ElasticSearch Communication & Stakeholder Relations 3

Question 1

An executive asks why the engineering team wants to increase the number of shards before a major data ingestion event. What is the clearest business justification?

Accepted Answer

More shards allow Elasticsearch to distribute indexing and search workload across more nodes in parallel, improving throughput and reducing per-node load

Answer

Shards are the unit of parallelism in Elasticsearch; increasing shard count before a data surge distributes the load across the cluster.

Question 2

A project manager asks what a 'yellow' cluster health status means and whether they should be alarmed. What is the correct explanation?

Accepted Answer

Yellow means all primary shards are active but at least one replica shard is unassigned, so data is available but redundancy is reduced

Answer

Yellow status indicates primaries are healthy and data is accessible, but missing replicas mean reduced fault tolerance until reassignment completes.

Question 3

During a post-incident review, a stakeholder asks why a mapping explosion caused cluster instability. How do you explain it?

Accepted Answer

Dynamic field mapping allowed unbounded new fields to be created, exhausting JVM heap memory used to hold mapping metadata

Answer

Unbounded dynamic mapping creates thousands of fields in the cluster state, consuming heap memory on all nodes and causing instability.

Question 4

A non-technical stakeholder wants to understand what 'relevance scoring' means in Elasticsearch. Which explanation is most accurate?

Accepted Answer

Elasticsearch assigns each matching document a numeric score based on how well it matches the query terms, using factors like term frequency and field length

Answer

Elasticsearch uses TF/IDF or BM25 algorithms to compute a _score that reflects how closely a document matches the query, used to rank results.

Question 5

A stakeholder asks why the team is recommending Elasticsearch over a relational database for a log analytics use case. What is the strongest argument?

Accepted Answer

Elasticsearch is optimized for full-text search and aggregations over large volumes of semi-structured log data, with horizontal scalability that relational databases do not provide natively

Answer

Elasticsearch's inverted index, distributed architecture, and aggregation framework make it purpose-built for log search and analytics at scale.

ElasticSearch Practice Test

ElasticSearch Practice Test

ElasticSearch Communication & Stakeholder Relations 3