Docs
  • Release notes
  • Troubleshoot
  • Reference
  • Elastic fundamentals
  • Solutions and use cases
  • Manage data
  • Explore and analyze
  • Deploy and manage
  • Manage your Cloud account and preferences
  • Troubleshoot
  • Release notes
  • Reference
  • Extend and contribute
  • Contribute to the docs
  • The Elasticsearch data store
    • Index basics
      • Perform operations on indices
    • Near real-time search
    • Data streams
      • Set up a data stream
      • Use a data stream
      • Modify a data stream
      • Manage a data stream
      • Time series data streams
        • Quickstart
        • Set up a TSDS
        • Downsampling
          • Concepts
          • Configuration
          • Querying
        • Advanced topics
          • Time-bound indices
          • Reindex a TSDS
          • OTLP/HTTP endpoint
      • Logs data stream
      • Failure store
        • Using failure stores to address ingestion issues
    • Mapping
      • Dynamic mapping
        • Dynamic field mapping
        • Dynamic templates
      • Explicit mapping
      • Runtime fields
        • Map a runtime field
        • Define runtime fields in a search request
        • Override field values at query time
        • Retrieve a runtime field
        • Index a runtime field
        • Explore your data with runtime fields
      • Removal of mapping types
      • Update mapping API examples
    • Text analysis
      • Concepts
        • Anatomy of an analyzer
        • Index and search analysis
        • Stemming
        • Token graphs
      • Configure text analysis
        • Test an analyzer
        • Configuring built-in analyzers
        • Create a custom analyzer
        • Specify an analyzer
    • Templates
      • Simulate multi-component templates
      • Ignore missing component templates
    • Aliases
    • Manage data from the command line
  • Ingest: Bring your data to Elastic
    • Ingesting time series data
    • Ingesting data for Elastic solutions
    • Ingesting data from applications
      • Ingest data with Node.js
      • Ingest data with Python
      • Ingest data from Beats with Logstash as a proxy
      • Ingest data from a relational database
      • Ingest logs from a Python application using Filebeat
      • Ingest logs from a Node.js web application using Filebeat
    • Ingest architectures
      • Elastic Agent to Elasticsearch
        • Elastic Agent to Elasticsearch: Agent installed
        • Elastic Agent to Elasticsearch: APIs for collection
      • Elastic Agent to Logstash to Elasticsearch
        • Elastic Agent to Logstash (for enrichment) to Elasticsearch
        • Elastic Agent to Logstash to Elasticsearch: Logstash Persistent Queue (PQ) for buffering
        • Elastic Agent to Logstash to Elasticsearch: Logstash as a proxy
        • Elastic Agent to Logstash for routing to multiple Elasticsearch clusters and additional destinations
      • Elastic Agent to proxy to Elasticsearch
      • Elastic Agent to Elasticsearch with Kafka as middleware message queue
        • Elastic Agent to Logstash to Kafka to Logstash to Elasticsearch: Kafka as middleware message queue
        • Elastic Agent to Logstash to Kafka to Kafka ES Sink to Elasticsearch: Kafka as middleware message queue
      • Logstash to Elasticsearch
      • Elastic air-gapped architectures
        • Elastic Agent to Elasticsearch: Air-gapped environment
        • Elastic Agent to Logstash: Air-gapped environment
    • Sample data
    • Upload data files
    • Transform and enrich data
      • Calculate the ingest lag metadata
      • Elasticsearch ingest pipelines
        • Example
        • Create readable and maintainable ingest pipelines
        • Error handling
      • Logstash pipelines
      • Data enrichment
        • Set up an enrich processor
        • Example: Enrich your data based on geolocation