ng-elastic | Ionic 2 directive to auto expand textareas | File Upload library

On my AWS EC2 linux server I'am running one ELK stack, where logstash is transforming postgress database and importing into Elasticsearch. This setup is currently in use for my development environment. We have come to a point where we created staging environment and so we also need probably a separate ELK stack for staging, since we don't want to mix the data from 2 separate databases (dev and stage).

I have quite minor experience in ELK, I have checked some options but did not find any solution to this problem.

What I have tried is to create another docker-compose file with different container names and ports. When I run docker-compose.elastic.dev.yml it normally creates first ELK stack. Then I run docker-compose.elastic.stage.yml but it starts to recreate existing ELK containers. I have tried to play with docker-compose settings but no luck so far. Any suggestions?

Just for reference, kibana is not included in dev, because we dont need it there.

docker-compose.elastic.stage.yml

I have a table of keywords. I want to query the keywords table given a string of text and return the keywords found. I was able to get this working in Elasticsearch using this solution. Is this something that is possible in Postgres using the available text search functions? How would the text search query look?

Example:

I would like to repeat the hyperparameter tuning (alpha and/or lambda) of glmnet in mlr3 to avoid variability in smaller data sets

In caret, I could do this with "repeatedcv"

Since I really like the mlr3 family packages I would like to use them for my analysis. However, I am not sure about the correct way how to do this step in mlr3

Example data

I have a beautiful mlr3 ensemble model (combined glmnet and glm) for binary prediction, see details here

I am trying to index json string file to Elastic Search using C# NEST library. I found this post which is related. But there is a syntax error at .Index

We've deployed an ElasticSearch cluster via Azure Marketplace (the "Self-Managed" flavor) it deploys the cluster as a VM Availability Set. However, we want to be able to scale up the number of data nodes when needed, similar to how we can do with our other VM Scale Sets (very easy to accomplish in Azure). Reading the article here: https://www.elastic.co/blog/deploying-elasticsearch-on-microsoft-azure (see the last paragraph of the "Availability" section), it even mentions taking this approach, although it doesn't give instructions on how to accomplish this (the Scale Sets link just leads to a general description of VM scale sets).

Does anyone know how to get ElasticSearch set up in Azure as a Scale Set instead of Availability Set?

EDITED - Based on comments of @opster elasticsearch ninja, I edited original question to keep it focused on low disk watermarks error for ES.

For more general server optimization on small machine, see: Debugging Elasticsearch and tuning on small server, single node

For original follow up on the original question and considerations related to debugging ES failures, also: https://chat.stackoverflow.com/rooms/213776/discussion-between-opster-elasticsearch-ninja-and-user305883

Problem : I noticed that elasticsearch is failing frequently, and need to restart the server manually.

This question may relate to: High disk watermark exceeded even when there is not much data in my index

I want to have a better understanding about what elasticsearch will do if the disk size fails, how to optimise configuration and only afterwards eventually restart automatically when system fails.

Could you help in understanding how to read the elasticsearch journal and make a choice to fix the problems accordingly, suggesting best practices to tune server ops on a small server machine ?

My priority is not to have system crash; it is ok to have a bit less performance, no budget to increase server size.

Hardware

I am running elasticsearch on a single small server (2GB), have 3 index (500mb, 20mb and 65mb of store size) and several GB free on disk (state solid) : I would like to allow use virtual memory VS consuming RAM.

Below what I did:

What does the journal say?

journalctl | grep elasticsearch> explore failures related to ES.

I have tried to install Elastic search on AWS with 3 instances with 1 master node and 2 data nodes. I have followed the steps mentioned https://www.elastic.co/blog/running-elasticsearch-on-aws.

Below is the elasticsearch.yml setting that I have edit based on the need.

Context: I want to use Spring-Data to connect to ElasticSearch and retrieve data searching for at least two letters in any position of the word.

Examples:

Loaded these two documents: