![]() ![]() ![]() From Kibana, users can create powerful visualizations of their data, share dashboards, and manage the Elastic Stack. Once indexed in Elasticsearch, users can run complex queries against their data and use aggregations to retrieve complex summaries of their data. Data ingestion is the process by which this raw data is parsed, normalized, and enriched before it is indexed in Elasticsearch. Raw data flows into Elasticsearch from a variety of sources, including log files, system metrics, and web applications. In conclusion, the Elastic Stack makes the log management process a very simple task. This form of scalability allows it to handle huge amounts of data. The shard component initiates the feature of redundancy, which can overcome issues like hardware failures. Related data is often stored in the same index, which consists of one or more primary shards, and zero or more replica shards. Rebalancing and routing are done automatically. The created indices are divided into components called shards (explained below) and each shard can have zero or more replicas. Elastic Stack is scalable and distributed. That’s why it is well suited for time-sensitive use cases such as security analytics and infrastructure monitoring.
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