1. Project Overview

DataSophon

Helps you manage and monitor clusters more easily

A next-generation cloud-native big data management platform designed to help users quickly build stable, efficient, and elastically scalable cloud-native big data platforms.

Vision

Dedicated to rapidly deploying, managing, monitoring, and automating the operations and maintenance of cloud-native big data platforms, helping you quickly build stable, efficient, and elastically scalable cloud-native big data platforms.

2. Open Source License

Licensed under Apache-2.0

3. Screenshots

4. Feature Overview

What is DataSophon?

"The Three-Body Problem," winner of the Hugo Award, the highest honor in science fiction literature, is widely known for its stunning hard science fiction style. Its author, Liu Cixin, has been praised for "single-handedly elevating Chinese science fiction to a world-class level."

As a key character in The Three-Body Problem, the Sophon is created by unfolding a nine-dimensional proton into two dimensions, transforming it into a supercomputer through circuit etching, and then returning it to the microscopic eleven-dimensional space to monitor every human action. It uses quantum entanglement to transmit instant reports to the Trisolarian civilization four light-years away. Simply put, the Sophon is an AI-powered real-time remote monitoring and management platform deployed on Earth by the Trisolarian civilization.

DataSophon is also a similar management platform. However, unlike the Sophon, whose purpose is to lock down humanity's fundamental sciences and prevent technological breakthroughs, DataSophon is dedicated to rapidly deploying, managing, monitoring, and automating the operations and maintenance of cloud-native big data platforms, helping you quickly build stable, efficient, and elastically scalable cloud-native big data platforms.

Main Features

• Easy Deployment: Users can complete initial environment configuration in just a few steps, enabling rapid deployment of large-scale big data clusters supporting thousands of nodes.

• Comprehensive Open-Source Ecosystem Compatibility: Built on an open management architecture, it integrates various commonly used big data components covering every stage of big data processing, including data integration, data storage, computing engines, task scheduling, and permission management.

• Complex Environment Compatibility: Its minimalist architecture makes it easy to adapt to various complex environments. It supports mixed deployments on ARM and x86 machines, as well as commonly used Linux-based operating systems.

• Convenient Operations and Maintenance: Based on real-world production practices, it displays the monitoring metrics users care about most. Clusters, nodes, and services can be easily monitored and managed, significantly improving operational efficiency.

• Security and Reliability: DataSophon supports Kerberos authentication and data encryption, and uses Ranger for data access control, providing data encryption and permission management to ensure data security.

• Convenient Alerts: Supports alert group and alert metric management, with comprehensive monitoring metrics. Users can customize alert groups and metrics according to their monitoring requirements.

5. Tech Stack

Product Architecture

Technical Architecture

Integrated components

All integrated components have undergone compatibility testing and have been running reliably in big data clusters with more than 300 nodes, processing approximately 400 billion records per day. Even with massive data volumes, tuning costs for the various big data components remain low. The platform displays commonly used configurations and those that users need to optimize by default.

Sequence number	Name	Version	Description
1	HDFS	3.3.3	Distributed Big Data Storage
2	YARN	3.3.3	Distributed Resource Scheduling and Management Platform
3	ZooKeeper	3.5.10	Distributed Coordination System
4	FLINK	1.15.2	Real-Time Computing Engine
5	DolphoinScheduler	3.1.1	Distributed, Easily Extensible Visual Workflow Task Scheduling Platform
6	StreamPark	1.2.3	High-Performance Stream Processing Development Framework, a Cloud-Native Platform Integrating Stream and Batch Processing & Lakehouse Architecture
7	Spark	3.1.3	Distributed Computing System
8	Hive	3.1.0	Offline Data Warehouse
9	Kafka	2.4.1	High-Throughput Distributed Publish-Subscribe Messaging System
10	Trino	367	Distributed SQL Interactive Query Engine
11	Doris	1.1.5	Next-Generation Ultra-Fast MPP Database for All Scenarios
12	Hbase	2.4.16	Distributed Columnar Storage Database
13	Ranger	2.1.0	Permission Control Framework
14	ElasticSearch	7.16.2	High-Performance Search Engine
15	Prometheus	2.17.2	High-Performance Monitoring Metrics Collection and Alerting System
16	Grafana	9.1.6	Monitoring, Analytics, and Data Visualization Suite
17	AlertManager	0.23.0	Alert Notification Management System

Source: DataSophon Official Documentation