# Train Ticket:A Benchmark Microservice System
#
源代码github链接:https://github.com/FudanSELab/train-ticket
The project is a train ticket booking system based on microservice architecture which contains 41 microservices. The programming languages and frameworks it used are as below.
- Java - Spring Boot, Spring Cloud
- Node.js - Express
- Python - Django
- Go - Webgo
- DB - Mongo、MySQL
You can get more details at [Wiki Pages](https://github.com/FudanSELab/train-ticket/wiki).
## Service Architecture Graph
![architecture](./image/2.png)
## Quick Start
We provide k8s deployment to quickly deploy our application: [Using Kubernetes](#Using-Kubernetes).
### Using Kubernetes
Here is the steps to deploy the Train Ticket onto any existing Kubernetes cluster.
#### Presequisite
* An existing Kubernetes cluster
* Helm supported, you can see https://helm.sh/docs/helm/helm_install/ for helm install
* PVC supported, you can see https://openebs.io/docs/2.12.x/user-guides/installation for localPV support.
#### 1. Clone the Repository
```bash
git clone --depth=1 https://github.com/FudanSELab/train-ticket.git
cd train-ticket/
```
#### 2. Deploy the application
### For Quick Start
```bash
make deploy
```
Note: if you want specify namespace, set Namespace paramter:
```bash
make deploy Namespace=yournamespace
```
### Deploy Mysql Clusters For Each Services
```bash
make deploy DeployArgs="--independent-db"
```
### With Moinitorig
```bash
make deploy DeployArgs="--with-monitoring"
```
### With Distributed Tracing
```bash
make deploy DeployArgs="--with-tracing"
```
### Deploy All
```bash
make deploy DeployArgs="--all"
```
### Customise Deployment
You can freely combine parameters for custom deployment, for example, deploy with monitoring and tracing:
```bash
make deploy DeployArgs="--with-tracing --with-monitoring"
```
### Reset Deployment
```
make reset-deploy
# if you specify namespace when deploy, set namespace as well when reset
# make reset-deploy Namespace=yournamespace
```
#### 3. Run `kubectl get pods` to see pods are in a ready state
#### 4. Visit the Train Ticket web page at [http://[Node-IP]:32677](http://[Node-IP]:32677).
## Build From Source
In the above, We use pre-built images to quickly deploy the application.
If you want to build the application from source, you can refer to [the Installation Guide](https://github.com/FudanSELab/train-ticket/wiki/Installation-Guide).
## Test scripts
Use scripts to test train-ticket: [https://github.com/FudanSELab/train-ticket-auto-query](https://github.com/FudanSELab/train-ticket-auto-query)
## Screenshot
![screenshot](./image/main_interface.png)
In order to know how to use the application, you can refer to [the User Guide](https://github.com/FudanSELab/train-ticket/wiki/User-Guide).
## Communication
* [FAQ](https://github.com/FudanSELab/train-ticket/wiki/FAQ)
* [Submit an issue](https://github.com/FudanSELab/train-ticket/issues)
* [Open a pull request](https://github.com/FudanSELab/train-ticket/pulls)
## Information
* [Release Note](https://github.com/FudanSELab/train-ticket/wiki/Release-Note)
## Serverless Train Ticket
We have released a serverless version of Train Ticket.
* [serverless-trainticket](https://github.com/FudanSELab/serverless-trainticket)
## Paper Reference
Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu.
**Enjoy your observability: an industrial survey of microservice tracing and analysis**
[Empirical Software Engineering](https://www.springer.com/journal/10664/), Volume 27, 25, 2022.
Download:[[PDF](https://link.springer.com/content/pdf/10.1007/s10664-021-10063-9.pdf)]
Chenxi Zhang, Xin Peng, Chaofeng Sha, Ke Zhang, Zhenqing Fu, Xiya Wu, Qingwei Lin, Dongmei Zhang
**DeepTraLog: Trace-Log Combined Microservice Anomaly Detection through Graph-based Deep Learning**
In Proceedings of the 44th International Conference on Software Engineering ([ICSE 2022](https://dblp.uni-trier.de/db/conf/icse/icse2022.html)) , Pittsburgh, USA, May, 2022.
Download:[[PDF](https://dl.acm.org/doi/pdf/10.1145/3510003.3510180)]
Dewei Liu, Chuan He, Xin Peng, Fan Lin, Chenxi Zhang, Shengfang Gong, Ziang Li, Jiayu Ou, Zheshun Wu
**MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems**
In Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice ([ICSE-SEIP 2021](https://dblp.uni-trier.de/db/conf/icse/seip2021.html#LiuH0LZGLOW21)) , Madrid, Spain, May, 2021.
Download:[[PDF](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9402058)]
Qilin Xiang, Xin Peng, Chuan He, Hanzhang Wang, Tao Xie, Dewei Liu, Gang Zhang, Yuanfang Cai
**No Free Lunch: Microservice Practices Reconsidered in Industry**
arXiv preprint arXiv:2106.07321, 2021.
Download:[[PDF](https://arxiv.org/pdf/2106.07321.pdf)]
Xiaofeng Guo, Xin Peng, Hanzhang Wang, Wanxue Li, Huai Jiang, Dan Ding, Tao Xie, Liangfei Su
**Graph-based trace analysis for microservice architecture understanding and problem diagnosis**
In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering ([ESEC/FSE 2020](https://dblp.uni-trier.de/db/conf/sigsoft/fse2020.html)) , Virtual Event, USA, November, 2020.
Download:[[PDF](https://dl.acm.org/doi/pdf/10.1145/3368089.3417066)]
Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Dewei Liu, Qilin Xiang, and Chuan He.
**Latent Error Prediction and Fault Localization for Microservice Applications by Learning from System Trace Logs.**
In Proceedings of the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering ([ESEC/FSE 2019](https://dblp.uni-trier.de/db/conf/sigsoft/fse2019.html)) , Tallinn, Estonia, August 2019.
Download: [[PDF](https://cspengxin.github.io/publications/fse19-zhou-microservice.pdf)] [[BibTeX](https://dblp.uni-trier.de/rec/bibtex/conf/sigsoft/Zhou0X0JLXH19)]
Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, and Dan Ding.
**Fault Analysis and Debugging of Microservice Systems: Industrial Survey, Benchmark System, and Empirical Study.**
[IEEE Transactions on Software Engineering](https://www.computer.org/web/tse) , To appear.
Download: [[PDF](https://cspengxin.github.io/publications/tse19-msdebugging.pdf)]
Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Wenhai Li, Chao Ji, and Dan Ding.
**Delta Debugging Microservice Systems.**
In Proceedings of 33rd IEEE/ACM International Conference on Automated Software Engineering ([ASE 2018](http://ase2018.com/)) , Short Paper, Montpellier, France, September 2018.
Download: [[PDF](https://cspengxin.github.io/publications/ase18-debugmicroservice.pdf)] [[BibTeX](https://dblp.uni-trier.de/rec/bibtex/conf/kbse/ZhouPX0LJD18)]
An extended version to appear in IEEE Transactions on Services Computing.
Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chenjie Xu, Chao Ji, and Wenyun Zhao.
**Poster: Benchmarking Microservice Systems for Software Engineering Research.**
In Proceedings of the 40th International Conference on Software Engineering ([ICSE 2018](https://www.icse2018.org/)) , Posters, Gothenburg, Sweden, May 2018.
Download: [[PDF](https://cspengxin.github.io/publications/icse18poster-microservices.pdf)] [[BibTeX](https://dblp.uni-trier.de/rec/bibtex/conf/icse/ZhouPX0XJZ18)]