dromara/hertzbeat

Features

• Agentless Collections - Gathers performance data from applications and networks using standard protocols without requiring local agent installations.
• Infrastructure Monitoring - Collects performance metrics from servers, databases, and network hardware without requiring local software agents.
• AI-Driven Observability Interfaces - Uses large language models to process monitoring data and generate system insights.
• Real-time Event Triggers - Detects critical system events and triggers immediate notifications to ensure rapid response to infrastructure failures.
• Alert Thresholds - Processes alerts through configurable threshold rules to determine when notifications should be dispatched.
• Alert Managers - Functions as an infrastructure alerting manager that triggers real-time alerts based on metric thresholds.
• Centralized Logging Systems - Consolidates system logs from various sources into a single location using the OTLP protocol.
• Log Aggregation - Consolidates system logs from various sources into a single location using the OpenTelemetry Protocol.
• Agentless Collection - Provides agentless gathering of performance data from servers, databases, and network hardware using standard protocols.
• Automated Alerting Workflows - Sets threshold rules to detect critical system failures and dispatches notifications via webhooks or messaging channels.
• Rule-Based Alerting Engines - Triggers real-time notifications by comparing incoming metrics against preconfigured numerical limits and status rules.
• Multi-Channel Alerting Engines - Dispatches health and error notifications across multiple third-party communication platforms via webhooks and messaging.
• Real-Time Monitoring Systems - Tracks the health and behavior of applications and infrastructure in real-time to detect issues and analyze patterns.
• System Monitoring Platforms - Provides a real-time observability platform that collects metrics from servers, databases, and networks without local agents.
• AI-Powered Observability Analysis - Integrates an analysis engine that uses large language models to process monitoring data and generate system insights.
• Collector Cluster Deployments - Distributes data collection across multiple nodes in public or private modes to scale monitoring reach.
• High Availability Clustering - Utilizes distributed collector clustering to ensure high availability and scale data gathering across large networks.
• Horizontal Scaling Tools - Expands data collection capacity through the horizontal scaling of multi-collector clusters.
• Cloud-Edge Collaborative Architectures - Implements a cloud-edge collaborative architecture to optimize data throughput and reduce latency during collection.
• Distributed Metric Collection - Scales data gathering across multiple collector nodes and cloud-edge environments to monitor large-scale networks.
• Log Aggregation Systems - Provides a centralized system for consuming and consolidating logs using the OpenTelemetry Protocol.
• AI-Powered Analysis Engines - Integrates an analysis engine that uses large language models to process monitoring data and generate system insights.
• Public Status Pages - Creates real-time dashboards to communicate the operational health and availability of services to external users.
• YAML Templates - Uses YAML templates to define custom metric collection logic and protocol specifications for dynamic extensions.
• Metric Collection Templates - Allows the definition of YAML templates to collect new metric types for specific protocols and service types.
• Custom Telemetry Extensions - Enables the extension of monitoring capabilities via YAML templates to track proprietary or specialized systems.
• Infrastructure Monitoring - Agentless, real-time monitoring system for web services and middleware.
• Monitoring - Real-time monitoring system with agentless support.
• Self-Hosted Status Pages - Real-time monitoring system with agentless status page capabilities.

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