Which core open source component of the Elastic-stack is responsible for accepting the data in its native format and making elements of the data consistent across all sources?

1. Beats: Beats are lightweight, single-purpose data shippers. They are used to send data from hundreds or thousands of machines and systems to Logstash or Elasticsearch. Each Beat is tailored to ship specific types of data, like logs, metrics, or network packet data.
2. Elasticsearch: This is a distributed search and analytics engine. It is the core component that stores all the data you send to the Elastic Stack. Elasticsearch allows you to search, analyze, and visualize the data in real time.
3. Kibana: Kibana is a web interface for searching and visualizing logs and time-stamped data. It provides graphical representation of the Elasticsearch data and is used to create dashboards that enable users to interact with their data.
4. Logstash: This is the correct answer for the question. Logstash is a server-side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to Elasticsearch. Logstash is equipped with an extensive plugin ecosystem that transforms and prepares your data regardless of the source or format – this includes making disparate data from various sources consistent and queryable.

In summary, Logstash is responsible for centralizing, transforming, and preparing data before it is indexed into Elasticsearch. It can dynamically unify data from disparate sources and normalize the data, making it ready for further analysis and visualization in Kibana.