Best AI tools for< Kubernetes Administrator >

KubeHelper is an AI-powered tool designed to reduce Kubernetes downtime by providing troubleshooting solutions and command searches. It seamlessly integrates with Slack, allowing users to interact with their Kubernetes cluster in plain English without the need to remember complex commands. With features like troubleshooting steps, command search, infrastructure management, scaling capabilities, and service disruption detection, KubeHelper aims to simplify Kubernetes operations and enhance system reliability.

Parity is the world's first AI SRE tool designed to assist on-call engineers working with Kubernetes. It acts as the first line of defense by conducting investigations, determining root causes, and suggesting remediation before the engineer even opens their laptop. With features like Root Cause Analysis in Seconds, Intelligent Runbook Execution, and the ability to chat directly with the cluster, Parity streamlines incident response and enhances operational efficiency.

Webb.ai is an AI-powered platform that offers automated troubleshooting for Kubernetes. It is designed to assist users in identifying and resolving issues within their Kubernetes environment efficiently. By leveraging AI technology, Webb.ai provides insights and recommendations to streamline the troubleshooting process, ultimately improving system reliability and performance. The platform is user-friendly and caters to both beginners and experienced users in the field of Kubernetes management.

unSkript is an Agentic Gen AI platform designed for IT support, offering proactive health checks, issue diagnosis, and resolution. It leverages AI to detect and resolve customer issues before they escalate, reducing MTTR and improving resolution rates. The platform uses Agentic AI for intelligent correlation of signals, automated RCA, and Generative AI-based remediation. unSkript is trusted by top companies worldwide and aims to transform reactive issue detection into proactive product health monitoring.

Roboweb is an AI assistant designed for exploratory programming. It integrates OpenAI's ChatGPT into JupyterLab to provide users with an optimal environment for exploratory programming tasks. The tool assists users in fixing errors in their code, deploying applications on Kubernetes, and managing their OpenAPI keys seamlessly. With a user-friendly interface and advanced AI capabilities, Roboweb aims to streamline the programming process and enhance productivity for developers and programmers.

Kubeflow is an open-source machine learning (ML) toolkit that makes deploying ML workflows on Kubernetes simple, portable, and scalable. It provides a unified interface for model training, serving, and hyperparameter tuning, and supports a variety of popular ML frameworks including PyTorch, TensorFlow, and XGBoost. Kubeflow is designed to be used with Kubernetes, a container orchestration system that automates the deployment, management, and scaling of containerized applications.

AquilaX is an AI-powered DevSecOps platform that simplifies security and accelerates development processes. It offers a comprehensive suite of security scanning tools, including secret identification, PII scanning, SAST, container scanning, and more. AquilaX is designed to integrate seamlessly into the development workflow, providing fast and accurate results by leveraging AI models trained on extensive datasets. The platform prioritizes developer experience by eliminating noise and false positives, making it a go-to choice for modern Secure-SDLC teams worldwide.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Rafay is an AI-powered platform that accelerates cloud-native and AI/ML initiatives for enterprises. It provides automation for Kubernetes clusters, cloud cost optimization, and AI workbenches as a service. Rafay enables platform teams to focus on innovation by automating self-service cloud infrastructure workflows.

Nebius AI is an AI-centric cloud platform designed to handle intensive workloads efficiently. It offers a range of advanced features to support various AI applications and projects. The platform ensures high performance and security for users, enabling them to leverage AI technology effectively in their work. With Nebius AI, users can access cutting-edge AI tools and resources to enhance their projects and streamline their workflows.

Operant is a cloud-native runtime protection platform that offers instant visibility and control from infrastructure to APIs. It provides AI security shield for applications, API threat protection, Kubernetes security, automatic microsegmentation, and DevSecOps solutions. Operant helps defend APIs, protect Kubernetes, and shield AI applications by detecting and blocking various attacks in real-time. It simplifies security for cloud-native environments with zero instrumentation, application code changes, or integrations.

Microsoft Azure is a cloud computing service that offers a wide range of products and services, including virtual machines, AI services, Kubernetes service, DevOps, SQL databases, and more. It provides solutions for cloud migration, data analytics, application development, and intelligent apps. Azure also offers resources for startups, learning materials, and community support. With a global infrastructure and a focus on AI innovation, Azure aims to help businesses optimize their infrastructure, innovate with data analytics, and future-proof their operations.

Mystic.ai is an AI tool designed to deploy and scale Machine Learning models with ease. It offers a fully managed Kubernetes platform that runs in your own cloud, allowing users to deploy ML models in their own Azure/AWS/GCP account or in a shared GPU cluster. Mystic.ai provides cost optimizations, fast inference, simpler developer experience, and performance optimizations to ensure high-performance AI model serving. With features like pay-as-you-go API, cloud integration with AWS/Azure/GCP, and a beautiful dashboard, Mystic.ai simplifies the deployment and management of ML models for data scientists and AI engineers.

Union.ai is an infrastructure platform designed for AI, ML, and data workloads. It offers a scalable MLOps platform that optimizes resources, reduces costs, and fosters collaboration among team members. Union.ai provides features such as declarative infrastructure, data lineage tracking, accelerated datasets, and more to streamline AI orchestration on Kubernetes. It aims to simplify the management of AI, ML, and data workflows in production environments by addressing complexities and offering cost-effective strategies.

Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.

PrimeOrbit is an AI-driven cloud cost optimization platform designed to empower operations and boost ROI for enterprises. The platform focuses on streamlining operations and simplifying cost management by delivering quality-centric solutions. It offers AI-driven optimization recommendations, automated cost allocation, and tailored FinOps for optimal efficiency and control. PrimeOrbit stands out by providing user-centric approach, superior AI recommendations, customization, and flexible enterprise workflow. It supports major cloud providers including AWS, Azure, and GCP, with full support for GCP and Kubernetes coming soon. The platform ensures complete cost allocation across cloud resources, empowering decision-makers to optimize cloud spending efficiently and effectively.

Koordinator is a QoS based scheduling system for hybrid orchestration workloads on Kubernetes. It aims to improve runtime efficiency and reliability of latency sensitive workloads and batch jobs, simplify resource-related configuration tuning, and increase pod deployment density. It enhances Kubernetes user experience by optimizing resource utilization, improving performance, providing flexible scheduling policies, and easy integration into existing clusters.

KubeSphere is a distributed operating system for cloud-native application management, using Kubernetes as its kernel. It provides a plug-and-play architecture, allowing third-party applications to be seamlessly integrated into its ecosystem. KubeSphere is also a multi-tenant container platform with full-stack automated IT operation and streamlined DevOps workflows. It provides developer-friendly wizard web UI, helping enterprises to build out a more robust and feature-rich platform, which includes most common functionalities needed for enterprise Kubernetes strategy.

K8sGPT is a tool for scanning your Kubernetes clusters, diagnosing, and triaging issues in simple English. It has SRE experience codified into its analyzers and helps to pull out the most relevant information to enrich it with AI.

k8m is an AI-driven Mini Kubernetes AI Dashboard lightweight console tool designed to simplify cluster management. It is built on AMIS and uses 'kom' as the Kubernetes API client. k8m has built-in Qwen2.5-Coder-7B model interaction capabilities and supports integration with your own private large models. Its key features include miniaturized design for easy deployment, user-friendly interface for intuitive operation, efficient performance with backend in Golang and frontend based on Baidu AMIS, pod file management for browsing, editing, uploading, downloading, and deleting files, pod runtime management for real-time log viewing, log downloading, and executing shell commands within pods, CRD management for automatic discovery and management of CRD resources, and intelligent translation and diagnosis based on ChatGPT for YAML property translation, Describe information interpretation, AI log diagnosis, and command recommendations, providing intelligent support for managing k8s. It is cross-platform compatible with Linux, macOS, and Windows, supporting multiple architectures like x86 and ARM for seamless operation. k8m's design philosophy is 'AI-driven, lightweight and efficient, simplifying complexity,' helping developers and operators quickly get started and easily manage Kubernetes clusters.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

Deploy langgenius/dify, an LLM based chat bot app on kubernetes with helm chart.

Flux All-In-One is a lightweight distribution optimized for running the GitOps Toolkit controllers as a single deployable unit on Kubernetes clusters. It is designed for bare clusters, edge clusters, clusters with restricted communication, clusters with egress via proxies, and serverless clusters. The distribution follows semver versioning and provides documentation for specifications, installation, upgrade, OCI sync configuration, Git sync configuration, and multi-tenancy configuration. Users can deploy Flux using Timoni CLI and a Timoni Bundle file, fine-tune installation options, sync from public Git repositories, bootstrap repositories, and uninstall Flux without affecting reconciled workloads.

Runbooks is a repository that is no longer active. The project has been deprecated in favor of KubeAI, a platform designed to simplify the operationalization of AI on Kubernetes. For more information, please refer to the new repository at https://github.com/substratusai/kubeai.

Robusta is a tool designed to enhance Prometheus notifications for Kubernetes environments. It offers features such as smart grouping to reduce notification spam, AI investigation for alert analysis, alert enrichment with additional data like pod logs, self-healing capabilities for defining auto-remediation rules, advanced routing options, problem detection without PromQL, change-tracking for Kubernetes resources, auto-resolve functionality, and integration with various external systems like Slack, Teams, and Jira. Users can utilize Robusta with or without Prometheus, and it can be installed alongside existing Prometheus setups or as part of an all-in-one Kubernetes observability stack.

Omnia is a deployment tool designed to turn servers with RPM-based Linux images into functioning Slurm/Kubernetes clusters. It provides an Ansible playbook-based deployment for Slurm and Kubernetes on servers running an RPM-based Linux OS. The tool simplifies the process of setting up and managing clusters, making it easier for users to deploy and maintain their infrastructure.

Helios is a powerful open-source tool for managing and monitoring your Kubernetes clusters. It provides a user-friendly interface to easily visualize and control your cluster resources, including pods, deployments, services, and more. With Helios, you can efficiently manage your containerized applications and ensure high availability and performance of your Kubernetes infrastructure.

AIStore on Kubernetes is a toolkit for deploying a lightweight, scalable object storage solution designed for AI applications in a Kubernetes environment. It includes documentation, Ansible playbooks, Kubernetes operator, Helm charts, and Terraform definitions for deployment on public cloud platforms. The system overview shows deployment across nodes with proxy and target pods utilizing Persistent Volumes. The AIStore Operator automates cluster management tasks. The repository focuses on production deployments but offers different deployment options. Thorough planning and configuration decisions are essential for successful multi-node deployment. The AIStore Operator simplifies tasks like starting, deploying, adjusting size, and updating AIStore resources within Kubernetes.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

AzureOpenAI-with-APIM is a repository that provides a one-button deploy solution for Azure API Management (APIM), Key Vault, and Log Analytics to work seamlessly with Azure OpenAI endpoints. It enables organizations to scale and manage their Azure OpenAI service efficiently by issuing subscription keys via APIM, delivering usage metrics, and implementing policies for access control and cost management. The repository offers detailed guidance on implementing APIM to enhance Azure OpenAI resiliency, scalability, performance, monitoring, and chargeback capabilities.

OpenOrch is a daemon that transforms servers into a powerful development environment, running AI models, containers, and microservices. It serves as a blend of Kubernetes and a language-agnostic backend framework for building applications on fixed-resource setups. Users can deploy AI models and build microservices, managing applications while retaining control over infrastructure and data.

Airbroke is an open-source error catcher tool designed for modern web applications. It provides a PostgreSQL-based backend with an Airbrake-compatible HTTP collector endpoint and a React-based frontend for error management. The tool focuses on simplicity, maintaining a small database footprint even under heavy data ingestion. Users can ask AI about issues, replay HTTP exceptions, and save/manage bookmarks for important occurrences. Airbroke supports multiple OAuth providers for secure user authentication and offers occurrence charts for better insights into error occurrences. The tool can be deployed in various ways, including building from source, using Docker images, deploying on Vercel, Render.com, Kubernetes with Helm, or Docker Compose. It requires Node.js, PostgreSQL, and specific system resources for deployment.

ClearML Fractional GPU is a tool designed to optimize GPU resource utilization by allowing multiple containers to run on the same GPU with driver-level memory limitation and compute time-slicing. It supports CUDA 11.x & CUDA 12.x, preventing greedy processes from grabbing the entire GPU memory. The tool offers options like Dynamic GPU Slicing, Container-based Memory Limits, and Kubernetes-based Static MIG Slicing to enhance hardware utilization and workload performance for AI development.

AutoPilot Observability (APO) is an out-of-the-box observability platform that provides one-click installation and ready-to-use capabilities. APO's OneAgent supports one-click configuration-free installation of Tracing probes, collects application fault scene logs, infrastructure metrics, network metrics of applications and downstream dependencies, and Kubernetes events. It supports collecting causality metrics based on eBPF implementation. APO integrates OpenTelemetry probes, otel-collector, Jaeger, ClickHouse, and VictoriaMetrics, reducing user configuration work. APO innovatively integrates eBPF technology with the OpenTelemetry ecosystem, significantly reducing data storage volume. It offers guided troubleshooting using eBPF technology to assist users in pinpointing fault causes on a single page.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted WebUI designed to operate entirely offline. It supports various LLM runners, including Ollama and OpenAI-compatible APIs. For more information, be sure to check out our Open WebUI Documentation.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

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