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
Related
I configured a geo cluster using pacemaker and DRBD.
The cluster has 3 different nodes, each node is in a different geographic location.
The locations are pretty close to one another and the communication between them is fast enough for our requirements (around 80MB/s).
I have one master node, one slave node and the third node is an arbitrator.
I use AWS route 53 failover DNS record to do a failover between the nodes in the different sites.
A failover will happen from the master to the slave only if the slave has a quorum, thus ensuring it has communication to the outside world.
I have read that using booth is advised to perform failover between clusters/nodes in different locations - but having a quorum between different geographic locations seems to work very well.
I want to emphasize that I don't have a cluster of clusters - it is a single cluster, with each node in a different geo-location.
My question is - do I need booth in my case? If so - why? Am I missing something?
Booth helps in overlay cluster consisting of clusters running at different sites.
You have one single cluster and hence you should be okay with just Quorum.
I have been reading up on ES Cluster design and have started to design the cluster we need. Please can someone clarify some of the things that are still not clear to me?
So we want to start off with 3 servers.
At the beginning we will have all three as Master, Data and Ingest with minimum two master. This basically means, we are sticking to defaults.
Question 1 is - What are data nodes exactly? Is full index replicated across other data nodes? So if one goes down, in our case the third one should be promoted to master server and the cluster should function.
Found this link Shards and replicas in Elasticsearch and it explains what data nodes are. So basically if our index has 12 shards, it might be that ES will store 4 primary shards on each data node and 8 replicas. Is this correct?
Question 2: With this as starting point, can we add more servers to function as data nodes, ingest nodes etc.
Question 3: We have setup a load balancer in front of the ES nodes, is this the recommended way of accessing ES Clusters over 9200. When ingesting, should this address be used and it will randomly be routed to an ingest node. When querying it should route to a random ES node that can handle searches.
What are data nodes exactly?
Disks for the shards.
Is full index replicated across other data nodes?
Yes, replica means availability as well, getting the concept of shards is key to understand this and don't get confused.
in our case the third one should be promoted to master server and the cluster should function.
Yes, read about the green, yellow and red statuses, in this case, it will turn from green to yellow, it means is still functioning but actions required, but read about "master eligibility" and also, avoid split brain, very important. https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-node.html#master-node
With this as starting point, can we add more servers to function as data nodes, ingest nodes etc.
as many as you want, what is the app requirement? high read low write? vice-versa? equals? define how do you want to grow the cluster depending on the use case.
Question 3: We have setup a load balancer in front of the ES nodes, is this the recommended way of accessing ES Clusters over 9200. When ingesting, should this address be used and it will randomly be routed to an ingest node. When querying it should route to a random ES node that can handle searches.
If it is, for instance, a nginx, it works because I have done it, have a clear understanding on the concept of the nodes roles, for example, the "coordinating node" would handle some process flow that some requests might require and nginx is not aware of.
IMO now that you have the instances, it is a great opportunity for you to learn-by-doing and experiment with them, so move the configs, try to reproduce the problems your app might have and see what happens, aha!moments will happen and full grasp is gotten here.
we are new to elasticsearch and beginning to set-up a coordination node for our UI client to query the index. didn't really understand the difference between master node and coordination node. does coordination has to be scaled up separately based in the site traffic? will other nodes share the load?
The master node is responsible for managing the cluster topology. It neither indexes data nor participates in search tasks.
The data nodes are the real work horses of your ES cluster and are responsible for indexing data and running searches/aggregations.
Coordinating nodes (formerly called "client nodes") are some kind of load balancers within your ES cluster. They are optional and if you don't have any coordinating nodes, your data nodes will be the coordinating nodes. They don't index data but their main job is to distribute search tasks to the relevant data nodes (which they know where to find thanks to the master node) and gather all the results before aggregating them and returning them to the client application.
So depending on your cluster size, amount of data and SLA requirements, you might need to spawn one or more coordinating nodes in order to properly serve your clients. Without any real numbers, it is hard to advise anything at this point, but the above describes how each kind of node works.
If you're just beginning and don't have much data, you don't need any dedicated coordinating node, a simple data node is perfectly fine.
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.
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.