WGCLOUD: A Lightweight Distributed Server Monitoring System for Linux and Windows

What WGCLOUD monitors and who it is for

WGCLOUD is a distributed server monitoring system designed for operations teams who need broad hardware and software visibility without complex configuration. The README describes it as a new-generation minimal operations monitoring system that promotes rapid deployment and minimizes the learning curve.

The system collects a wide range of metrics from each monitored host. On the hardware side, it tracks CPU usage, CPU temperature, memory usage, disk capacity, disk I/O read and write rates, disk IOPS, disk SMART health status, GPU information, MAC addresses, BIOS information, and motherboard details. On the software side, it monitors running processes, open ports, Docker containers, log files, firewall status, crontab entries, and recent user login records.

Beyond individual host metrics, WGCLOUD monitors service APIs, network devices such as switches, routers, and printers, databases, and Kubernetes clusters. It can execute commands across multiple hosts simultaneously (batch command dispatch) and provides web-based SSH access that functions as a bastion host. The target audience is operations teams managing a mix of Linux, Windows, and Unix servers who want a single interface rather than separate tools for each concern.

Server-agent architecture and data flow

WGCLOUD uses a server-agent model. Each monitored host runs the agent component, which collects local metrics and reports them to the central server. The README states that the agent reports every 2 minutes by default, but this interval is configurable. The server receives the data, processes it, stores it in the database, and renders charts and dashboards in the web interface.

The README notes that version 2.3.7 replaced the earlier SIGAR-based metric collection with the OSHI library. OSHI is a Java library that collects operating system and hardware information via native APIs. This change affects which JDK versions are required and which platforms are supported.

The communication between agent and server uses HTTP. The README includes a diagram showing this topology, labeled as an HTTP protocol communication diagram. The server end handles all chart generation and data processing, which keeps the agent lightweight. The README states the system can support thousands of hosts monitored simultaneously, with the agent running on each.

The server component is built on Spring Boot and Bootstrap. The architecture is described as a distributed monitoring system built on a microservices pattern. The source code for both the server and agent is in the `wgcloud-server/` and `wgcloud-agent/` directories respectively.

Installation and initial setup

The README describes the setup process in terms of development tools and database initialization. For development, the project can be opened with IntelliJ IDEA directly (recommended) or imported as a Maven project in Eclipse. The JDK version must be 1.8 or JDK11.

The database backend is MySQL. The README specifies creating a database named `wgcloud` and importing the `wgcloud.sql` file found in the `sql/` directory. WGCLOUD also supports MariaDB, PostgreSQL, and Oracle as alternatives. The SQL import creates the schema and any seed data required for the application to start.

For production deployment, the README describes using pre-built JAR files alongside shell scripts in the `bin/` directory. These scripts start and stop the server and agent components on Linux and Windows. The release JAR is named `wgcloud-server-release.jar`, and the scripts must be placed in the same directory as the JAR to work correctly.

Online documentation and the commercial version download are both at wgstart.com. The open-source repository is version v2.3.7, while the commercial version receives more frequent updates and is recommended for production environments by the README.

Platform support matrix

The README documents a broad platform support matrix. On Linux, WGCLOUD monitors Debian, RedHat, CentOS, Ubuntu, Fedora, SUSE, and less common distributions such as Kylin (Qilin), UOS (Tongxin), and LoongArch (MIPS-based Loongson). Windows support covers Windows Server 2008 R2 through Windows Server 2025, and client Windows from Windows 7 through Windows 11. Unix support includes Solaris, FreeBSD, and OpenBSD. macOS support covers both amd64 and arm64 architectures.

Additional support is listed for ARM, Android, RISC-V (riscv64), IBM S/390 (s390x), Raspberry Pi, and AIX. This coverage is unusually broad for a monitoring system, and suggests that the OSHI library's platform support directly maps to what WGCLOUD can monitor.

The Windows monitoring includes Windows service lists, which the README calls out specifically. This matters for organizations that run mixed Linux and Windows server environments and need a single monitoring dashboard rather than separate tools for each platform.

For container environments, WGCLOUD monitors Docker containers individually. For Kubernetes, the feature list includes K8S monitoring, though the README does not describe the depth of Kubernetes visibility in the open-source version.

Feature scope beyond basic metrics

WGCLOUD includes several features that go beyond graph-based metric display. The big-screen display (daping) mode renders metrics in a large-format visualization suitable for a network operations center screen. The topology diagram feature automatically generates a network topology map from discovered devices.

The file integrity monitoring feature detects when monitored files are changed, which is relevant for detecting unauthorized modifications to configuration files or binaries. The alert system sends notifications through email, DingTalk (a Chinese enterprise messaging platform), WeChat, and SMS.

The SNMP monitoring feature supports network devices that expose metrics via SNMP, such as switches, routers, and printers. The middleware monitoring covers Redis, Nginx, Kafka, and databases. Asset management and task scheduling are also included.

The README notes an AI auto-analysis feature, though it does not describe the implementation or what AI model or service powers it. Password management and work notes are listed as additional features, suggesting that WGCLOUD is positioned as an operations workspace rather than a standalone metrics collector.

Open-source version versus commercial version

The repository holds the open-source version at v2.3.7. The README is direct about the trade-off: the commercial version has more features, better performance, stronger security, greater stability, more frequent version updates, and better support. The README recommends the commercial version for production environments.

The commercial version is available at wgstart.com and is described as free to use but not open-source. This means the source code is not available for inspection or modification. The README does not enumerate which specific features are exclusive to the commercial version.

For teams that need to inspect and audit the code they run in production, the open-source v2.3.7 is the only option. For teams that need ongoing security patches and new feature delivery and are comfortable with a closed-source tool, the commercial version may be more appropriate.

The project is licensed under Apache-2.0, which permits commercial use and modification of the open-source version. Contributions to the open-source repository are welcomed, and the README requests that users add links to the project on their blogs or websites rather than financial contributions.

WGCLOUD versus Prometheus and Grafana

The dominant open-source monitoring stack for infrastructure is Prometheus for metric collection and Grafana for visualization. These tools are composable: a separate exporter runs on each host or service and exposes metrics that Prometheus scrapes. Grafana queries Prometheus and renders dashboards. The community maintains hundreds of exporters for every common service.

WGCLOUD is an integrated alternative. It collects metrics through its own agent without requiring per-service exporters, and it renders its own dashboards without Grafana. This reduces the number of moving parts in the monitoring stack, which is the main reason to choose WGCLOUD. The trade-off is flexibility: Prometheus with custom exporters can monitor anything with a programmable interface, while WGCLOUD monitors what its agent knows how to collect.

For teams starting from scratch without existing Prometheus infrastructure, WGCLOUD's faster initial setup is a genuine advantage. For teams with existing Prometheus dashboards and alert rules, migrating to WGCLOUD would mean rebuilding that configuration. The last push to the WGCLOUD repository was on 2026-09-04, with v3.7.0 released on 2026-09-03, confirming active development.

Editorial conclusion

WGCLOUD suits operations teams who need a self-hosted monitoring system that covers a broad range of metrics from a single web dashboard, runs without installing Prometheus exporters or writing Grafana dashboards, and supports both Linux and Windows servers. It is not the right choice for teams with existing Prometheus and Grafana infrastructure, since those ecosystems are more composable and have a larger community of exporters. Before deploying WGCLOUD, review the LICENSE for the open-source version, compare the feature list between v2.3.7 (open source) and the commercial version at wgstart.com, and confirm that your JDK version is 1.8 or JDK11 as documented.

Frequently asked questions

Official sources

1. License: Apache-2.0
2. Project website
3. README
4. Releases
5. tianshiyeben/wgcloud on GitHub