Container Log Aggregation Tools

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

SigNoz is a full-stack observability platform designed to collect, store, and visualize metrics, logs, and distributed traces in a unified environment. It leverages OpenTelemetry-based data collection to ingest telemetry from diverse sources using vendor-neutral protocols, ensuring interoperability across complex microservices architectures. The platform utilizes a high-performance columnar storage engine to enable rapid aggregation and filtering, providing a centralized backend for monitoring application health and performance. What distinguishes the platform is its focus on automated instru

HertzBeat is an agentless monitoring platform designed to collect performance metrics from network devices, databases, and servers without requiring client software. It functions as an infrastructure monitoring dashboard, an alert management system, and a centralized log aggregator using the OpenTelemetry Protocol. The system utilizes a cloud-edge collection hierarchy to scale data gathering across clusters and isolated networks. It distinguishes itself with a flexible extensibility model, allowing users to define new monitoring workflows through configuration-based metric templates and custo

SkyWalking is an application performance monitoring system and observability platform designed to collect and analyze metrics, traces, and logs from distributed microservices. It functions as a distributed tracing platform and a telemetry data pipeline that ingests and aggregates observability data from various language agents. The project features an AI-powered anomaly detector that uses machine learning to calculate metric baselines and identify irregular URI patterns. It includes an eBPF performance profiler for diagnosing CPU and network bottlenecks at the kernel level and generates inter

SkyWalking is a comprehensive observability stack and application performance monitoring platform. It functions as a distributed tracing system and an AI application monitor, providing a centralized suite for collecting and analyzing logs, metrics, and traces to maintain the health of containerized architectures. The platform distinguishes itself through a service topology visualizer that renders interactive maps of infrastructure dependencies and communication patterns. It also includes specialized capabilities for generative AI workflow observation to track the execution flow and performanc

This project is a containerized orchestration layer for the Elastic Stack, providing a pre-configured set of Docker Compose files to deploy Elasticsearch, Logstash, and Kibana as a unified data analysis stack. It functions as a centralized log management system for ingesting, indexing, and searching log data using a cluster of interconnected services. The deployment pattern includes an Elasticsearch cluster manager that enables scaling data nodes through replica scaling and internal discovery. It provides a web-based administration interface for monitoring cluster health and status. The syst

Loki is a horizontally scalable, highly available log aggregation engine designed to store and query massive volumes of unstructured log data. It functions as a distributed observability platform that correlates logs, metrics, and traces to provide comprehensive visibility into the health and performance of complex infrastructure. The system distinguishes itself through a distributed query execution model that processes large datasets in parallel across cluster nodes. It utilizes label-based stream indexing and a distributed index to map log data to specific chunks, enabling rapid retrieval w

Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r

hl is a set of command-line interface tools for filtering, aggregating, streaming, and visualizing structured log data across multiple sources. It functions as a log filter, file aggregator, real-time streamer, and structured log viewer. The project specializes in transforming JSON and logfmt data into human-readable formats for visual analysis. It enables the merging of multiple log files and compressed archives into a single chronologically sorted stream, while supporting live tracking of multiple sources into a unified real-time view. Capabilities include field-based filtering via key-val

VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct

ngxtop is a real-time web server dashboard and traffic analyzer that transforms raw Nginx access logs into immediate visual metrics. It functions as a live monitor for tracking request rates, response codes, and bandwidth usage by parsing server logs as they are written. The tool extracts performance data from combined, common, and JSON log structures. It uses these parsed logs to identify high-traffic endpoints and server error patterns for troubleshooting. The system processes log streams through a pipeline that includes schema-based extraction, record filtering via evaluatable expressions

GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

Dozzle is a web-based dashboard designed for the real-time monitoring and management of Docker container environments. It provides a centralized interface to stream live logs, track resource utilization, and perform administrative tasks across multiple host environments. The platform distinguishes itself by offering an interactive terminal emulator that allows users to execute commands directly within running containers from a browser. It also includes built-in alerting capabilities, enabling users to monitor log streams for specific patterns and receive automated notifications when critical

Serilog is a structured logging library for .NET applications that records events as rich data objects instead of plain text strings. It functions as a multi-sink framework, allowing a single log stream to be emitted to diverse destinations such as files, consoles, and cloud databases through a structured event pipeline. The framework distinguishes itself through dynamic metadata enrichment, using log event enrichers to add contextual properties and telemetry to logs for improved traceability and analysis. It employs a routing system that filters, enriches, and directs these structured events