If I need a 3-node cluster do I need to have 3 instances? Or are they created in same instance?
https://i.stack.imgur.com/4oRAI.png
If you need a 3-node cluster then you must have 3 instances. Node means a separate instance and 3 machine ElasticSearch cluster will have different jobs assigned to each node.
What is an Elasticsearch cluster?
As the name implies, an Elasticsearch cluster is a group of one or more Elasticsearch nodes instances that are connected together. The power of an Elasticsearch cluster lies in the distribution of tasks, searching and indexing, across all the nodes in the cluster.
The nodes in the Elasticsearch cluster can be assigned different jobs or responsibilities:
Data Nodes - stores data and executes data-related operations such as search and aggregation
Master Nodes - in charge of cluster-wide management and configuration actions such as adding and removing nodes
Client Nodes - forwards cluster requests to the master node and data-related requests to data nodes
Ingest Nodes - for pre-processing documents before indexing
By default, each node is automatically assigned a unique identifier, or name, that is used for management purposes and becomes even more important in a multi-node, or clustered, environment.
When installed, a single Elasticsearch node will form a new single-node cluster entitled elasticsearch but it can also be configured to join an existing cluster using the cluster name.
Related
I have 3 elastic node , How can I cluster there three nodes with always same master node , I didn't find any good docs about new elastic 7 way of specify discovery and master node:
discovery.seed_hosts: [ ]
cluster.initial_master_nodes: []
for example I have node a, b, c and I want node a to be master what what should be discovery.seed_hosts and cluster.initial_master_nodes for master node and child nodes
UPDATE
with using Daniel answer , and checking ports are open and node have same cluster name , other nodes didn't join cluster, is there any additional config needed?
UPDATE 2
looks like nodes found each other but for some reason can't choose master node with election:
master not discovered or elected yet, an election requires 2 nodes
with ids [wOZEfOs9TvqGWIHHcKXtkQ, Cs0xaF-BSBGMGB8a-swznA]
Solution
Deleting folder data of all nodes start a node and then add other nodes with first node (as master) as seed host.
Elasticsearch allows you to specify the role of a node. A node (an instance of Elasticsearch) can serve as a coordinating node, master node, voting_only node, data node, ingest node or machine learning node.
With respect to master nodes you can only configure which nodes potentially can become the (active) master, but you cannot specify which one of the so-called master-eligible nodes will be the active master node.
The only exception to this is when you only configure one master-eligible node, then obviously only this one can become the active master. But be aware that in order to get true high availability you need to have at least 3 master-eligible nodes (this ensures that your cluster will still be 100% operational even when losing one of the master-eligible nodes).
Therefore Elastic always recommends to configure 3 or 5 nodes in your cluster as master-eligible nodes. You can configure that role via the node.master property in the Elasticsearch.yml-file. Setting it to true (default) allows that node to become master, while false will ensure that this node never ever will become master and also will not participate in the master election.
Over the life-time of your cluster (master-eligible) nodes might get added and removed. Elasticsearch automatically manages your cluster and the master node election process with the ultimate goal to prevent a split brain scenario from happening, meaning you eventually end up having 2 clusters which go by the same name but with independent master nodes. To prevent that from happening when starting up your cluster for the very first time (bootstrapping your cluster) Elastic requires you to configure the cluster.initial_master_nodes property with the names of the nodes that initially will serve as master-eligible nodes. This property only needs to be configured on nodes that are master-eligible and the setting will only be considered for the very first startup of your cluster. As values you put in the names as configured with the node.name property of your master-eligible nodes.
The discovery.seed_hosts property supports the discovery process which is all about enabling a new node to establish communication with an already existing cluster and eventually joining it when the cluster.name matches. You are supposed to configure it with an array of host names (not node names!) on which you expect other instances of Elasticsearch belonging to the same cluster to be running. You don't need to add all 100 host names of the 100 nodes you may have in your cluster. It's sufficient to list host names of the most stable node names there. As master (eligible) nodes are supposed to be very stable nodes, Elastic recommends to put the host of all master-eligible nodes (typically 3) in there. Whenever you start/restart a node, it goes through this discovery process.
Conclusion
With a cluster made up of 3 nodes you would configure all of them as master-eligible nodes and list the 3 node names in the cluster.initial_master_nodes setting. And you would put all the 3 host names also in the discovery.seed_hosts setting to support the discovery process.
Useful information from the Elasticsearch reference:
Important discovery and cluster formation settings
Discovery and cluster formation settings
Bootstrapping a cluster
I currently have single node for elasticsearch in a windows server. Can you please explain how to add one extra node for failover in different machine? I also wonder how two nodes can be kept identical using NEST.
Usually, you don't run a failover node, but run a cluster of nodes to provide High Availability.
A minimum topology of 3 master eligible nodes with minimum_master_nodes set to 2 and a sharding strategy that distributes primary and replica shards over nodes to provide data redundancy is the minimum viable topology I'd consider running in production.
I need to provide many elasticSearch instances for different clients but hosted in my infrastructre.
For the moment it is only some small instances.
I am wondering if it is not better to build a big ElastSearch Cluster with 3-5 servers to handle all instances and then each client gets a different index in this cluster and each instance is distributed over servers.
Or maybe another idea?
And another question is about quorum, what is the quorum for ES please?
thanks,
You don’t have to assign each client to different index, Elasticsearch cluster will automatically share loading among all nodes which share shards.
If you are not sure how many nodes are needed, start from a small cluster then keep monitoring the health status of cluster. Add more nodes to the cluster if server loading is high; remove nodes if server loading is low.
When the cluster continuously grow, you may need to assign a dedicated role to each node. In this way, you will have more control over the cluster, easier to diagnose the problem and plan resources. For example, adding more master nodes to stabilize the cluster, adding more data nodes to increase searching and indexing performance, adding more coordinate nodes to handle client requests.
A quorum is defined as majority of eligible master nodes in cluster as follows:
(master_eligible_nodes / 2) + 1
I have ELK stack with Elasticsearch, Logstash and kibana installed on 3 different instances.
Now I want to make 3 node cluster of Elasticsearch.
I will make one node as master and 2 data nodes.
I want to know in logstash config
elasticsearch {
hosts => "http://es01:9200"
Which address I need to enter there master node or data node. and also if I have 3 master nodes then which address I need to write there.
similarly in kibana , I use
elasticsearch.url: es01:9200
In cluster env which url I need to use?
In general, the answer depends on your cluster data size and load.
Nevertheless, I'll try to answer your questions assuming the master node is not a data eligible node as well. This means it only takes care for cluster-wide actions such as creating or deleting an index, tracking which nodes are part of the cluster, and deciding which shards to allocate to which nodes. For this purposes, it is very recommended to have your master node as stable and less loaded as possible.
So, in your logstash config I would put the addresses of your two data nodes as follows:
elasticsearch{
hosts => ["http://es01:9200", "http://es02:9200"]
}
This confirmation maximize performance and fault tolerance as your master do not contain data and if one node failes it will continue to work with the other.
Please note that it is very recommended to have at least 3 master eligible nodes configured in Elasticsearch clusters since if you are loosing the (only) master node you loose data. 3 is to avoid split brain
Regarding kibana, since all nodes in the cluster "knows" each other. You basically can put any address in the cluster. But, for the same reasons as above it is recommended to fill one of your data nodes addresses.
For further reading, please refer to this documentation.
Hope I have managed to help!
Problem descriptions:
- Multiple machines producing logs.
- On each machine we have logstash which filters the log files and sends them to a local elasticsearch
- We would like to keep the machines as separate as possible and avoid intercommunication
- But we would also like to be able to visualize all of these logs with a single Kibana instance
Approaches:
Make each machine a single node ES cluster, and have one of the machines as a tribe node with Kibana installed on this machine (of course with avoiding indices conflict)
Make all machines (nodes) part of a single cluster with each node writing to unique index of one shard and statically map each shard to its node, and finally of course having one instance of kibana for the cluster
Question:
Which approach is more appropriate for the described scenario in terms of: limiting inter machine communications, cluster management, and maybe other aspects that I haven't think about ?
Tribe node is there because of this requirements. So my advice to use the Tribe node setup.
With the second option;
There will be a cluster but you will not use its benefits (replica shards, shard relocation, query performance, etc)
Benefits mentioned above will be pain points that will generate configuration complexity and troubleshooting hell.
Besides the shard allocation and node communication there will be other things to configure that nodes will have when they are in a cluster.