What Is Elastic Stack?
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Elastic Stack, formerly known as ELK stack, includes:
- Elasticsearch: the search engine where all your data is stored.
- Logstash: the tool to parse, enrich, and filter data before storing them into Elasticsearch.
- Kibana: the tool to visualize data stored in Elasticsearch.
Elastic Stack also includes Beats - lightweight shippers (agents lighter than Logstash) to get, parse, and store data:
- Filebeat: used (mainly) to analyze Linux/Unix log files.
- Packetbeat: used to analyze network packets.
- Winlogbeat: used to analyze Windows events.
Elastic Stack includes many other tools, but they are out of the scope of this introductory post.
You can get Elastic Stack as:
- Opensource: downloadable from GitHub but also from Opendistro;
- Basic: free product with limited features;
- Licensed (Gold, Platinum, Enterprise): including features like auditing, LDAP authentication, alerting, machine learning… (see subscription page for more details).
Elastic Common Schema (ECS)
Recently ELK users started to realize that injecting logs is not enough. Correlating logs requires to have in a standard form. ECS is the suggested (not mandatory) format to inject log: each log injected into Elastic Stack should be translated to adhere to ECS format.
If you start using ECS you’ll be able to:
- correlate events from different sources
- share and reuse dashboards
ECS covers how documents inserted into Elastic Stack should be structured, but does not (currently) cover indexes. It’s also not all-encompassing; for example, it’s still missing a reference to email objects.
On the positive side, the ECS maintainers are willing to receive proposals, and are fast enough to discuss and integrate changes into official ECS releases.