mentorhub-elasticsearch

This repository builds a containerized utility that is used to configure the Elasticsearch database used by mentorHub for search services, and optionally load test data harvested from a MongoDB database.

DISCLAIMER

Running the Elasticsearch and Kibana backing services as containers will cause you to download quite large docker images. If you are working in a capacity or performance constrained environment you should schedule the downloading of these images accordingly.

Prerequisites

• Docker Desktop
• MentorHub Developer Edition
• NodeJS and NPM

Customize configuration

See Tsconfig Reference

Contributing

The ./src/configure.ts script is the entrypoint for this utility.

Seperation of Concerns

The ./src/config folder contains runtime configuration management code. The ./src/utils folder contains mongodb and elasticsearch IO functions.

Workflow

You should do all work in a feature branch, and when you are ready to have your code deployed to the cloud open a pull request against that feature branch. Do not open a pull request without first building and testing the containers locally.

Build

To build code for production deployment

npm run build

Testing changes locally

To start the backing service and run the script locally use this script.

npm run start

NOTE: This command does a mh down to initialize the docker environment before starting the elasticsearch database with kibana.

Testing changes without backing services

To run the script locally without starting any backing services use this script.

npm run local

Build and run the container

Use the following command to build and run the container with backing services.

npm run container

Test the output

Use this command to test the output

npm run test

Using Kibana to verify configuration

The docker compose file always starts Kibana along with ElasticSearch. You can use the Kibana dashboard. Choose Dev Tools from the hamburger menu, to run queries or review configurations of the Elasticsearch database. Here are a few handy elasticsearch queries to run in Kibana:

List Indexes

GET /_cat/indices

Get all indexed documents

GET mentorhub/_search

Delete the index and all data

DELETE /mentorhub

Find all documents

GET mentorhub/_search

Find all curriculum documents

GET mentorhub/_search
{
  "query": {
    "match": {
      "collection_name": "curriculum"
    }
  }
}

Find all inactive people documents

GET mentorhub/_search
{
  "query": {
    "query_string": {
      "query": "Inactive people"
    }
  }
}

Elasticsearch docker reference

this guide provides valuable configuration and troubleshooting guides for the elasticsearch container.