Elastic Certified Engineer

It is performance-based. Elastic describes it as a rigorous, performance-based exam covering a full range of Elasticsearch skills across operations, development, and more. You do not answer multiple-choice items; you complete hands-on tasks directly against live clusters, and your work is assessed on whether the requested outcome was actually achieved.

Three hours. Elastic states that candidates must complete a series of challenging, real-world, hands-on tasks within three hours, all performed on a collection of Elasticsearch clusters. Because the workload is scenario-driven rather than item-driven, budget your time early and move on from a task that is consuming disproportionate effort.

Practical. Hiroshi Yoshioka, the first person certified, said the exam was not an examination of knowledge but of how well you can implement Elasticsearch as a solution. You are given a use case and asked whether you can solve the problem by combining the different functions of Elasticsearch.

Elastic frames it as a full range of Elasticsearch skills across operations and development. Certified engineers describe preparing around index and cluster management, search, aggregation, Watcher, and machine learning, alongside data processing and ingestion tooling. Treat operations and development as equally weighted in your study plan rather than specialising in one.

A commonly reported path: start with Kibana visualisations, move to data processing and inputs with Logstash, then deepen into Elasticsearch itself - search, aggregation, Watcher, and machine learning - and finally re-read the official documentation on index and cluster management. Structured training such as Elasticsearch Engineer I and II is frequently cited as the point where gaps became obvious.

Certified engineers consistently describe it as hard. One CTO who passed called it "not easy"; another said the certification lets you tackle issues you do not necessarily see in everyday work. The difficulty comes less from obscure features than from needing to select and combine the right functions quickly under time pressure.

Knowing features in isolation but not being able to combine them to solve a stated use case. Candidates who only read documentation and never build clusters tend to struggle. Practise end-to-end scenarios - ingest data, model it, query it, aggregate it, alert on it - so that choosing the right tool under time pressure becomes routine.

Yes, remotely with webcam monitoring. The first certified engineer noted that monitoring via web camera during the examination was more severe than expected, with the proctor paying attention to slight movements of the eyes and mouth. Assume a quiet, private room, a working camera, and no interruptions or second screens.

Those details are not stated in the Elastic blog posts this page is based on, so we do not publish figures that may be out of date. Fees, retake rules, and recertification or validity terms are set by Elastic and change over time - check Elastic's official certification page before booking.

No. Elastic Certified Analyst is a separate, newer credential designed for data analysts who have mastered analysing and observing time-series data using Kibana. It is a distinct certification aimed at a different role, not a revision of the Elastic Certified Engineer exam, and the two should not be confused when planning your study path.