Search Results for "kubernetes"
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23 projects for "kubernetes" with 2 filters applied:
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kubectl-ai
AI assistant for managing Kubernetes clusters from the terminal
kubectl-ai is an AI-powered command-line assistant designed to help users manage and interact with Kubernetes clusters through natural language queries. It acts as an intelligent interface that interprets user intent and translates it into appropriate Kubernetes operations and commands. By integrating large language models, it enables users to ask questions or request actions in plain language instead of manually crafting complex Kubernetes commands. kubectl-ai runs directly in the terminal and integrates with the existing kubectl workflow, making it familiar for Kubernetes administrators and developers. ... -
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kMCP
Kubernetes Controller for building, testing and deploying MCP servers
KMCP is a companion toolchain for building, testing, and deploying MCP servers with a workflow that spans local development through Kubernetes production deployments. It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD), allowing MCP servers to be represented as native Kubernetes objects you can operate with familiar kubectl-driven patterns. ... -
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kagent
Kubernetes native framework for building AI agents
Kagent is a Kubernetes-native framework for building, deploying, and operating AI agents as first-class cloud-native workloads. It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. ... -
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Kubeflow Trainer
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
Kubeflow Trainer is a Kubernetes-native platform designed for scalable, distributed training and fine-tuning of machine learning models, particularly large language models, across multi-node and multi-GPU environments. It extends the Kubeflow ecosystem by providing a unified framework for orchestrating training workloads using Kubernetes primitives, enabling seamless scaling from single-machine experiments to large production clusters. -
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Open WebUI
User-friendly AI Interface
...It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security, responsive design across devices, and full Markdown and LaTeX support for enriched interactions. Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. ... -
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kgateway
The Cloud-Native API Gateway and AI Gateway
kgateway is a mature, cloud-native API and ingress gateway designed to provide unified API connectivity for services, microservices, serverless workloads, and AI-centric systems running on Kubernetes clusters. It implements the Kubernetes Gateway API and can operate as both a lightweight in-cluster microgateway and a centralized gateway capable of handling billions of API calls with high performance and low latency. By integrating with Envoy and advanced data planes, it handles modern ingress concerns such as traffic routing, authentication, authorization, rate limiting, and observability for traditional HTTP/gRPC services and AI workloads alike. ... -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
...It supports multiple programming languages through SDKs, allowing developers to integrate sandbox capabilities into their systems without building custom isolation layers. The platform is built to work with container technologies such as Docker and Kubernetes, enabling scalable and production ready deployments. OpenSandbox is particularly useful for AI agents, code execution services, and any scenario where untrusted code must be executed safely. Its architecture emphasizes flexibility, security boundaries, and operational consistency across environments. Overall, the project aims to standardize sandbox execution for modern AI and cloud native workflows. -
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Sail
A drop-in Apache Spark replacement written in Rust
...Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. It also emphasizes cost efficiency, with benchmarks showing significant performance improvements and reduced infrastructure usage compared to traditional systems. -
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Machine Learning Zoomcamp
Learn ML engineering for free in 4 months
...Later modules focus on practical engineering topics such as containerization with Docker, API development with FastAPI, and scaling machine learning services using Kubernetes and cloud platforms. The repository includes lecture materials, assignments, and projects that allow learners to gain hands-on experience implementing machine learning pipelines. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Bionic GPT
Bionic is an on-premise replacement for ChatGPT
Bionic is an on-premise generative AI platform positioned as a private replacement for ChatGPT, with a strong emphasis on data confidentiality, team collaboration, and enterprise deployment. It can run locally on a laptop for small pilots, but it is also designed to scale into data center and Kubernetes environments for much larger usage. The interface is intentionally familiar, offering a ChatGPT-like experience with customizable branding, fast Rust-based performance, and conversation history management. Beyond chat, Bionic focuses heavily on enterprise RAG by letting users create AI assistants that work with their own documents, share those assistants across teams, and configure embeddings, chunking, and system prompts through the UI. ... -
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AgentField
Build and run AI agents like microservices
AgentField is an open-source control plane designed to run AI agents as production-grade backend services, applying cloud-native principles similar to Kubernetes to the world of autonomous software. Instead of treating agents as isolated scripts or prototypes, the system elevates them to first-class infrastructure components that can be deployed, orchestrated, and managed at scale across distributed environments. Developers define agents as typed functions, and the platform automatically handles orchestration, communication, identity, and execution, allowing agents to behave like APIs within a broader system architecture. ... -
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C3
The goal of CLAIMED is to enable low-code/no-code rapid prototyping
...CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators. These operators can be orchestrated into pipelines that run on modern infrastructure platforms such as Kubernetes and Kubeflow. The system emphasizes reproducibility and scalability, allowing researchers and engineers to reuse existing components and integrate them into larger scientific or data engineering workflows. It also aims to support trusted and explainable AI systems by integrating tools for fairness analysis, explainability, and adversarial robustness. -
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Jina-Serve
Build multimodal AI applications with cloud-native stack
...The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as Kubernetes. Jina Serve focuses on making it easier to turn machine learning models into production-ready services without forcing developers to manage complex infrastructure manually. The framework supports many major machine learning libraries and data types, making it suitable for multimodal AI systems that process text, images, audio, and other inputs. -
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Polyaxon
MLOps tools for managing & orchestrating the ML LifeCycle
...It provides a unified solution for tracking experiments, managing datasets, scheduling jobs, and comparing results across runs, which greatly improves productivity and collaboration in data science teams. Polyaxon integrates seamlessly with Kubernetes and container orchestration so that workloads can be scheduled efficiently, GPU and CPU resources are shared, and distributed training across multiple nodes is straightforward. It supports connection to external Git repositories for source-controlled experiments, making it easy to pull code directly for runs and enabling continuous integration workflows with tools like GitHub Actions. -
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Ploomber
The fastest way to build data pipelines
...Ploomber automatically manages task dependencies and execution order, allowing complex pipelines with multiple stages to run reliably. The framework can deploy pipelines across different computing environments including Kubernetes, Airflow, AWS Batch, and high-performance computing clusters. It also helps teams maintain reproducibility by tracking changes in code and rerunning only outdated pipeline tasks. -
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Casibase
Open-source enterprise-level AI knowledge base and MCP
Casibase is an open-source AI cloud platform designed to function as an enterprise knowledge base, container management system, and collaboration environment for AI-driven applications. The project combines knowledge management, messaging, and forum features with large language model integration to create an interactive platform for storing and querying domain-specific knowledge. Built with a separated frontend and backend architecture, Casibase provides a web-based administrative interface... -
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HolmesGPT
CNCF Sandbox Project
HolmesGPT is an open-source AI agent designed to help DevOps and site reliability engineering teams diagnose and resolve production incidents. The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in... -
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Google Agent Skills
Agent Skills for Google products and technologies
...Each skill provides guidance, best practices, and procedural instructions that agents can use to perform tasks more effectively. The repository includes skills for services like BigQuery, Cloud Run, Firebase, and Kubernetes, as well as onboarding and architectural patterns. It is designed to integrate with agent platforms through a standardized installation system. The project emphasizes reusable, composable knowledge units that can enhance agent reasoning and execution. It is actively developed and intended to support modern AI-driven development workflows. ... -
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also... -
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...Using tools such as Librosa and ONNX, it performs sonic analysis on your audio files locally, allowing you to curate playlists for any mood or occasion without relying on external APIs. Deploy it easily on your local machine with Docker Compose or Podman, or scale it in a Kubernetes cluster (supports AMD64 and ARM64). It integrates with the main music servers' APIs such as Jellyfin, Navidrome, LMS, Lyrion, and Emby. More integrations may be added in the future. AudioMuse-AI lets you explore your music library in innovative ways, just start with an initial analysis, and you’ll unlock features like Clustering, Instant Playlist, Music Playlist and many more
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LlamaGPT
Self-hosted ChatGPT-like chatbot powered by Llama models locally
LlamaGPT is a self-hosted chatbot application designed to provide a conversational AI experience similar to ChatGPT while running entirely on local hardware. It uses Llama-based large language models to generate responses and operate without requiring external AI services. Because the system runs locally, it keeps all interactions and data on the user's device, enabling a fully private environment for experimentation with AI chat interfaces. LlamaGPT includes both a user interface and an API... -
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OptiMate
Libraries for optimizing AI models, inference speed, and GPU usage
...One of the core components, Speedster, focuses on accelerating model inference by applying state of the art optimization techniques to increase performance while lowering operational costs. Another component, Nos, targets infrastructure optimization by improving GPU utilization in Kubernetes clusters through dynamic partitioning and elastic resource quotas. -
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SQLFlow
SQL compiler bridging databases and machine learning workflows
SQLFlow is an open source project designed to bridge the gap between traditional SQL-based data processing and modern machine learning workflows by extending SQL syntax with AI capabilities. It acts as a compiler that translates SQL programs into executable workflows, enabling users to train, evaluate, and deploy machine learning models directly from SQL statements. It integrates with multiple database engines such as MySQL, Hive, and MaxCompute, while also supporting machine learning...
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