dromara/hertzbeat
Hertzbeat
HertzBeat is a real-time observability platform that provides agentless monitoring for servers, databases, and networks. It functions as an infrastructure alerting manager, an OpenTelemetry Protocol log aggregator, and a public status page generator.
The platform integrates an analysis engine that uses large language models to process monitoring data and generate system insights. It utilizes a cloud-edge collaborative architecture and distributed collector clustering to scale data gathering across large-scale networks.
The system covers a broad range of observability capabilities, including threshold-based alerting, centralized log aggregation, and the use of YAML templates to define custom metric collection for specific protocols and services. It supports multi-channel alert dispatch via webhooks and messaging platforms to communicate critical system failures.
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.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
