Execution Model
Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud. Availability This functionality is generally available and ready for production usage. Serverless interfaces and procedures might differ from classic Elastic Stack deployments. The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.
Serverless
Generally available
Stack
Generally available
The Logstash event processing pipeline coordinates the execution of inputs, filters, and outputs.
Each input stage in the Logstash pipeline runs in its own thread. Inputs write events to a central queue that is either in memory (default) or on disk. Each pipeline worker thread takes a batch of events off this queue, runs the batch of events through the configured filters, and then runs the filtered events through any outputs. The size of the batch and number of pipeline worker threads are configurable (see Tuning and profiling logstash pipeline performance).
By default, Logstash uses in-memory bounded queues between pipeline stages (input → filter and filter → output) to buffer events. If Logstash terminates unsafely, any events that are stored in memory will be lost. To help prevent data loss, you can enable Logstash to persist in-flight events to disk. See Persistent queues (PQ) for more information.