From 407fc9067741144410ae7d8baf51a8d0e2234360 Mon Sep 17 00:00:00 2001
From: Vicla <792850+laiwei@users.noreply.github.com>
Date: Wed, 14 Aug 2024 12:20:11 +0800
Subject: [PATCH] update readme_en (#2099)
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README.md | 17 ++++---
README_en.md | 125 +++++++++++++++++++++++++++------------------------
2 files changed, 78 insertions(+), 64 deletions(-)
diff --git a/README.md b/README.md
index fbbd1756b..fda29e270 100644
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## 夜莺 Nightingale 是什么
-夜莺监控是一款开源云原生观测分析工具，采用 All-in-One 的设计理念，集数据采集、可视化、监控告警、数据分析于一体，与云原生生态紧密集成，提供开箱即用的企业级监控分析和告警能力。夜莺于 2020 年 3 月 20 日，在 github 上发布 v1 版本，已累计迭代 100 多个版本。
+夜莺监控是一款开源云原生观测分析工具，采用 All-in-One 的设计理念，集数据采集、可视化、监控告警、数据分析于一体，与云原生生态紧密集成，提供开箱即用的企业级监控分析和告警能力。夜莺于 2020 年 3 月 20 日，在 GitHub 上发布 v1 版本，已累计迭代 100 多个版本。
夜莺最初由滴滴开发和开源，并于 2022 年 5 月 11 日，捐赠予中国计算机学会开源发展委员会（CCF ODC），为 CCF ODC 成立后接受捐赠的第一个开源项目。夜莺的核心研发团队，也是 Open-Falcon 项目原核心研发人员，从 2014 年（Open-Falcon 是 2014 年开源）算起来，也有 10 年了，只为把监控这个事情做好。
## 快速开始
-- 👉[文档中心](https://flashcat.cloud/docs/) | [下载中心](https://flashcat.cloud/download/nightingale/)
-- ❤️[报告 Bug](https://github.com/ccfos/nightingale/issues/new?assignees=&labels=&projects=&template=question.yml)
-- ℹ️为了提供更快速的访问体验，上述文档和下载站点托管于 [FlashcatCloud](https://flashcat.cloud)
+- 👉 [文档中心](https://flashcat.cloud/docs/) | [下载中心](https://flashcat.cloud/download/nightingale/)
+- ❤️ [报告 Bug](https://github.com/ccfos/nightingale/issues/new?assignees=&labels=&projects=&template=question.yml)
+- ℹ️ 为了提供更快速的访问体验，上述文档和下载站点托管于 [FlashcatCloud](https://flashcat.cloud)
## 功能特点
@@ -50,6 +50,11 @@
## 截图演示
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+你可以在页面的右上角，切换语言和主题，目前我们支持英语、简体中文、繁体中文。
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即时查询，类似 Prometheus 内置的查询分析页面，做 ad-hoc 查询，夜莺做了一些 UI 优化，同时提供了一些内置 promql 指标，让不太了解 promql 的用户也可以快速查询。
@@ -90,8 +95,8 @@
## 社区共建
-- ❇️请阅读浏览[夜莺开源项目和社区治理架构草案](./doc/community-governance.md)，真诚欢迎每一位用户、开发者、公司以及组织，使用夜莺监控、积极反馈 Bug、提交功能需求、分享最佳实践，共建专业、活跃的夜莺开源社区。
-- 夜莺贡献者❤️
+- ❇️ 请阅读浏览[夜莺开源项目和社区治理架构草案](./doc/community-governance.md)，真诚欢迎每一位用户、开发者、公司以及组织，使用夜莺监控、积极反馈 Bug、提交功能需求、分享最佳实践，共建专业、活跃的夜莺开源社区。
+- ❤️ 夜莺贡献者
diff --git a/README_en.md b/README_en.md
index 6e446c3b7..9ca4a7987 100644
--- a/README_en.md
+++ b/README_en.md
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+ Open-source Alert Management Expert, an Integrated Observability Platform
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- An open-source cloud-native monitoring system that is all-in-one
- Out-of-the-box, it integrates data collection, visualization, and monitoring alert
- We recommend upgrading your Prometheus + AlertManager + Grafana combination to Nightingale!
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+
[English](./README_en.md) | [中文](./README.md)
+## What is Nightingale
-## Highlighted Features
+Nightingale aims to combine the advantages of Prometheus and Grafana. It manages alert rules and visualizes metrics, logs, traces in a beautiful WebUI.
-- **Out-of-the-box**
- - Supports multiple deployment methods such as **Docker, Helm Chart, and cloud services**, integrates data collection, monitoring, and alerting into one system, and comes with various monitoring dashboards, quick views, and alert rule templates. **It greatly reduces the construction cost, learning cost, and usage cost of cloud-native monitoring systems**.
-- **Professional Alerting**
- - Provides visual alert configuration and management, supports various alert rules, offers the ability to configure silence and subscription rules, supports multiple alert delivery channels, and has features such as alert self-healing and event management.
-- **Cloud-Native**
- - Quickly builds an enterprise-level cloud-native monitoring system through a turnkey approach, supports multiple collectors such as [Categraf](https://github.com/flashcatcloud/categraf), Telegraf, and Grafana-agent, supports multiple data sources such as Prometheus, VictoriaMetrics, M3DB, ElasticSearch, and Jaeger, and is compatible with importing Grafana dashboards. **It seamlessly integrates with the cloud-native ecosystem**.
-- **High Performance and High Availability**
- - Due to the multi-data-source management engine of Nightingale and its excellent architecture design, and utilizing a high-performance time-series database, it can handle data collection, storage, and alert analysis scenarios with billions of time-series data, saving a lot of costs.
- - Nightingale components can be horizontally scaled with no single point of failure. It has been deployed in thousands of enterprises and tested in harsh production practices. Many leading Internet companies have used Nightingale for cluster machines with hundreds of nodes, processing billions of time-series data.
-- **Flexible Extension and Centralized Management**
- - Nightingale can be deployed on a 1-core 1G cloud host, deployed in a cluster of hundreds of machines, or run in Kubernetes. Time-series databases, alert engines, and other components can also be decentralized to various data centers and regions, balancing edge deployment with centralized management. **It solves the problem of data fragmentation and lack of unified views**.
+Originally developed and open-sourced by Didi, Nightingale was donated to the China Computer Federation Open Source Development Committee (CCF ODC) on May 11, 2022, becoming the first open-source project accepted by the CCF ODC after its establishment.
-#### If you are using Prometheus and have one or more of the following requirement scenarios, it is recommended that you upgrade to Nightingale:
+## Quick Start
-- Multiple systems such as Prometheus, Alertmanager, Grafana, etc. are fragmented and lack a unified view and cannot be used out of the box;
-- The way to manage Prometheus and Alertmanager by modifying configuration files has a big learning curve and is difficult to collaborate;
-- Too much data to scale-up your Prometheus cluster;
-- Multiple Prometheus clusters running in production environments, which faced high management and usage costs;
+- 👉 [Documentation](https://flashcat.cloud/docs/) | [Download](https://flashcat.cloud/download/nightingale/)
+- ❤️ [Report a Bug](https://github.com/ccfos/nightingale/issues/new?assignees=&labels=&projects=&template=question.yml)
+- ℹ️ For faster access, the above documentation and download sites are hosted on [FlashcatCloud](https://flashcat.cloud).
-#### If you are using Zabbix and have the following scenarios, it is recommended that you upgrade to Nightingale:
+## Features
-- Monitoring too much data and wanting a better scalable solution;
-- A high learning curve and a desire for better efficiency of collaborative use in a multi-person, multi-team model;
-- Microservice and cloud-native architectures with variable monitoring data lifecycles and high monitoring data dimension bases, which are not easily adaptable to the Zabbix data model;
+- **Integration with Multiple Time-Series Databases:** Supports integration with various time-series databases such as Prometheus, VictoriaMetrics, Thanos, Mimir, M3DB, and TDengine, enabling unified alert management.
+- **Advanced Alerting Capabilities:** Comes with built-in support for multiple alerting rules, extensible to common notification channels. It also supports alert suppression, silencing, subscription, self-healing, and alert event management.
+- **High-Performance Visualization Engine:** Offers various chart styles with numerous built-in dashboard templates and the ability to import Grafana templates. Ready to use with a business-friendly open-source license.
+- **Support for Common Collectors:** Compatible with [Categraf](https://flashcat.cloud/product/categraf), Telegraf, Grafana-agent, Datadog-agent, and various exporters as collectors—there's no data that can't be monitored.
+- **Seamless Integration with [Flashduty](https://flashcat.cloud/product/flashcat-duty/):** Enables alert aggregation, acknowledgment, escalation, scheduling, and IM integration, ensuring no alerts are missed, reducing unnecessary interruptions, and enhancing efficient collaboration.
-#### If you are using [open-falcon](https://github.com/open-falcon/falcon-plus), we recommend you to upgrade to Nightingale：
-- For more information about open-falcon and Nightingale, please refer to read [Ten features and trends of cloud-native monitoring](https://mp.weixin.qq.com/s?__biz=MzkzNjI5OTM5Nw==&mid=2247483738&idx=1&sn=e8bdbb974a2cd003c1abcc2b5405dd18&chksm=c2a19fb0f5d616a63185cd79277a79a6b80118ef2185890d0683d2bb20451bd9303c78d083c5#rd)。
+## Screenshots
-## Getting Started
+You can switch languages and themes in the top right corner. We now support English, Simplified Chinese, and Traditional Chinese.
-[https://n9e.github.io/](https://n9e.github.io/)
+
-## Screenshots
+### Instant Query
-https://user-images.githubusercontent.com/792850/216888712-2565fcea-9df5-47bd-a49e-d60af9bd76e8.mp4
+Similar to the built-in query analysis page in Prometheus, Nightingale offers an ad-hoc query feature with UI enhancements. It also provides built-in PromQL metrics, allowing users unfamiliar with PromQL to quickly perform queries.
-## Architecture
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+### Metric View
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+Alternatively, you can use the Metric View to access data. With this feature, Instant Query becomes less necessary, as it caters more to advanced users. Regular users can easily perform queries using the Metric View.
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+### Built-in Dashboards
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+Nightingale includes commonly used dashboards that can be imported and used directly. You can also import Grafana dashboards, although compatibility is limited to basic Grafana charts. If you’re accustomed to Grafana, it’s recommended to continue using it for visualization, with Nightingale serving as an alerting engine.
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+### Built-in Alert Rules
-Nightingale monitoring can receive monitoring data reported by various collectors (such as [Categraf](https://github.com/flashcatcloud/categraf) , telegraf, grafana-agent, Prometheus, etc.) and write them to various popular time-series databases (such as Prometheus, M3DB, VictoriaMetrics, Thanos, TDEngine, etc.). It provides configuration capabilities for alert rules, silence rules, and subscription rules, as well as the ability to view monitoring data. It also provides automatic alarm self-healing mechanisms (such as automatically calling back to a webhook address or executing a script after an alarm is triggered), and the ability to store and manage historical alarm events and view them in groups.
+In addition to the built-in dashboards, Nightingale also comes with numerous alert rules that are ready to use out of the box.
-If the performance of a standalone time-series database (such as Prometheus) has bottlenecks or poor disaster recovery, we recommend using [VictoriaMetrics](https://github.com/VictoriaMetrics/VictoriaMetrics). The VictoriaMetrics architecture is relatively simple, has excellent performance, and is easy to deploy and maintain. The architecture diagram is as shown above. For more detailed documentation on VictoriaMetrics, please refer to its [official website](https://victoriametrics.com/).
+
-**We welcome you to participate in the Nightingale open-source project and community in various ways, including but not limited to**：
-- Adding and improving documentation => [n9e.github.io](https://n9e.github.io/)
-- Sharing your best practices and experience in using Nightingale monitoring => [Article sharing]((https://n9e.github.io/docs/prologue/share/))
-- Submitting product suggestions => [github issue](https://github.com/ccfos/nightingale/issues/new?assignees=&labels=kind%2Ffeature&template=enhancement.md)
-- Submitting code to make Nightingale monitoring faster, more stable, and easier to use => [github pull request](https://github.com/didi/nightingale/pulls)
-**Respecting, recognizing, and recording the work of every contributor** is the first guiding principle of the Nightingale open-source community. We advocate effective questioning, which not only respects the developer's time but also contributes to the accumulation of knowledge in the entire community
-- Before asking a question, please first refer to the [FAQ](https://www.gitlink.org.cn/ccfos/nightingale/wiki/faq)
-- We use [GitHub Discussions](https://github.com/ccfos/nightingale/discussions) as the communication forum. You can search and ask questions here.
-- We also recommend that you join ours [Slack channel](https://n9e-talk.slack.com/) to exchange experiences with other Nightingale users.
+## Architecture
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+In most community scenarios, Nightingale is primarily used as an alert engine, integrating with multiple time-series databases to unify alert rule management. Grafana remains the preferred tool for visualization. As an alert engine, the product architecture of Nightingale is as follows:
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+For certain edge data centers with poor network connectivity to the central Nightingale server, we offer a distributed deployment mode for the alert engine. In this mode, even if the network is disconnected, the alerting functionality remains unaffected.
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-## Who is using Nightingale
-You can register your usage and share your experience by posting on **[Who is Using Nightingale](https://github.com/ccfos/nightingale/issues/897)**.
+
+## Communication Channels
+
+- **Report Bugs:** It is highly recommended to submit issues via the [Nightingale GitHub Issue tracker](https://github.com/ccfos/nightingale/issues/new?assignees=&labels=kind%2Fbug&projects=&template=bug_report.yml).
+- **Documentation:** For more information, we recommend thoroughly browsing the [Nightingale Documentation Site](https://flashcat.cloud/docs/content/flashcat-monitor/nightingale-v7/introduction/).
## Stargazers over time
-[](https://starchart.cc/ccfos/nightingale)
-## Contributors
+[](https://star-history.com/#ccfos/nightingale&Date)
+
+## Community Co-Building
+
+- ❇️ Please read the [Nightingale Open Source Project and Community Governance Draft](./doc/community-governance.md). We sincerely welcome every user, developer, company, and organization to use Nightingale, actively report bugs, submit feature requests, share best practices, and help build a professional and active open-source community.
+- ❤️ Nightingale Contributors
## License
-[Apache License V2.0](https://github.com/didi/nightingale/blob/main/LICENSE)
\ No newline at end of file
+- [Apache License V2.0](https://github.com/didi/nightingale/blob/main/LICENSE)