Understanding of Elasticsearch external service and evolution of usage in the PEGA application

In this post, let’s understand the Elasticsearch service and the evolution of usage in the Pega versions. Elasticsearch is a robust, scalable, and distributed text-based search engine. It is used for Real-time search, Full-text search, Log analytics and monitoring applications. Many organisations maintain their elastic search as a stand-alone central hub app. Other applications like [Front-end web apps, Salesforce, AWS API Gateway APIs, etc…] can leverage the external elastic search service for indexing or search-related requirements. So, understanding how elastic search works is really important. Organisations can leverage the external service from cloud [AWS, Google, Azure, etc…] service providers, stand-alone apps in VM or can run in containers using docker images.

Conventional PEGA product has the elastic search product as an embedded service. Then from PEGA 8.6 onwards provided the capability to connect to an external elastic search service using the provided plugin. From PEGA 8.8 onwards, with Kubernetes deployment recommendation - PEGA provided a separate docker image — Search Reporting Service to connect to an external elastic search. Elasticsearch reduces the database queries in the case of global search and reporting scenarios. Kibana is used as a data analytics and…