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The emergence of blockchain interoperability in the last few years has been playing a pivotal role in the development of blockchain technology. Hyperledger has been supporting multiple projects in this domain, leading to semantic and technical interoperability advancements. For example, Hyperledger has been investing resources in the adoption of different interoperability standards, such as the Secure Asset Transfer Protocol (SATP), being standardized at the Internet Engineering Task Force (IETF) However, security, privacy, and organizational interoperability are still the most prominent challenges in the space. This internship attempts to partially address these issues. This internship connects these three dots by offering the ability to Hyperledger Cacti to create robust consortia that adhere to privacy and security needs, required by organizations leveraging our open-source project. The present internship compresses the development and studying of the API Server, a core component of the Cacti Node. The mentee will develop API Server support for gRPC and the Connect protocols. Furthermore, an integration with SATP to create consortia will be performed. This can be achieved with some scripts for the end user to generate API Servers and SATP consortia configurations, served by a simple UI. This could become the new de-facto Cacti UI.
This project aims to bring real-time, AI-powered live translation to the eventyay-video platform. Currently, the SUSI Translator prototype works well but relies on local computer microphones and standalone scripts. To make it ready for live online events, this project will upgrade it into a fast, web-native system that works entirely in the browser. The solution captures live audio directly from the speaker's browser, immediately filtering out silence to save server costs. This speech is then streamed at high speeds to a backend server. There, AI models (Whisper and an LLM) transcribe and translate the speech. To prevent robotic or broken grammar, the AI uses a "sliding window" to remember the last few spoken sentences, ensuring translations make sense in context. Finally, the translated text is sent back to the audience's screen as smooth, easy-to-read subtitles. Key Deliverables: - A browser-based audio capture and silence-filtering module. - A high-speed server connection (WebSockets) for instant data transfer. - A context-aware AI translation pipeline that prevents grammatical errors. - A stable, flicker-free subtitle interface built directly into the eventyay-video player.
<p>Our objective is to determine the best architectural and parallelization options for the BLonD future C++ code base. Project includes:</p> <ul> <li>Existing simulations performance profile data and component interaction diagrams.</li> <li>Micro benchmark data selection for regional stress testing that can reveal of currently existing architectural pitfalls.</li> <li>Prototypes for potential architecture evolution that are exclusively designed for BLonD performance optimization covering wide amount of task and data parallelization technics: from local SMID optimizations and coprocessor kernels to cluster technics.</li> </ul> <p>Main project deliverable will be a report covering possible architecture directions rooted in profile data, performance tests and future possibilities. This report will include UML diagrams showing architectural blueprints for concurrency and parallelism directions, structured performance analysis of performed tests and created prototypes, a table comparing selected technologies in terms of:</p> <ul> <li>Top available simulation scale.</li> <li>Integration into current architectural model.</li> <li>Prototype testing results.</li> <li>Profiling tools.</li> <li>Publically available information and documentation.</li> <li>Hardware requirements.</li> </ul>
Institutional departments, such as the Biomedical Informatics (BMI) Department of Emory University School of Medicine, manage vast amounts of data, often reaching petabyte scales across multiple Linux-based storage servers. Researchers storing data in these systems need a streamlined way to modify ACLs to grant or revoke access for collaborators. Currently, the IT team at BMI is responsible for manually handling these ACL modifications, which is time-consuming, error-prone, and inefficient, especially as data volume and user demands grow. To address this challenge at BMI and similar institutions worldwide, a Web Management Interface is needed to allow users to modify ACLs securely. This solution would eliminate the burden on IT teams by enabling on-demand permission management while ensuring security and reliability. The proposed system will feature a robust and highly configurable backend, high-speed databases, orchestration daemons for file storage servers, and an intuitive frontend. The proposal includes an in-depth analysis of required components, high-level and low-level design considerations, technology selection, and the demonstration of a functional prototype as proof of concept. The goal is to deliver a production-ready, secure, scalable, and reliable system for managing ACLs across multiple servers hosting filesystems such as NFS, BeeGFS, and others. This solution will streamline access control management and prepare it for deployment at BMI and other institutions worldwide, significantly reducing the manual workload for IT teams.
<p>The goal of the project would be to add support for PSIMI-TAB format to the admin tools of the DV-IMPACT database and allow the upload and download of PPI network data in the same format. Currently, the data upload can only be performed by the database admin. The objective is to create registration and user profile system that allows users to register and upload their own data independently without the need of the database admin to be involved in the upload process.</p> <p>The summarized goals would be:</p> <ol> <li>Create registration and user profile system that allows users to register and upload their own data independently.</li> <li>Add support for PSIMI-TAB format to the admin tools of the DV-IMPACT database.</li> <li>Add download PPI networks in PSIMI-TAB format to the frontend of DV-IMPACT database.</li> </ol> <p>The Project fulfills all these issues by:</p> <ol> <li>Creating a User Profile system type forum.</li> <li>Allow users to register, upload and download domain-peptide PPI data in the specified format.</li> <li>Modify the DV-IMPACT database present in the server to handle the upload to the admin tools in PSIMI-TAB format.</li> </ol> <p>Link to the evaluation task: <a href="http://dvimpact.herokuapp.com/" target="_blank">http://dvimpact.herokuapp.com/</a></p> <p>Github Repo: <a href="https://github.com/jajodiaraghav/DV-IMPACT" target="_blank">https://github.com/jajodiaraghav/DV-IMPACT</a></p>
OGC SensorThings API is an international standard to eliminate vendor lock-ins in IoT systems and to create an open geospatial ecosystem by defining a standard data model and describe how to retrieve the ingested data. However, the standard by itself does not specify a way to physically store the data. Most of the current server implementations are all based on Postgres databases using the PostGIS extension. Unfortunately, relational databases are not a great choice to store large volumes of data, which is often the case with IoT applications. As a result, retrieving large volumes of data from any of the open source SensorThings API servers is painfully slow. Modern data lakehouse standards and cloud-native geospatial file formats offer a scalable, modular, cost-effective and a much faster way to store and work with large volumes of geospatial data on the web. Specifically, Apache Iceberg is an open table format for organizing data lakes in object stores and ensuring ACID guarantees. GeoParquet is a cloud-native geospatial file encoding, based on a columnar data storage format for tabular data that significantly compresses the data and improves querying efficiency. A cloud native SensorThings API extension using Apache Iceberg could significantly enhance the standard's ability to ingest and aggregate large heterogeneous streams of sensor data. The proposal hence puts forth a design architecture for any SensorThings API server to use Iceberg to store and retrieve sensor data in a more efficient manner reducing memory overhead and network latencies when retrieving such data over the web. Eventually, as GeoParquet gets merged into Iceberg, the implementation will support a much faster alternative to existing SensorThings API implementations for handling sensor data at scale.
<p>[Headlamp](https://headlamp.dev) is an open-source, extensible Kubernetes web UI offering easy cluster management, multi-cluster support, RBAC, and a plugin system for adding custom functionality. Users who work with Kmesh today have to switch back and forth between Headlamp (for general Kubernetes resource management) and CLI tools / `kubectl` (for Kmesh-specific inspection), which creates a fragmented workflow and a poor user experience. There is currently no simple visual way to view Kmesh resources, inspect waypoints and related components, understand overall mesh status, or troubleshoot issues quickly from within an interface users already use. This project proposes building a Headlamp plugin for Kmesh that brings Kmesh resources directly into the Headlamp UI, providing lightweight visibility of Kmesh resources alongside other Kubernetes resources. The full-featured Kmesh dashboard remains the place for advanced operations; the Headlamp plugin focuses on reducing context switching and improving ease of use for day-to-day workflows.</p><p><br></p><p><br></p><p>Expected Outcome:</p><p><br></p><p> - A Headlamp plugin (TypeScript/React) that registers Kmesh CRDs and surfaces them as first-class resources in the Headlamp UI.</p><p><br></p><p> - List and detail views for core Kmesh resources (e.g., waypoints and eBPF map)</p><p><br></p><p> - Visual indicators of mesh status: per-resource health, readiness, and recent Events; cluster-level summary of Kmesh components.</p><p><br></p><p> - Inspection helpers: pretty-printed YAML, related-pod views, and quick links to associated workloads/services.</p><p><br></p><p> - Documentation (README, screenshots, install guide) and a published plugin (Helm/manifest or Headlamp plugin registry entry).</p><p><br></p><p> - Unit/component tests for the plugin and an end-to-end smoke test against a kind/minikube cluster running Kmesh.</p>
<p>Meshery is the open source cloud native manager that empowers platform engineers to design and operate infrastructure. As infrastructure complexity grows, the need for intelligent assistance becomes critical. This project focuses on developing and enhancing a dedicated AI Adapter and AI Connections for Meshery. This adapter serves as the bridge between Meshery’s core orchestration engine and various Large Language Models (LLMs). The goal is to enable "Natural Language to Infrastructure" capabilities, allowing users to describe their architectural intent (e.g., "Deploy a highly available Kubernetes cluster on AWS with Prometheus monitoring") and have Meshery auto-generate the visual topology and configuration manifests. The intern will work on decoupling the AI logic from the core platform, allowing users to "Bring Your Own Key" (BYOK)—supporting both cloud-based providers (OpenAI, Anthropic) and local inference runners (Ollama, LocalAI).</p><p><br></p><p>Recommended Skills:</p><p> - Proficiency in Golang (Go) is essential, as Meshery’s backend is written in Go.</p><p> - Familiarity with MCP Servers, REST APIs, LLM APIs (OpenAI, Vertex AI), local inference servers (Ollama).</p><p> - Basic understanding of Kubernetes, Docker, and Infrastructure-as-Code (IaC) concepts.</p><p> - Experience with REST, GraphQL, and gRPC.</p><p> - Nice to have: Experience with React (for frontend integration in Meshery UI).</p><p><br></p><p>Responsibilities:</p><p> - Co-design and implement the interface for the AI Adapter in Go to communicate with the Meshery Server.</p><p> - Implement support for connecting to local LLMs (via Ollama) to ensure data privacy for users who cannot send infrastructure data to the public cloud.</p><p> - Improve the "System Prompt" and context-window management to feed the LLM relevant data regarding Meshery Models (schema definitions) so the AI generates valid infrastructure configurations.</p><p> - Write unit and integration tests to ensure the reliability of the adapter.</p><p> - Create user guides on how to configure the adapter with different AI providers.</p><p>- Expected Outcome:</p><p> - A fully functional AI Adapter (or Connection) integrated into the Meshery ecosystem.</p><p> - Demonstrable capability for users to swap between at least two different LLM providers (e.g., OpenAI vs. a local Llama 3 model).</p><p> - Implementation of a feature where natural language queries result in a rendered design.</p><p> - Merged pull requests (PRs) including code, tests, and documentation.</p><p><br></p>
<p>Kyverno recently completed two CNCF assessments: a security assessment by the CNCF TAG Security & Compliance group and a General Technical Review by the CNCF TOC Project Reviews subproject. Together they produced a set of findings spanning documentation, threat modeling, network policies, global context cache bounds, API server authentication, SAST tooling, API stability and non-goals, UX/adopter research, webhook cert issuance/rotation guidance, "safe-mode" / temporary disable patterns, SLOs/SLIs and alerting/runbooks, dependency lifecycle and SCA workflows, third-party notices, and the security response process. The findings are tracked in umbrella issues for each assessment. In this mentorship, the mentee will work through the open findings from **both** the TAG Security & Compliance assessment and the General Technical Review, propose and implement fixes across the Kyverno codebase, docs, and Helm charts, and help close out both assessments. Work includes implementing cache bounds for the Global Context, restricting Global Context access in namespaced policies, adding API server request authentication for the admission webhook, generating sample/network-policy templates and a CLI command to produce a Kyverno NetworkPolicy, integrating SAST tooling (e.g. semgrep, Nancy) into CI, updating the threat model and architecture diagrams, documenting core CRDs/API stability, webhook cert rotation, safe-mode/incident playbooks, SLOs/SLIs and reference dashboards, the SCA/dependency lifecycle workflow, and improving the security documentation on kyverno.io.</p><p><br></p><p>Expected Outcome:</p><p> - Resolve the open findings tracked in [kyverno/kyverno#15335](https://github.com/kyverno/kyverno/issues/15335) (TAG Security & Compliance assessment) and [kyverno/kyverno#15473](https://github.com/kyverno/kyverno/issues/15473) (General Technical Review assessment).</p><p> - Implement Global Context cache bounds and access restrictions for namespaced policies (kyverno/kyverno#15359).</p><p> - Add admission webhook authentication of requests from the API server.</p><p> - Refresh the threat model (including CLI and other deployment options) and the architecture diagram to separate logical and physical components.</p><p> - Document core CRDs/APIs and per-API-group stability policy, webhook cert issuance/rotation guidance, recommended "temporary disable" / safe-mode patterns, SLOs/SLIs with reference dashboards/runbooks, and the end-to-end dependency/SCA workflow.</p><p> - Update the Kyverno security documentation: fix the audits page links, document risks of external data lookups, link to published security advisories, and link the current security response process.</p><p> - Add tests covering the new behaviors and document the changes in the Kyverno docs site.</p><p><br></p>
<p>This project aims at implementing TDS (Tabular Data Stream) protocol of Microsoft SQL Server based on SPI of the Reactive SQL Client for Eclipse Vert.x. It should be a reactive non-blocking client and provide the abilities to interact with MSSQL server including connection, authentication, query execution and SQL data types encoding and parsing.</p>
FFmpeg can send WebRTC streams via WHIP but has no way to receive them. This project fills that gap by implementing a WHEP demuxer in libavformat, built on top of the existing WHIP code. The plan is to reuse SDP, ICE, DTLS, and SRTP as much as possible and just flip the direction. The end goal is making ffplay whep://server/stream work, with a clean patch series ready for ffmpeg-devel.
The project aims to create an intuitive tool in React for browsing AiiDA graphs, replacing the outdated AiiDA Provenance Browser in Materials Cloud Explore. This tool will interface with AiiDA via REST API, enabling dynamic graph exploration, clear differentiation of input and output nodes, complete visualization of connecting nodes, and node preview without page redirection. The desired result is an AiiDA node graph viewer developed with React, potentially published as a Component on the npm repository
The website lacks visual consistency, accessibility features, and a dark mode—critical elements for enhancing the experience of developers and engaging contributing organizations. To address this, I will follow a two-phase approach: first, planning and designing UI components and layouts.; second, implementing these designs using React.js, Next.js, TypeScript, and Tailwind CSS v4.0. Deliverables include a responsive, accessible interface, reusable component system, robust dark mode support, and performance-optimized code.
<p>TrackPal is a public based mobile application that will be implemented using react-native. And the components that are in operation with this application, will be created based on the Go-social components. By using this mobile application, users can share their locations when they are on a bus or train and that shared location will be updated when it moves and other users can see the shared details. This will solve the problem with users have, so that they can find the bus's or train's current location by just tapping on a route or train number on the screen.</p>
Ipv6 is the internet's future, and it necessitated a more scalable survey tool to comprehend how routing, DNS function and other traffic. The purpose of this project is to create an IPv6 listener that will passively collect IPv6 traffic data as a passive data collection tool for cyber security research. Survey6 tool has three main components: Probe, C&C Server & Data Aggregator. This year's aim is to design and implement a data aggregate component. It aims to design a big data scale async and robust data uploading pipeline.
<p>The current web application of OWTF has no login/signup implementation. Through this project, I want to work on developing the login and signup components using React with Redux for state management. I will also work on implementing a set of full-fledged robust API endpoints for serving these login/signup-related requests. As part of this project, I will also like to add OAuth authentication using Google, GitHub, and Twitter. Finally, I will write unit/functional tests to guarantee the proper working of each component ensuring the complete module is foolproof.</p>
<p>A common sight on today’s streets is the number of abandoned animals languishing on the streets suffering with injuries and disease and live without a any shelter. The silent suffering of these souls caught the attention of dynamic, animal lover, so Animal Rescue App initiative to develop a mobile app to track animals that are in need of help. Animal Rescue App Connect animal lovers, vets, and other NGOs in real time. They Can Track the Animals That Actually Need the Help. The Mobile Application will Implement From the React native using the Components of the Go social and firebase and the admin Website from the React js and firebase.</p>
In order to improve Thanos usage for users, we would like to define our APIs, both HTTP and gRPC, in protobuf/OpenAPI and expose the automatically generated documentation in the website. We also want to define the configuration of our components in protobuf. This would allow users to use tools for documentation, validation, type checking and even code generation to use our APIs efficiently. During this project we also expect collaboration with the Prometheus project to implement similar improvements on Prometheus' side. https://github.com/cncf/mentoring/blob/master/summerofcode/2021.md#port-the-prometheus-api-to-openapi. Optionally we would like to work on the index page on every Thanos component server that will expose those resources for easier debug.
kruise-game contains two CRDs GameServer and GameServerSet. Game servers can be managed by deploying or changing the corresponding CR. However, in actual production use, a release or operation and maintenance action is often a combination of a series of operations on CR. For example, set the GameServer image tag with ids 1, 7, and 10 to v0.3; adjust the update priority of GameServer with ids 5, 9, and 11 before updating the game server, etc. Therefore, a set of APIs with operation and maintenance semantics is needed, which users can directly use or integrate into their own operation and maintenance platform to facilitate operation and maintenance operations. Expected Outcome: * A service component that includes multiple APIs
<p>This proposal will present the project goal of idea 5, which is to integrate the web-monitoring software into the Wayback Machine and help to further advance it, and how this can be achieved. More specifically, the following solutions are suggested as part of the implementation plan: making the login screen optional, querying the CDX server and not the web-monitoring-db, implementing a mechanism for making changes to the UI easily, improving the code so it is able to handle a lot more data, using The Wayback Machine's calendar to present a webpage capture's dates, and keeping only the required project components. In addition, this proposal contains a link to a server hosting my implementation of some of the proposed solutions. Apart from that, a timeline that presents a rough plan of how the project would be implemented is included. Last but not least, biographical information is provided.</p>
<p>Since the migration to Android Architecture Components has already started, this project aims to integrate Room instead of SQLiteDatabase as a better approach for data persistence. This idea involves the following challenges:</p> <ul> <li>Initially, all the API responses need to be cached in order to reduce the number of connections to the server (especially Featured Projects and the Categories displayed on the main screen)</li> <li>To continue, the structure of the projects (JSON instead of XML) needs to be improved</li> <li>Showing and caching the user projects (local/on-server-stored projects) in the Projects screen will give the user the control to modify/delete his projects from one place</li> <li>Kotlin will be the only used language -- no more Java!</li> <li>MVVM architecture will be used.</li> </ul>
<p>Robots are slowly becoming a part of the internet of things, and easy control and universal access will be a step in future of robotics. MRPT’s Web Framework Library should address this problem.A lightweight publisher/subscriber mechanism needs to be created for MRPT. The C++ server library and the javascript library will then leverage this to create further applications. There will be two libraries, a C++ server library for RPC on the robot. Another will be a javascript library which provides modules for such procedure calls.This task involve serialization of existing mrpt objects for JSON transfer, RPC protocol, websocket setup, 3D rendering of objects in js, reusable js components for sending and receiving data from user created app where the user is largely benefitted from easy to use library methods and objects.</p>
Kubeflow Pipelines (KFP) currently only supports MySQL/MariaDB databases, creating a significant limitation for many organizations that standardize on PostgreSQL. This project aims to implement comprehensive PostgreSQL support across the KFP stack, including the API server, cache server, and ML Metadata components. The solution involves developing database abstraction layers, SQL dialect adapters, and migration tools that enable users to seamlessly deploy KFP with PostgreSQL backends. By providing this integration, the project will greatly expand deployment options for enterprise environments where MySQL is prohibited by policy, benefit organizations leveraging PostgreSQL's superior data warehousing capabilities, and eliminate the need for unsupported workarounds that currently require substantial effort from users. The end result will be a more flexible, enterprise-ready Kubeflow Pipelines platform that meets diverse organizational requirements.
Vitess uses a couple of tools to benchmark its codebase and to make sure that new code doesn’t introduce performance regressions. These tools are: arewefastyet and the VReplication Benchmarking Framework. We currently have an old frontend UI that serves arewefastyet. However, this UI is slow, not optimized and not easily extensible. It uses the built-in Golang template system to serve pages. We would like to create a common frontend UI that will be used by both benchmarking tools and that will replace the current arewefastyet’s UI. The mentee will have the responsibility of creating the UI using (most likely) React/Vite on Vercel. The frontend component will connect to our already-existing backend components: a MySQL database and arewefastyet’s REST API. - Expected Outcome: The expected outcome is to have a working frontend UI that integrates well with our different backends (databases and benchmarking tools’ APIs).