Bun is a fast, all-in-one toolkit for running, building, testing, and debugging JavaScript and TypeScript, from a single script to a full-stack application.

Now Bun v1.1 has released at April 1st, let’s explore what’s new in Bun v1.1.

Download the installer package from the 

Once you have downloaded the installer, run it and follow the instructions to complete the installation process.

Start your first Bun project using Bun CLI.

Exciting news for Windows 10 users and beyond—Bun is now available for your platform! This marks a significant leap forward, opening up opportunities for a broader developer community to utilize Bun.

Bun's compatibility with Windows is robust, successfully passing 98% of the tests we use for macOS and Linux. This comprehensive coverage ensures that the full suite of Bun's capabilities—runtime, test runner, package manager, and bundler—are fully operational on Windows.

Ready to dive in with Bun on your Windows machine? Simply input the following command into your terminal to begin: > powershell -c "irm bun.sh/install.ps1 | iex"

Bun seamlessly integrates with JavaScript, TypeScript, and JSX thanks to its custom-built transpiler, which is crafted from highly efficient native code for optimal performance.

From the release of Bun 1.0, a specialized caching system has been in place for files exceeding 50KB, eliminating unnecessary re-transpilation and thereby enhancing speed and efficiency.

As a result of these innovations, command-line utilities such as tsc now execute up to twice as swiftly compared to their performance in Bun 1.0.

The Bun Shell has been transformed into a cross-platform shell, accessible not only on Unix-like systems but also on Windows, akin to bash.

Why should scripting with JavaScript, the most ubiquitous scripting language, be fraught with complexity? Bun simplifies the process.

To make bun run faster on Windows, Bun team has engineered a new file-format: .bunx.

The .bunx file serves as a universal symlink, functioning across different file systems to launch scripts or executables via Bun or Node.js. This innovation was driven by multiple factors:

The unreliability of traditional symlinks on Windows systems.

The inability of Windows to recognize shebangs (e.g., #!/usr/bin/env bun) at the start of files.

Our goal to streamline the process by eliminating the need for three separate types of executable files: .cmd, .sh, and .ps1.

Our desire to bypass the often confusing prompts asking to "Terminate batch job? (Y/n)".

Bun 1.1 is a significant update to the fast and versatile JavaScript and TypeScript toolkit, introducing Windows support, new APIs like Bun.Glob and Bun.Semver, enhanced features such as IPC support, and improvements in performance and stability.

What's New in Bun v1.1

RSS3 has launched its Alpha Mainnet earlier this month, and it has surged beyond $30M in TVL. Anyone with more than 10,000 tokens can run a RSS3 Node on the Alpha Mainnet, just deploy the node instance somewhere on the cloud and set it up with some easy steps.

Now Zeabur has simplified the process for running a RSS3 Node much more easily, you can run the node with just one click on Zeabur! Let’s explore the best way you can start an Alpha Node in this article.

 is a decentralized network indexing and structuring open information, making it accessible and valuable for the next Twitter, Google, and OpenAI.

Inspired by the original RSS protocol, RSS3 stands as a decentralized network committed to the 

 paving the way for open AI and the Open Web.

Recently RSS3 has announced its Alpha Mainnet and allow holders to register Alpha Nodes and contribute to information freedom. Now there are more than $30M in TVL.

 and deposit them to RSS3 VSL Mainnet to start an Alpha Node. You can check 

You need to create an account on Zeabur through GitHub, and upgrade your account to 

Once you’ve prepared your RSS3 tokens and bridge them to VSL Mainnet, you can register a node on 

Before you deploy the RSS3 Node template, you need to prepare two important variables for verifying the node:

`NODE_DISCOVERY_MAINTAINER_SIGNATURE`: A signature for a specific string used to verify the ownership of your wallet address, which can be obtained using the SIGNATURE button on RSS3 Explorer.

`NODE_DISCOVERY_MAINTAINER_EVM_ADDRESS` : The wallet address you use to register your node. You can get the evm address in your wallet that binds the explorer.

, click the deploy button, then you will see a modal like the following picture for you to fill in those two variables, choose a public domain and deployed region area.

After you’ve finished these setups, simply click on the Confirm button, then your deployment will be finished in one minute, and that’s all, your RSS3 Node just start working!

>💡 You will need to upgrade to Developer Plan or Team Plan to keep your RSS Node running stably.(Start at US$ 5 per month)

As you can see, you can get your registered Alpha Node running on Zeabur within 3 minutes, no virtual machine and docker files needed, just one click to bring your RSS3 Node alive. And you just need US$ 5 per month to keep the node running, that’s much lower than the benefit of owning an Alpha Node I guess. 😄 Start a node in 3 minutes and explore the RSS3 Alpha Mainnet!

Run Your RSS3 Node with One Click

This tutorial will guide you through developing a simple Telegram bot from scratch, utilizing the GrammY framework with JavaScript, and deploying it on Zeabur.

Developing Telegram bots with JavaScript offers several options, such as node-telegram-bot-api or GrammY. The first one is Telegram's Node.js SDK, while GrammY is an emerging, mature framework that comes with many pre-packaged functionalities, simplifying our development process.

 is a deployment service platform that makes it convenient for developers to deploy their services with one click, without worrying about server infrastructure.

To keep a Telegram bot running continuously, we have two options:

Running it locally, which requires the computer to stay connected and on

Deploying it to the cloud, completing development and deploying with one click to Zeabur for continuous and stable bot service

The process to create a bot on Telegram is straightforward. Open Telegram, search for 

. In the chat, follow the guide and send the `/newbot` command to create a bot, then copy its token.

Node.js environment installed on your computer

A package manager like npm/pnpm installed

First, create a new folder to store your bot code. Then, open a terminal in that directory and enter the command `npm init` to generate a default package.json. Next, install the grammy dependency with `npm install grammy`.

At this point, you can run your bot with the following command:

After running the bot, you can send messages to the bot you just created on Telegram, and it will reply with "Received: + your message content."

After development is complete, you can deploy your bot to the cloud. Zeabur is recommended for easy one-click deployment.

First, visit Zeabur's official website and register a new account using GitHub. After entering the dashboard, click to create a new project and select your preferred region; here, we choose a data center in Hong Kong.

After creating the project, click to create a new service on the project page, choose to deploy from a GitHub repository, select the bot repository you just created, and click import. Zeabur will automatically start deploying your bot. Wait about a minute for the deployment to finish, and then you can go back and enjoy chatting with your bot.

If you just want to have a bot that allows you to use ChatGPT or Gemini on Telegram, you can directly deploy a few bots from Zeabur's template market, such as 

. After clicking deploy, Zeabur will automatically create a corresponding repository for you. You only need to enter your bot token and API key during deployment to start using it.

Create and Deploy a Telegram Bot with JavaScript

This article will guide you to complete the building and deploying of a Flask back-end application from scratch using 

, allowing developers to provide one-click deployment services for applications quickly without leaving the terminal. With just a few commands, the application can run in the cloud and be configured with a domain for access.

Using Zeabur CLI to Deploy a Simple Flask + MySQL Application

 for installation according to the operating system.

For example, on the MacOS platform, execute the following command in the command line to complete the installation:

 to create a virtual Python environment for development and debugging, and then install related dependencies. Here we use 

Create the app.py file at the directory root. This is the main entry file for the flask application: 

In the above code, a simple TodoList application is completed. REST API completes the addition/deletion/query of tasks. By reading the environment variable DATABASE_URL, the important information for connecting to MySQL is obtained. The flask web server starts on 0.0.0.0, and the port is obtained through the environment variable PORT.

In general, backend application development requires testing of the database server. Traditional methods such as local running/ Docker deployment are relatively cumbersome. Zeabur provides a new way to quickly deploy database services:

, and enter in the terminal to create a project: `zeabur project create zeabur-cli-flask-demo`

Create a MySQL Prebuilt Serivice: `zeabur service deploy`
In the selection box, choose the Prebuilt type, and select the MySQL type in the next selection box:

After creation, we can view the Service list in the Project. Enter zeabur service list in the terminal to see the service just created.

Get connection information, enter in the terminal and select the MySQL Service just created: `zeabur service instruction`
We note down this information, and use it in the following steps to connect to the database via the public network:

Using the above information, start the flask application for local testing. Enter the following in the terminal:

After successful operation, you can use debugging tools like 

Step Four: Deploy Backend Flask Application

 provides a convenient command to deploy local code to Zeabur with one click. Just knock zeabur in the application directory, and CLI will automatically upload your code and deploy it.

For the application to run normally, we still need to create environment variables to connect to the database. Since the flask service and MySQL service are under the same Project, we can use 

 to connect to the database more efficiently:
Check the network information of the MySQL service, enter zeabur service network in the terminal and select the relevant service:

Based on the above domain name, we create the environment variable of the flask application in turn. Enter zeabur variable create in the terminal:

The above environment variables MYSQL_USERNAME, MYSQL_PASSWORD, MYSQL_PORT, MYSQL_DATABASE are all system-generated injections, eliminating the trouble of manual filling. The PORT environment variable allows Zeabur to automatically recognize the web port and automatically bind public network access.

For the service to apply the environment variables, we should restart the service. Enter zeabur service restart in the terminal:

To access the web service on the public network, we still need to bind a domain name. Here we use *.zeabur.app to automatically generate a domain name as an example. Enter zeabur domain create in the terminal:

At this point, we have completed all the steps. Now we can use debugging tools like 

 to deploy backend applications is a quick and comfortable process, which can greatly improve your efficiency in agile development, making testing and production deployment very convenient.

How to Use Zeabur CLI to Deploy a Simple Flask Application

Notion is an excellent content management system useful for creating personal and business blogs. It allows you to create shareable web pages filled with headings, text, images, and videos, which you can organize in various ways.

A blog is a powerful tool for sharing your thoughts, experiences, and expertise with your audience. It can help establish your online presence, foster community, and become a platform for expressing your unique ideas.

Different from Notion, your contents are visible to a wider audience when transformed into a blog. This is because blogs are indexed by search engines, making your content more discoverable and accessible to those who are interested in your topic.

How can I sync my Notion content to the blog?

Yes, you absolutely can. With Notion official APIs, you can easily get your Notion contents through a page ID. And there are many great template for building a blog website using Notion API, such as Notion Next and Nobelium.

All you need to do is to enable share and copy paste your Notion page ID, and the service will automatically sync your Notion contents into your online blog site.

There are many ways to deploy your blog site. For example, you can rent or build a server by yourself to use as a hosting machine. You can also choose some platform for deploying your site at ease. Zeabur is one of the platform for you to deploy your sites with one click.

Here is a simple tutorial for deploying Notion Next to Zeabur in 3 minutes.

Step 1: Get your account for GitHub and Zeabur

First of all, you need a GitHub account and a Zeabur account. You can use your GitHub account to sign up Zeabur.

 to get your GitHub account. After you’ve got one, head over to 

 and click on the Get Started button. A modal will appear showcasing a 'login with GitHub' button. Click on it, grant Zeabur permission to connect with your GitHub, and voila! You'll have your Zeabur account set up.

Step 2: Find the Notion Next template on Zeabur templates

After you’ve agreed Zeabur’s service terms and get your account ready, you can go to the templates gallery to find 

Step 3: Follow the instructions in the template page

As you can see, you need to finish some setup for deploying this template.

First one is your Notion page id, which is mentioned above, you need to fill in to let this service connected to your Notion database.

And then you need to specify a repo for this service, Zeabur will automatically create a GitHub repo for you binding with the service.

Last, select a region to deploy your blog and press the deploy button. The deployment will start automatically.

Step 4: Bind a domain to show everyone your blog

After the deployment is finished, you can bind a domain in the Networking tab in your service page.

You can either use a free sub domain ends with .zeabur.app or use your own domain by updating your DNS record.

You can also check a more detailed guide for binding domain for your blog website 

How to Use Notion as Blog Database - Deploy a Notion Based Blog in 3 Minutes

Like is a very common feature, but the implementation of the like function for QBS 1 and QBS 100000 is vastly different in difficulty. However, even the simplest like system might take about half an hour to develop from scratch. But there's an open-source and free Backend as a Service that can help you implement a like feature in your application in just 10 minutes.

 encapsulates different like implementations for different performance requirements, making it easy for developers to invoke through different methods like SDK, gRPC, and RESTful.

Let us help you implement a like feature in your application in less than 10 minutes through a journal.

Likit needs to expose two ports to the outside. In Zeabur, this can be achieved by binding a domain.The first port handles HTTP requests. Through it, you can access the dashboard to manage Likit and also use RESTful to call APIs.The second port handles gRPC requests. In the SDKs for Golang and Java, please enter the domain name bound to this port.

We click on the previously bound HTTP domain to enter Likit's dashboard.

You should copy the password for the Likit Dashboard from the left side of the Zeabur control panel. Afterward, click on the bound domain to access Likit, paste the password, and then enter the Dashboard.

You should copy the password of the Likit Dashboard from the left side of the Zeabur control panel, then click on the previously bound domain to enter Likit, paste the password, and then enter the Dashboard.

Here, we briefly explain three concepts that will often be encountered later: BusinessId, MessageId, and UserId.

, refers to a specific business, such as comment likes or post votes. It is determined by the user when manually creating in Likit Dashboard. However, we recommend using all uppercase and connecting words with underscores, like COMMENT_LIKE.

, is the ID of the object being liked; it should be unique in each business.

, is the unique ID of the user who likes.

, Each Business must specify a Vote Engine when created. Different Vote Engines have different algorithms and implementations, and require different components to meet the needs of different users. For example, later we will specify a Simple Vote Vote Engine, which is suitable for small applications and only needs a Redis.

Alright, let's create a new Business here. Fill in the Title and Id, choose a Simple Vote, and remember to select Redis as well.

Up to now, we have already created the Business, so everything related to Likit has been configured. Now, we can start calling the API in our backend code.

If your backend is written in Java with Spring, then all you need to use is 

If your backend is written in Golang, then 

Install likit-go: `go get github.com/likit/likit-go`

If your backend is implemented neither in Golang nor Java, then I recommend using gRPC to call the Likit API. You can see the complete API definition of Likit and some gRPC SDKs for other languages 

 is a very simple and easy-to-use Backend as a Service. If you want to implement a like, dislike, or voting feature in your new project, it's worth a try.

How to Implement a Like Feature in Just 10 Minutes

Shifting from Google Analytics to open source, self-hosted alternatives can significantly enhance data privacy and customization. This blog post introduces the top five open source analytics tools, offering a comprehensive comparison of their features, benefits, and unique capabilities.

Matomo offers a robust, feature-rich alternative to Google Analytics, with the added benefit of full data ownership and privacy.

Extensive customization for reports and dashboards.

A range of plugins for extended functionality.

 A healthcare website uses Matomo to securely track user interactions while maintaining strict compliance with health data privacy regulations.

Plausible stands out for its simplicity and commitment to user privacy, making it a great choice for small to medium-sized websites.

Open source with an option for self-hosting.

 An educational blog opts for Plausible to track user engagement metrics without impacting site performance or user privacy.

Umami is a straightforward and easy-to-use analytics tool, perfect for those seeking simplicity and ease of use.

Simple, clean interface for easy data interpretation.

Tracks multiple websites under one account.

Self-hosted with a focus on user privacy.

 A portfolio website for a freelance designer utilizes Umami to monitor visitor interactions and optimize content accordingly.

Open Web Analytics offers a comprehensive set of features, rivaling commercial analytics tools, with the flexibility of open source.

Detailed tracking of visitors, including mouse tracking.

Rich set of data reports and visualizations.

 An e-commerce site uses OWA to analyze customer paths and improve the shopping experience, boosting conversion rates.

Countly is notable for its ability to analyze both web and mobile app data, providing a unified view of user interactions across platforms.

Extensive plugin library for custom functionality.

Mobile analytics for iOS and Android apps.

Strong focus on privacy and data security.

 A mobile app development company uses Countly to track user engagement across their portfolio of apps and websites, streamlining their marketing and development efforts.

Choosing the right open source, self-hosted alternative to Google Analytics depends on your specific needs, whether it's for enhanced privacy, detailed data insights, or ease of use. Each of these tools offers unique strengths, empowering website owners with the flexibility and control needed in today's digital landscape.

Top 5 Self-Hosted, Open Source Alternatives to Google Analytics

In today's fast-paced digital world, ensuring the uptime and reliability of web services is crucial. 

Uptime Kuma, a self-hosted monitoring tool

, has become a popular choice for many. When deployed on platforms like Zeabur, it offers enhanced convenience and efficiency. This guide provides a detailed walkthrough on how to deploy Uptime Kuma on Zeabur with just one click.

Uptime Kuma is an open-source monitoring solution that helps you keep track of your website's uptime and response time. It's designed to be a more privacy-conscious alternative to third-party services.

: Tracks your website’s uptime continuously.

: Notifies you through various channels when your site is down.

Zeabur is a cloud platform that simplifies the deployment and management of applications. It's known for its user-friendly interface and one-click deployment features.

: Intuitive UI for straightforward application management.

: Easily scales resources according to your needs.

: Implements robust security measures to protect your applications.

Before starting, ensure you have a Zeabur account and understand the basics of navigating its dashboard.

: Create a project, and then click on the **Deploy New Service** button to find Uptime Kuma in the prebuilt marketplace. Zeabur will start the deployment for you after you select Uptime Kuma.

 You can bind a domain for your Uptime Kuma service in the domain tab.

: Check if Uptime Kuma is running correctly.

: Configure your sites or services to be monitored.

Deploying Uptime Kuma on Zeabur with one click is a seamless process that enhances your website monitoring capabilities. By following this guide, you can quickly set up a robust monitoring system.

For more detailed tutorial, you can check 

Deploy Uptime Kuma in 3 Minutes

On October 27, 2023, Zeabur experienced a service outage. The outage affected the tpe1 cluster located in the Taipei region, resulting in a service interruption of approximately 1 hour. The cause of the outage was a mistake made by an intern, leading to the deletion of our Kubernetes cluster located in the Google Cloud Platform's Taipei data center.

Upon receiving alerts from the monitoring service, Zeabur's operations team acted swiftly and restored services for both enterprise and developer users within two hours. The scope of the outage was relatively broad, with the main users affected including:

Containerized services of the free, developer, and enterprise plans deployed in the tpe1 (Taipei) region

Serverless services of the free, developer, and enterprise plans deployed in the tpe1 (Taipei) region

If your deployed services happen to be in the affected region, then you might have been unable to access the services you deployed on Zeabur during this time on October 27, 2023.

We deeply apologize for the mistakes made during this incident and the resulting impact.

During the process of deleting an obsolete test cluster, an intern, due to lack of operational experience and internal oversight in permission management, failed to report this risky operation to supervisors. Mistakenly, the production Google Kubernetes Engine cluster was deleted, causing it to become unavailable and all services in the tpe1 (Taipei) region to be disrupted.

UTC 2:40 - tpe1 cluster is deleted, all services go offline. 

UTC 2:41 - The service health monitoring system detects the interruption and sends an emergency alert to the project monitoring team. 

UTC 2:45 - The cause of the outage is identified. Operations staff immediately start investigating and discover the cluster is inaccessible. Further inspection reveals the cluster has been deleted and the process is irreversible. The team initiates emergency response measures. 

UTC 2:50 - After attempting to communicate with Google Cloud Platform, the project tech lead and operations staff try to directly restore the cluster but fail. They attempt to restore the cluster using Google Kubernetes Engine backup, but upon inspection, it's found that the backup service was not enabled for this cluster. 

UTC 3:00 - Team investigations reveal that the deleted cluster does not affect the Persistent Disk in Google Cloud Platform's Compute Engine, confirming that user service data has not been lost. 

UTC 3:10 - The process of migrating disrupted services to the tpe0 (Taipei) region begins. The team starts re-linking user data to a backup cluster in the Taipei region through automation scripts. 

UTC 3:30 - The primary functions of the cluster are restored, user services go back online, services for enterprise plan customers are restored, and the development team starts addressing user-reported tickets. 

UTC 3:48 - The team issues an outage announcement, suggesting users temporarily migrate stateless services to the hkg1 (Hong Kong) or sfo1 (North America) regions as a temporary solution. 

UTC 3:56 - The team releases a service recovery statement, offering users a solution and a process for ticket submission. 

UTC 6:10 - The team announces full service restoration. All tickets from developer plan customers submitted during the outage are resolved. They set up a ticket submission process for user service recovery requests and continue restoring services for users.

A lack of security awareness among employees. Before executing dangerous operations, they did not promptly report to supervisory developers for review and failed to double-check the targeted resources.

In-house permission management was not granular enough. This led to employees having administrative access to the production environment clusters, without specific access controls.

The disaster recovery plan was inadequate. Kubernetes resources were not backed up automatically on a regular basis, making it impossible to rapidly restore from backups after an incident.

There was a lack of established emergency response procedures for related urgent situations, leading to longer response times.

The monitoring system rapidly detected multiple 502 errors across various services, and a large number of alarms were triggered in a short time. Investigation showed that all issues were originating from the `TPE1` cluster. Subsequent internal checks within the development group revealed that there was an operation to delete the development cluster within a minute. However, due to the failure to report to the supervisory developers for review in time, and continuously operating under a high-privilege account, the production cluster was accidentally deleted.

In the shortest possible time, the development team initiated emergency measures. Engineers from the team contacted Google Cloud Platform customer service and confirmed that once a deletion operation is executed, it cannot be reversed. Moreover, since the Google Kubernetes Engine backup function was not enabled, it was impossible to restore the cluster through this method.

Upon team investigation, it was determined that the persistent storage hard drives of the cluster were not destroyed due to the cluster deletion. Therefore, the decision was made to manually create new stateful services in the backup cluster by binding to the original hard drives. Stateless services were rebuilt from scratch.

Infrastructure operations engineers increased computing nodes in the Taipei backup cluster, `tpe0`, creating new deployments to accommodate user services from the faulty cluster. Once the cluster was ready, the team started restoring user services using automated scripts and the original persistent hard drives. 

Thanks to the robustness of the existing Zeabur system and some straightforward migration scripts, the development team quickly transferred services to the backup cluster. After validating the feasibility of experimental manual migration, services for enterprise solution users were given priority for restoration.

Once the migration of affected users' clusters was completed, the services for enterprise solution users were restored. The development team then began addressing user tickets. Services for developer plan users and free plan users began to be restored gradually through a refined automated process.

Updated Emergency Plan: Users can temporarily migrate stateless services to the Hong Kong `HKG1` cluster or the US `SFO1` cluster as a solution. Stateful services, on the other hand, will be transferred to temporary clusters to effectively safeguard the integrity of user data.

Upon verification, it was confirmed that the business system can start correctly on the backup cluster and provide services to the outside world, resolving the service interruption incident.

After the emergency event concluded, the team immediately minimized control by deactivating all IAM permissions of the developers. Simultaneously, a security inspection of all infrastructure was undertaken, identifying several potential security risks and formulating an improvement plan.

Once all clusters were restored to normal, operational engineers activated the backup service for every cluster, performing a full backup. Regular backup services were initiated to incrementally back up user data at set intervals.

The team summarized and analyzed the event, reflecting and improving on the mistakes made during the incident. There was also a reassessment and redesign of the infrastructure's high availability and security.

Zeabur Blogs

What's New in Bun v1.1

Run Your RSS3 Node with One Click

Create and Deploy a Telegram Bot with JavaScript

How to Use Zeabur CLI to Deploy a Simple Flask Application

How to Use Notion as Blog Database - Deploy a Notion Based Blog in 3 Minutes

How to Implement a Like Feature in Just 10 Minutes

Top 5 Self-Hosted, Open Source Alternatives to Google Analytics

Deploy Uptime Kuma in 3 Minutes

Zeabur Taipei region outage on October 27, 2023

2023 年 10月 27 日 Zeabur 台北區域服務故障報告

How to Deploy Next.JS 14 Application in 3 Minutes

Deploy NestJS Application on Zeabur: A Step by Step Guide

Zeabur CLI

Visual Analysis Tool Face-off: Rath vs Trifacta vs Power BI

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