What is ELK stack?
- Elasticsearch [https://www.elastic.co/elasticsearch]
- Logstash [https://www.elastic.co/logstash]
- Kibana [https://www.elastic.co/kibana]
What is it used for?
- aggregates logs from all systems and applications
- logs analytics
- visualizations for application and infrastructure monitoring, faster troubleshooting, security analytics etc.
Elasticsearch
- distributed search and analytics engine built on Apache Lucene
- licensed, not open source
- OpenSearch is open-sourced alternative (supported by AWS)
- FluentD is another open-source data collection alternative
- data in the form of JSON documents is sent to Elasticsearch using:
- API
- ingestion tools
- Logstash
- Amazon Kinesis Data Firehose
- the original document automatically stored and a searchable reference is added to the document in the cluster’s index
- Elasticsearch REST-based API is used to manipulate with documents:
- send
- search
- retrieve
- uses schema-free JSON documents
- distributed system
- enables it to process large volumes of data in parallel, quickly finding the best matches for your queries
- operations such as reading or writing data usually take less than a second to complete => Elasticsearch can be used for near real-time use cases such as application monitoring and anomaly detection
- has support for various languages: Java, Python, PHP, JavaScript, Node.js, Ruby etc...
- .
Logstash
- log shipper
- helps easily transform source data and load it into Elasticsearch cluster
- .
Filebeat
- https://www.elastic.co/beats/filebeat
- log shipper
- both Filebeat and Logstash can be used to send logs from a file-based data source to a supported output destination
- Filebeat is a lightweight option, ideal for environments with limited resources and basic log parsing needs. Conversely, Logstash is tailored for scenarios that demand advanced log processing
- both FB and LS can be used in tandem when building a logging pipeline with the ELK Stack because both have a different function .
Kibana
- visualisation and reporting tool
- used with Elasticsearch to:
- visualize the data
- build interactive dashboards
- .
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