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Heartbeat, ELK Stack

Heartbeat: A heartbeat in distributed systems is a periodic signal or message sent by a node or component to inform others of its operational status and health.

Purpose:

  • Liveness Monitoring: Heartbeats help detect if a node or process is alive and responsive. If heartbeats stop, it may indicate a failure.
  • Failure Detection: They are crucial for timely identification of node failures or network partitions.
  • Load Balancing: In load balancing scenarios, heartbeats can be used to distribute incoming requests efficiently.
  • Resource Allocation: Heartbeats may convey information about resource availability or utilization.

How it Works:

  • Nodes or processes periodically send heartbeat signals/messages to a central coordinator or to one another.
  • If a node stops sending heartbeats within a predefined time (timeout), it is considered unavailable or failed.
  • Failure detection mechanisms can trigger actions like node recovery, redistribution of work, or raising alerts.

ELK Stack:

Elasticsearch:

  • Purpose: A distributed, RESTful search and analytics engine designed for horizontal scalability and real-time search.
  • Use Cases: Storing, searching, and analyzing large volumes of data, such as logs, metrics, and application-generated data.
  • Features: Full-text search, Fuzzy search, schema-free JSON documents, near real-time indexing, and extensive querying capabilities.

Logstash:

  • Purpose: A server-side data processing pipeline that ingests data from multiple sources, transforms it, and sends it to Elasticsearch.
  • Use Cases: Data ingestion, transformation, and enrichment for logs, metrics, and other events.
  • Features: Numerous input, filter, and output plugins for handling diverse data formats and sources.

Kibana:

  • Purpose: A web-based visualization and exploration tool for Elasticsearch data.
  • Use Cases: Creating dashboards, visualizations, and exploring data stored in Elasticsearch.
  • Features: Graphical representation of data, real-time monitoring, and user-friendly dashboards.

Workflow:

  • Ingest: Logstash ingests data from various sources, applies filters, and processes it.
  • Store: Processed data is stored in Elasticsearch, which can handle large-scale data storage and querying.
  • Visualize: Kibana provides a user interface to create visualizations and dashboards for data exploration.