Deployment Architecture

How to provide high availability for an indexer cluster master node and search head in AWS?

sent2020
Explorer

We are deploying a Splunk High Availability Cluster in AWS, where we have one master node, one search head and 3 peer nodes. I like to know how to provide HA for the Master and Search node. Can AMI backup of the running master be the best option? Please suggest your views.

0 Karma

nkwong_splunk
Splunk Employee
Splunk Employee

Here is a .conf2015 talk that my colleagues and I did on deploying a highly available Splunk Enterprise architecture on AWS. We talk about how to leverage autoscaling with the master node since it is a stateless server as mentioned in the above answer.

Slidedeck
http://conf.splunk.com/session/2015/conf2015_SYep_Splunk_Cloud_DeployingSplunkOnAmazon.pdf

Recording
http://conf.splunk.com/session/2015/recordings/2015-splunk-126.mp4

renjith_nair
Legend

For search head, better option is to use a search head cluster : http://docs.splunk.com/Documentation/Splunk/6.2.0/DistSearch/SHCarchitecture

For master node, since it's not storing data or not doing searches - If a master goes down, the cluster can continue to run as usual, as long as there are no other failures. Peers can continue to ingest data, stream copies to other peers, replicate buckets, and respond to search requests from the search head. An active-passive or stand-by set up is sufficient for master.

http://docs.splunk.com/Documentation/Splunk/6.2.0/Indexer/Handlemasternodefailure

---
What goes around comes around. If it helps, hit it with Karma 🙂
0 Karma
Get Updates on the Splunk Community!

Developer Spotlight with Paul Stout

Welcome to our very first developer spotlight release series where we'll feature some awesome Splunk ...

State of Splunk Careers 2024: Maximizing Career Outcomes and the Continued Value of ...

For the past four years, Splunk has partnered with Enterprise Strategy Group to conduct a survey that gauges ...

Data-Driven Success: Splunk & Financial Services

Splunk streamlines the process of extracting insights from large volumes of data. In this fast-paced world, ...