Shards and Replicas
- Shards and Replicas
- Shards and Replicas
- Shards and Replicas
- Shards and Replicas
- No time based indices No tiers Possible solution - routing
- No time based indices No tiers Possible solution - routing
- No time based indices No tiers Possible solution - routing