1. What is Elastic?
Ans:- Elastic is a search and analytics engine that provides solutions for various use cases like full-text search, logging, and data analysis.
2. What is Elasticsearch?
Ans:- Elasticsearch is an open-source, distributed search and analytics engine that is part of the Elastic Stack.
3. What is the Elastic Stack?
Ans:- The Elastic Stack, also known as ELK Stack, is a collection of open-source products for searching, analyzing, and visualizing data.
4. What are the main components of the Elastic Stack?
Ans:- The main components include Elasticsearch, Logstash, and Kibana (ELK). Beats are also commonly used for data shipping.
5. How does Elasticsearch work?
Ans:- Elasticsearch stores and indexes data in a distributed manner, allowing for fast and efficient searching, aggregations, and analytics.
6. What is Logstash?
Ans:- Logstash is a server-side data processing pipeline that ingests data from multiple sources, transforms it, and sends it to a desired destination.
7. What is Kibana?
Ans:- Kibana is a visualization and exploration tool that interacts with Elasticsearch data, providing a user-friendly interface for data analysis.
8. What is Beats in the Elastic Stack?
Ans:- Beats are lightweight data shippers that send data from various sources to Elasticsearch or Logstash.
9. What types of data can Elastic handle?
Ans:- Elastic is versatile and can handle various types of data, including structured and unstructured data.
10. How is data indexed in Elasticsearch?
Ans:- Data in Elasticsearch is indexed based on JSON documents, allowing for flexible and dynamic schemas.
11. What is an index in Elasticsearch?
Ans:- An index in Elasticsearch is a collection of documents that share a common structure.
12. How are search queries performed in Elasticsearch?
Ans:- Elasticsearch uses a powerful query language called Elasticsearch Query DSL for searching and filtering data.
13. What are shards in Elasticsearch?
Ans:- Shards are the basic units of storage in Elasticsearch, and an index can be divided into multiple shards for scalability.
14. How is security implemented in the Elastic Stack?
Ans:- Elastic Stack provides security features like authentication, authorization, and encryption to protect data and access.
15. What is X-Pack?
Ans:- X-Pack is a set of premium features and extensions for the Elastic Stack, providing additional functionality like security, monitoring, and machine learning.
16. What is the license model for Elastic Stack?
Ans:- As of version 7.11, the Elastic Stack is licensed under the Server Side Public License (SSPL).
17. How to install Elasticsearch?
Ans:- Installation instructions for Elasticsearch can be found on the official Elastic website.
18. How to configure Logstash?
Ans:- Logstash is configured using a configuration file where input, filter, and output plugins are defined.
19. How to create visualizations in Kibana?
Ans:- Kibana provides a user interface for creating visualizations such as charts, graphs, and dashboards.
20. Can Elasticsearch be used for time-series data?
Ans:- Yes, Elasticsearch is commonly used for indexing and querying time-series data.
21. What is the role of an analyzer in Elasticsearch?
Ans:- Analyzers in Elasticsearch are used during indexing to tokenize and index text fields.
22. How to handle data backup and recovery in Elasticsearch?
Ans:- Elastic provides various mechanisms for data backup and recovery, including snapshots and restore functionality.
23. What is the role of a mapping in Elasticsearch?
Ans:- A mapping in Elasticsearch defines the data type and properties of fields in an index.
24. How to perform aggregations in Elasticsearch?
Ans:- Aggregations in Elasticsearch allow for the analysis and summarization of data.
25. What is the role of the Ingest Node in Elasticsearch?
Ans:- The Ingest Node is a node in Elasticsearch that allows for the pre-processing of documents before indexing.
26. How to scale Elasticsearch horizontally?
Ans:- Horizontal scaling in Elasticsearch involves adding more nodes to the cluster to distribute the data and workload.
27. What is the purpose of the Cluster Coordination and Master nodes?
Ans:- Cluster Coordination and Master nodes are responsible for managing the cluster state and coordinating activities.
28. How does Elasticsearch handle conflicts during indexing?
Ans:- Elasticsearch uses a versioning system to handle conflicts during indexing.
29. Can Elasticsearch be integrated with other databases?
Ans:- Yes, Elasticsearch can be integrated with various databases and data sources.
30. How to secure Elasticsearch and Kibana?
Ans:- Security in Elasticsearch and Kibana involves setting up authentication, authorization, and encryption.
31. What is the role of a template in Elasticsearch?
Ans:- Templates in Elasticsearch allow for the pre-configuration of index settings and mappings.
32. What is the difference between a query and a filter in Elasticsearch?
Ans:- Queries in Elasticsearch are used for full-text search, while filters are used for exact matching and filtering.
33. How to upgrade Elasticsearch to a new version?
Ans:- Upgrading Elasticsearch involves careful planning and following the upgrade instructions provided by Elastic.
34. How to handle schema changes in Elasticsearch?
Ans:- Elasticsearch’s dynamic mapping allows for flexible handling of schema changes.
35. What is the purpose of the _source field in Elasticsearch?
Ans:- The _source field in Elasticsearch stores the original JSON document that was indexed.
36. How to perform a full-text search in Elasticsearch?
Ans:- Full-text search in Elasticsearch is performed using the Query DSL, which supports various types of queries.
37. What is the role of the Discovery Node in Elasticsearch?
Ans:- Discovery Nodes are responsible for detecting and maintaining the list of nodes in the cluster.
38. How does Elasticsearch handle tokenization and analysis of text fields?
Ans:- Elasticsearch uses analyzers to break down text into individual tokens and applies filters to process those tokens.
39. What are the common challenges in Elasticsearch performance tuning?
Ans:- Performance tuning may involve optimizing queries, increasing hardware resources, and adjusting index settings.
40. Can Elasticsearch be used for geospatial data?
Ans:- Yes, Elasticsearch supports geospatial data and provides geospatial queries and aggregations.
41. What is the role of the Master-eligible node in Elasticsearch?
Ans:- Master-eligible nodes can become master nodes and participate in cluster coordination.
42. How does the Elasticsearch cluster handle node failures?
Ans:- Elasticsearch is designed to handle node failures gracefully through mechanisms like shard replication and allocation.
43. What is the purpose of the Snapshot and Restore feature in Elasticsearch?
Ans:- The Snapshot and Restore feature allows for the backup and recovery of Elasticsearch data.
44. How to monitor an Elasticsearch cluster?
Ans:- Elasticsearch provides monitoring APIs, and third-party tools like the Elastic Stack’s X-Pack offer additional monitoring capabilities.
45. What are the common best practices for securing an Elasticsearch cluster?
Ans:- Best practices include securing network access, enabling authentication, and configuring role-based access control.
46. How to handle index aliasing in Elasticsearch?
Ans:- Index aliasing allows for the association of one or more indices with a single alias, providing flexibility in managing indices.
47. What is the role of the Snapshot Repository in Elasticsearch?
Ans:- The Snapshot Repository is a location where Elasticsearch stores its snapshots, typically in a remote file system or cloud storage.
48. How to handle index rollover for time-series data in Elasticsearch?
Ans:- Index rollover is a technique used to manage time-series data by creating new indices based on predefined conditions.
49. What is the purpose of the Mappings API in Elasticsearch?
Ans:- The Mappings API allows for the dynamic management of index mappings.
50. How to optimize storage usage in Elasticsearch?
Ans:- Techniques for optimizing storage usage include using appropriate data types, compressing data, and optimizing mappings.
