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In the existing Karmada architecture, each component should have its own unique certificates to ensure clear identity and security. Best practices dictate that each component's name be used as the Common Name (CN) in its certificate to facilitate identity differentiation. However, currently, all Karmada components share same identical certificate content, leading to confusion and potential security risks. The objective of this project is to enhance the compliance of the Karmada certificate system by ensuring that each component possesses distinct certificates that reflect its identity. This will improve system security, reduce management complexity, and align with industry standards. This project aims to achieve the following standards: 1. Utilize a single CA certificate for the entire Karmada system. 2. Issue individual server certificates for each server component, using the component name as the CN. 3. Issue individual client certificates for each client component, using the component name as the CN, same client can use consistent certificate for different servers. Expected Outcome: 1. Complete the issuance of different certificates for 8 server components and import the certificate content into the corresponding certificate Secrets. 2. Complete the issuance of different certificates for 11 client components and import the certificate content into the corresponding certificate Secrets or Config Secrets.
The KCL package management tool primarily handles the management of third-party KCL packages for the KCL project, which includes tasks such as uploading and downloading these packages. When adding third-party packages to the KCL project, it is important to adhere to version management strategies. This involves carefully selecting and downloading the appropriate version of a package, especially when different versions of the same package are available. Expected Outcome: Add version management to the KCL package management tool.
The Hyperledger Labs AIFAQ is an LLM ChatBot testable as a proof-of-concept. It replies to questions about Hyperledger standard documentation. The current version is a Google Colab Notebook which uses Gradio as GUI. This project proposes an implementation of a standard ChatBot GUI and the deployment of a prototype. Our end goal is to have a more usable system installed on a Cloud Server. Learning Objectives - Learn LLM background technology - Learn Javascript language and framework - Learn basics of Front-end development - Learn Cloud architecture and deployment - Learn how to create high quality documentation Expected Outcome and Deliverables - A Front-end component prototype - A simple container architecture - A good quality documentation
This internship will provide the opportunity to learn open source community standards, values, and processes by joining and contributing to the OpenDaylight community. The intern will interact with community members across many corporations large and small. Application of modern UX analysis, design, and website implementation technologies will provide ample opportunity to grow the applicant's skill set. The applicant will also learn some basic marketing principles in working with the LFN marketing team on this project.
Now VTP as the VNF test platform can support OVP VNF compliance and validation test. It can manage and orchestrate different VNF testing scenario across different SUT environment like ONAP MANO, OpenStack Cloud, Vendor VNFM, SDN Controller, etc under one umbrella across different Test providers and partner labs. As the open source test platform, it should include standard test case from standard organization, so that it can support the testing for standard component which can accelerate OVP test and certification process for commercial products implemented by reference standards. VTP is going to support ETSI NFV APIs conformance test. The mentee will be required to make the technical research and develop related test cases and integrate with VTP under guide of our team.
Integrate a new user experience into Meshery: a cloud native design configurator. This project involves presentation of Kuberenetes core resources and any custom resource (CRD) as a configurable component in a React-based user interface in which users design (in great detail) and deploy their cloud native infrastructure. Interns will familiarize with concepts of content lifecycle management.
Enhance Meshery's existing orchestration capabilities to include support for kro ResourceGraphDefinitions (RGDs) as first-class Meshery Models. This involves enabling Meshery to manage and orchestrate RGDs, similar to how it handles other Kubernetes resources. The project will also include generating support for ResourceGraphDefinition in Meshery's Model generator. Expected Outcome: - Meshery will be able to orchestrate and manage kro RGDs. This includes the ability to deploy, configure, and manage the lifecycle of RGDs through Meshery. The Meshery Model generator will be updated to automatically generate models for kro RGDs, simplifying their integration and management within Meshery. This will be an officially supported feature of Meshery.
Description: Use OCI References in image verification Expected Outcome: PR sent to kyverno/kyverno implementing support for OCI references in verifyImages rules
Microcks is a cloud native, open source tool under CNCF for API and microservices mocking and testing. This project focuses on creating a validated and repeatable SaaS architecture for deploying Microcks on AWS, with the ultimate goal of listing it on the AWS Marketplace through the AWS Partner Network Co-Sell program. By addressing the community's frequent demand, this initiative will simplify Microcks' adoption while leveraging a complete suite of AWS services to ensure scalability, security, and ease of deployment. The core Microcks maintainers focus on features, security, and enhancements. The adopters are responsible for production setups. However, a shared repository of best practices can help users learn from one another in a true open-source spirit. Participants will contribute to the Microcks community repository by documenting the AWS Marketplace deployment. Expected Outcome: Enable Microcks adopters to confidently deploy production-ready setups on AWS, ensuring the scalability and reliability needed for enterprise environments. By integrating Microcks into the AWS Marketplace, the project will further enhance its visibility and adoption within the AWS ecosystem. - Designing and validating a SaaS architecture that is compliant with AWS Foundational Technical Review (FTR). - Utilizing AWS-native services such as EKS, Aurora (PostgreSQL), DocumentDB, API Gateway, IAM, and CloudFormation for an end-to-end deployment. - Streamlined deployment workflows
Description: This project consists of developing an example Unity setup of a multiplayer game using the latest version of the NATS Server. Expected Outcome: A well documented repository under the `nats-io` GitHub organization that contains the artifacts and sample code of the setup using the .NET NATS Client (https://github.com/nats-io/nats.net)
Kruise Rollout (https://github.com/openkruise/rollouts) provide plugin-n-play progressive delivery for cloud native apps. The goal of this project is to develop a kubectl plugin so as to visualize rollout progress, e.g. the rollout steps, traffic status and involved pods. The kubectl plugin can leverage the existing kruise kubectl plugin project (https://github.com/openkruise/kruise-tools), and can use the Argo kubectl plugin (https://argo-rollouts.readthedocs.io/en/stable/features/kubectl-plugin/#visualizing-rollouts-and-experiments) as a reference. Expected Outcome: * kruise-tools enhancement for kruise rollout visualization * Well-documented with clear usage instructions and examples
Official website docs has not been updated for a long time including technology docs, talks, best practice and so on, which bothers users and developers a lot.
SidecarSet is an advance workload for sidecar container injection and upgrade. Currently the sidecar container resource must be set explicitely in the sidecar template, however in the cases of traffic proxy, log collection and device emulation etc, it is desirable to to set the resources according to resource of app container. The goal is to support the adaptively setting for sidecar resources and provide best practice for typical use cases. Expected Outcome: 1. Implementation for adaptively resources setting for sidecar in SidecarSet workload 2. Unit and integration tests 3. Documentation for the function usage and typical use cases in the OpenKruise website
This project focuses on implementing the backend API for managing Binding Policies. The API should support creating, reading, updating, and deleting policies while ensuring robust validation and performance. Objectives - Develop backend API endpoints for Binding Policy management. - Ensure proper validation and enforcement of Kubernetes standards. - Optimize backend performance for handling multiple policy requests. - Implement logging and error handling for better debugging. Expected Outcomes - A secure and scalable backend API for Binding Policies. - Full CRUD functionality accessible from the UI. - Improved validation and performance optimizations.
The Zowe Virtual Desktop needs to provide a way to easily transfer files and datasets from the mainframe to a user desktop and vice versa, while dealing with encoding and security.
OPNFV VSPERF already includes comprehensive Monitoring solution. However, it lacks the Log-Analysis and Alert-Management solution. This project aims to include log and alert management solutions based on opensources - ELK Stack. This will enhance the ability of VSPERF to: 1. Perform post-test correlation/causation analysis. 2. Adapt the Test-Traffic patterns based on the Alerts. The first aim is to create custom kibana dashboard analyzing and synthesizing VSPERF logs/events. For every test-run, VSPERF generates following logs: 1. vsperf-overall 2. vswitchd 3. trafficgen 4. host-cmds 5. guest-cmds These logs have useful information that can help user to understand the test behavior, and analyze the performance results. VSPERF will have Alerting from the Monitoring component, and lacks alerting from the logs. As the next step, this project aims to use the same information - The logs - and create alerts than will be notified to VSPERF.
<p>Currently, urunc launches sandbox monitors, such as Firecracker and QEMU</p><p>through command-line invocations. This approach offers limited control over the</p><p>sandbox lifecycle once the process is started. On the other hand, most</p><p>monitors expose remote management interfaces, typically through a socket-based</p><p>API.</p><p><br></p><p>These interfaces provide access to the same operations currently performed via</p><p>CLI, but also enable further control over the sandbox lifecycle. In particular,</p><p>they allow more fine-grained lifecycle management of the sandbox, including</p><p>querying and monitoring its state, performing device hotplug and unplug</p><p>operations and interacting with the guest.</p><p><br></p><p>This project aims to extend urunc's sandbox integration layer to support remote</p><p>management interfaces and to explore each monitor's capabilities in order to</p><p>extend the functionalities of urunc sandboxed containers.</p><p><br></p><p>Expected Outcome:</p><p> - A design document describing the updated architecture and workflow for</p><p> spawning and managing sandbox monitors in urunc.</p><p> - Implementation of the necessary changes in urunc to manage sandbox monitors</p><p> through their respective APIs.</p>
The component-model proposal merges and supersedes the Module Linking and Interface Types proposals. With this feature, WasmEdge can execute multiple modules wasm with Module Linking and and more flexible types with Interface Type.
Cloud Native Buildpacks is a specification and set of tools that help you take source code and convert them into OCI images. Sound familiar? Maybe you've heard of Docker, Source-2-Image, Kaniko, etc. Well you are not alone. The goal of this project is to refactor our existing ["features" page](https://buildpacks.io/features/#comparison) to provide an easier to comprehend comparison across other similar solutions. Through this project, you'll research each alternative, learn how they compare and aim to provide that information to the users in an easy to digest format. This will include designing and implementing a better format to compare projects and their features side-by-side.
All In is a community dedicated to advancing diversity, equity, and inclusion within open source. All In for Students is a paid, 12-month program for select college students from underrepresented backgrounds. During the program, students will receive professional development training, open source education, a structured 12-week open source project, and ultimately have the opportunity to join one of our corporate partners for a summer internship experience.
Envoy is an open source edge and service proxy, designed for cloud-native applications.
FINOS (FinTech Open Source Foundation - part of the Linux Foundation) is looking for a summer marketing intern to assist with: - Marketing research (members, projects, BD) - Social media (research, operations) - Content for website (research, operations) - Podcast production (research, operations)
The RISC-V Mentorship Program enables one or more 12-week internship-style projects per session, funded by RISC-V, to match mentors/project leaders together with mentees/interns . Mentees are guided through a series of milestones by one or more project mentors, with whom the mentees meet on a weekly basis. Convolution is the core operation of deep learning models and computer vision applications. MLIR supports various convolution operations. Our project is to vectorize them for the RISC-V backend. There are several methods to implement convolution vectorization, such as optimizing nested loops, implementing vectorization algorithm, converting to GEMM, etc. This project needs to choose a vectorization method and implement a conversion pass for the convolution operations. As for the vector semantic support, MLIR has the “Vector” dialect for the general vector abstraction, and it also allows the backend-specific vector dialect, such as the “x86vector” dialect, “arm_neon” dialect, and “arm_neon” dialect. Like these dialects, the project also needs to propose an “RVV” dialect and work with existing dialects and tools. Deliverables: - An MLIR “RVV” Dialect. (Operations in the dialect can support the convolution vectorization) - A conversion pass to vectorize convolution operations in “Linalg” dialect with “RVV” dialect enabled. - A conversion pass to lower the operations in “RVV” dialect to “LLVM IR” dialect. - Unit tests for “RVV” dialect and conversion passes.
The Software Package Data Exchange (SPDX) is an open source standard for communicating software bills of material information (including components, licenses, copyrights and security references). To support SPDX, an online tool has been developed which provides an easy all-in-one website to upload and parse SPDX documents for validation, comparison and conversion and search SPDX license list. This project will provide enhancements and support for the online tools including: - More automated and high-quality deployment for software updates - Removing some of the dependencies on a Python Java Bridge by moving features like license matching over to a native Python implementation - Improving performance and quality of the online tools implementation