As a development framework that is closely related to users, Dubbo may have a huge impact on users if any problems occur during the iteration process. Therefore, Dubbo needs a complete set of automated regression testing tools.
At present, Dubbo already has a set of testing tools based on docker-compose, but this set of tools cannot test the compatibility in the kubernetes environment. At the same time, we also need a more reliable test case construction system to ensure that the test cases are sufficiently complete.

Background

Dubbo currently supports the rest protocol based on http1, and the triple protocol based on http2, but currently the two protocols based on the http protocol are implemented independently, and at the same time, they cannot replace the underlying implementation, and their respective implementation costs are relatively high.

Target

In order to reduce maintenance costs, we hope to be able to abstract http. The underlying implementation of the target implementation of http has nothing to do with the protocol, and we hope that different protocols can reuse related implementations.

As a development framework that is closely related to users, Dubbo provides many functional features (such as configuring timeouts, retries, etc.). We hope that a tool can be given to users to scan which features are used, which features are deprecated, which ones will be deprecated in the future, and so on. Based on this tool, we can provide users with a better migration solution.
Suggestion: You can consider based on static code scanning or javaagent implementation.

Dubbo supports the communication mode based on the gRPC protocol through Triple. For this reason, Dubbo has developed a compiling plug-in for proto files based on jprotoc. Due to the activeness of jprotoc, currently Dubbo compiler cannot run well on the latest protobuf version. Therefore, we need to consider implementing a new compiler with reference to gRPC may have a huge impact on users if any problems occur during the iteration process. Therefore, Dubbo needs a complete set of automated regression testing tools.
At present, Dubbo already has a set of testing tools based on docker-compose, but this set of tools cannot test the compatibility in the kubernetes environment. At the same time, we also need a more reliable test case construction system to ensure that the test cases are sufficiently complete.

Dubbo is

As a development framework that is closely related to users, Dubbo provides many functional features (such as configuring timeouts, retries, etc.). We hope that a tool can be given to users to scan which features are used, which features are deprecated, which ones will be deprecated in the future, and so on. Based on this tool, we can provide users with a better migration solution.
Suggestion: You can consider based on static code scanning or javaagent implementation.and many usages by users may cause exceptions handled by Dubbo. Usually, in this case, users can only judge through logs. We hope to provide an i18n localized log output tool to provide users with a more friendly log troubleshooting experience.

As more and more projects start to develop based on Gradle and profit from Gradle, Dubbo also hopes to migrate to the Gradle project. This task requires you to transform the dubbo project[1] into a gradle project.

 [1] https://github.com/apache/dubbo

Dubbo supports the communication mode based on the gRPC protocol through Triple. For this reason, Dubbo has developed a compiling plug-in for proto files based on jprotoc. Due to the activeness of jprotoc, currently Dubbo compiler cannot run well on the latest protobuf version. Therefore, we need to consider implementing a new compiler with reference to gRPC.

Dubbo Admin is a development framework that is closely related to users, and many usages by users may cause exceptions handled by Dubbo. Usually, in this case, users can only judge through logs. We hope to provide an i18n localized log output tool to provide users with a more friendly log troubleshooting experienceconsole of Dubbo. Today, Dubbo's observability is becoming more and more powerful. We need to directly observe some indicators of Dubbo on Dubbo Admin, and even put forward suggestions for users to improve problems.

Background

At present, the abstraction of connection by client in different protocols in Dubbo is not perfect. For example, there is a big discrepancy between the client abstraction of connection in dubbo and triple protocols. As a result, the enhancement of connection-related functions in the client is more complicated, and the implementation cannot be reused. At the same time, the client also needs to implement a lot of repetitive code when extending the protocol.

Target

Reduce the complexity of the client part when extending the protocol, and increase the reuse of connection-related modules.

As more and more projects start to develop based on Gradle and profit from Gradle, Dubbo also hopes to migrate to the Gradle project. This task requires you to transform the dubbo project[1] into a gradle project.

 [1] https://github.com/apache/dubbo

Background

Dubbo currently supports protobuf as a serialization method. Protobuf relies on proto (Idl) for code generation, but currently lacks tools for managing Idl files. For example, for java users, proto files are used for each compilation. It is more troublesome, and everyone is used to using jar packages for dependencies.

Target

Implement an Idl management and control platform, support idl files to automatically generate dependency packages in various languages, and push them to relevant dependency warehouses

Dubbo Admin is a console of Dubbo. Today, Dubbo's observability is becoming more and more powerful. We need to directly observe some indicators of Dubbo on Dubbo Admin, and even put forward suggestions for users to improve problems.

For a large number of monolithic applications, problems such as performance will be encountered during large-scale deployment. For interface-oriented programming languages, Dubbo provides the capability of RPC remote calls, and we can help applications decouple through interfaces. Therefore, we can provide a deployer to help users realize the decoupling and splitting of microservices during deployment, and quickly provide performance optimization capabilities.

Background

At present, the abstraction of connection by client in different protocols in Dubbo is not perfect. For example, there is a big discrepancy between the client abstraction of connection in dubbo and triple protocols. As a result, the enhancement of connection-related functions in the client is more complicated, and the implementation cannot be reused. At the same time, the client also needs to implement a lot of repetitive code when extending the protocol.

Target

Reduce the complexity of the client part when extending the protocol, and increase the reuse of connection-related modules.

Since Dubbo runs on a distributed architecture, it naturally has the problem of difficult API interface definition management. It is often difficult for us to know which interface is running in the production environment. So we can provide an API-defined reporting platform, and even a management platform. This platform can automatically collect all APIs of the cluster, or can be directly defined by the user, and then unified distribution management is carried out through a mechanism similar to git and maven package management.

Background

Dubbo currently supports protobuf as a serialization method. Protobuf relies on proto (Idl) for code generation, but currently lacks tools for managing Idl files. For example, for java users, proto files are used for each compilation. It is more troublesome, and everyone is used to using jar packages for dependencies.

Target

Implement an Idl management and control platform, support idl files to automatically generate dependency packages in various languages, and push them to relevant dependency warehouses

Dubbo currently supports

For a large number of monolithic applications, problems such as performance will be encountered during large-scale deployment. For interface-oriented programming languages, Dubbo provides the capability of RPC remote calls, and we can help applications decouple through interfaces. Therefore, we can provide a deployer to help users realize the decoupling and splitting of microservices during deployment, and quickly provide performance optimization capabilitiesJava language features through hessian under the Java SDK, such as generics, interfaces, etc. These capabilities will not be compatible when calling across systems. Therefore, Dubbo needs to provide the ability to detect the interface definition and determine whether the interface published by the user can be described by native json.

Dubbo currently provides a very simple performance testing tool. But for such a complex framework as Dubbo, the functional coverage is very low. We urgently need a testing tool that can test multiple complex scenarios. In addition, we also hope that this set of testing tools can be run automatically, so that we can track the current performance of Dubbo in time

Since Dubbo runs on a distributed architecture, it naturally has the problem of difficult API interface definition management. It is often difficult for us to know which interface is running in the production environment. So we can provide an API-defined reporting platform, and even a management platform. This platform can automatically collect all APIs of the cluster, or can be directly defined by the user, and then unified distribution management is carried out through a mechanism similar to git and maven package management.

WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. For web client users, we can provide Dubbo's wasm client, so that front-end developers can simply initiate Dubbo requests in the browser, and realize Dubbo's full-link unification.

This task needs to be implemented on a browser such as Chrome to initiate a request to the Dubbo backend

Dubbo currently supports a large number of Java language features through hessian under the Java SDK, such as generics, interfaces, etc. These capabilities will not be compatible when calling across systems. Therefore, Dubbo needs to provide the ability to detect the interface definition and determine whether the interface published by the user can be described by native json.

At present, Dubbo provides RPC capabilities and a large number of service governance capabilities. This has led to the fact that Dubbo cannot be used well if some of Dubbo's own components only need to use RPC capabilities or some users who need extreme lightweight.
Goal: To provide a Dubbo RPC kernel, users can directly program for service calls and focus on RPC.

Dubbo currently provides a very simple performance testing tool. But for such a complex framework as Dubbo, the functional coverage is very low. We urgently need a testing tool that can test multiple complex scenarios. In addition, we also hope that this set of testing tools can be run automatically, so that we can track the current performance of Dubbo in time.

WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. For web client users, we can provide Dubbo's wasm client, so that front-end developers can simply initiate Dubbo requests in the browser, and realize Dubbo's full-link unification.

This task needs to be implemented on a browser such as Chrome to initiate a request to the Dubbo backend.

At present, Dubbo provides RPC capabilities and a large number of service governance capabilities. This has led to the fact that Dubbo cannot be used well if some of Dubbo's own components only need to use RPC capabilities or some users who need extreme lightweight.
Goal: To provide a Dubbo RPC kernel, users can directly program for service calls and focus on RPC.

Including but not limited to programming patterns, configuration, apis, documentation and demos

HTTP/3 has been formalized as a standard in the last year. Dubbo, as a framework that supports publishing and invoking Web services, needs to support the HTTP/3 protocol.

This task needs to expand the implementation of the current rest protocol to support publishing HTTP/3 services and calling HTTP/3 services.

Background

Dubbo currently supports the rest protocol based on http1, and the triple protocol based on http2, but currently the two protocols based on the http protocol are implemented independently, and at the same time, they cannot replace the underlying implementation, and their respective implementation costs are relatively high.

Target

In order to reduce maintenance costs, we hope to be able to abstract http. The underlying implementation of the target implementation of http has nothing to do with the protocol, and we hope that different protocols can reuse related implementations.

HTTP/3 has been formalized as a standard in the last year. Dubbo, as a framework that supports publishing and invoking Web services, needs to support the HTTP/3 protocol.

This task needs to expand the implementation of the current rest protocol to support publishing HTTP/3 services and calling HTTP/3 services.

Our Commons components use Commons Skin, a skin, or theme, for Apache Maven Site.

Our skin uses Bootstrap 2.x, but Bootstrap is already at 5.x release, and we are missing several improvements (UIUX, accessibility, browser compatibility) and JS/CSS bugs fixed over the years.

Work happening on Apache Maven Skins. Maybe we could adapt/use that one?

https://issues.apache.org/jira/browse/MSKINS-97

The Airavata Django Portal [1] allows users to create, execute and monitor computational experiments. However, when a user wants to then post-process or visualize the output of that computational experiment they must then download the output files and run tools that they may have on their computer or other systems. By integrating with JupyterHub the Django Portal can give users an environment in which they can explore the experiment's output data and gain insights.

The main requirements are:

• from the Django Portal a user can click a button and navigate to a JupyterHub instance that the user is immediately logged into using single sign on
• the user can save the Jupyter notebook and later retrieve it
• the user's files are available within the context of the running Jupyter instance
  • ideally users can also generate new outputs in the Jupyter instance and have them saved back in their portal data storage
• users can share their notebooks with other portal users
• (bonus) portal admins can suggest notebooks to use with specific applications so that with one click a user can open an experiment in a provided notebook
• users can manage their notebooks and can, for example, clone a notebook

[1] https://github.com/apache/airavata-django-portal

1. UI Framework 
   1. To host the jupyter environment we will need to envolop the notebooks in a user interface and connect it with Apache Airavata services 
   2. Leverage Airavata communications from within the Django Portal - https://github.com/apache/airavata-django-portal 
   3. Explore if the platform is better to be developed as VSCode extensions leveraging jupyter extensions like - https://github.com/Microsoft/vscode-jupyter
   4. Alternatively, explore developing a standalone native application using ElectronJS
2. Draft up a platform architecture - Airavata based infrastructure with functionality similar to collab. 
3. Authenticate with Airavata Custos Framework - https://github.com/apache/airavata-custos 
4. Extend Notebook filesystem using the virtual file system approaching integration with Airavata based storage and catalog
5. Make the notebooks registered with Airavata app catalog and experiment catalog. 

Advanced Possibilities:

Explore Multi-tenanted JupyterHub 

• Can K8 namespace isolation accomplish?
• Make deployment of Jupyter support as part of the default core
• Data and the user-level tenancy can be assumed, how to make sure infrastructure can isolate them, like not one gateway crashing a hosting environment.

1. How to leverage computational resources jupypter hub

As discussed on the architecture mailing list

As discussed on the architecture mailing list [1] and summarized at [2], Airavata will need to develop a metascheduler. In the short term, a user request (demeler, gobert) is to have airavata throttle jobs to resources. In the future more informed scheduling strategies needs to be integrated. Hopefully, the actual scheduling algorithms can be borrowed from third party implementations.

[1] - http://markmail.org/message/tdae5y3togyq4duv
[2] - https://cwiki.apache.org/confluence/display/AIRAVATA/Airavata+Metascheduler

Complete all transports in MFT

• Currently SCP, S3 is known to work
• Others need effort to optimize, test, and declare readiness
• Develop a complete a fully functional MFT Command-line interface
• Have a feature-complete Python SDK
A minimum implementation will be prvoided, students need to complete it and test it.
• -line interface
• Have a feature-complete Python SDK
• A minimum implementation will be prvoided, students need to complete it and test it. 

Custos does not have the capabilities to efficiently backup and restore a live instance. This is essential for high available services. 

Using SEAGrid Rich Client as an example, develop a native application based on electronJS to mimic Airavata Django Portal.

Reference example - https://github.com/SciGaP/seagrid-rich-client 

Custos does not have the capabilities to efficiently backup and restore a live instance. This is essential for high available services. 

Gateway admins need period reports for various reporting and planning. 

Features Include:

• Compute resources across that had at least one job submitted during the period <start date - End date>
• User groups created within a given period and how many users are in those and with permission levels and also number of jobs each user have submitted.
• List applications and number of jobs for each applications for a given period and group them by job status.
• Number of users that at least submitted a single job for the period <start date - End date>
• Total number of Unique Users
• User Registration Trends
• Number of experiments for a given period <Start date - End date> grouped by the experiment status
• The total cpu-hours used by a users, sorted, quarterly, plotted over a period of time
• The total cpu-hours consumed by application, sorted, quarterly, plotted over a period of time

Using SEAGrid Rich Client as an example, develop a native application based on electronJS to mimic Airavata Django Portal.