Best AI tools for< Automate Devops Tasks >

Kindo is an AI-powered platform designed for DevSecOps teams to automate tasks, write doctrine, and orchestrate infrastructure responses. It offers AI-powered Runbook automations to streamline workflows, automate tedious tasks, and enhance security controls. Kindo enables users to offload time-consuming tasks to AI Agents, prioritize critical tasks, and monitor AI-related activities for compliance and informed decision-making. The platform provides a comprehensive vantage point for modern infrastructure defense and instrumentation, allowing users to create repeatable processes, automate vulnerability assessment and remediation, and secure multi-cloud IAM configurations.

Kubiya is an AI-powered platform designed to reduce Time-To-Automation for Developer and Infrastructure Operations teams. It allows users to focus on high-impact work by automating routine tasks and processes, powered by an Agentic-Native Platform. Kubiya is trusted by world-class engineering and operations teams, offering features such as AI teammates, JIT Permissions, Infrastructure Provisioning, Help Desk support, and Incident Response automation.

Gitya is an AI-powered GitHub assistant designed to streamline your GitHub workflow by automating minor tasks and enhancing productivity. With features like GitHub App integration, AI-enhanced automation, PR management, and ticket automation, Gitya aims to help users spend less time on busywork and more time on high-impact engineering tasks. Users have praised Gitya for its ability to reduce time spent on bug fixes and PR management, ultimately leading to increased project efficiency and success.

Patched is an open-source workflow automation framework designed for development teams to build AI workflows that automate code reviews, documentation, and patches. It offers ready-to-go patchflows or the ability to create custom ones to accelerate mundane development tasks. Patched integrates seamlessly with popular platforms like Gitlab, GitHub, Jira, and more, allowing users to improve code quality, fix bugs, and create tickets efficiently. The application is privacy-focused, allowing users to deploy it within their own infrastructure for complete privacy. Patched is free and open-source, offering customization options via code or a no-code builder.

Tracecat is an open-source security automation platform that helps you automate security alerts, build AI-assisted workflows, orchestrate alerts, and close cases fast. It is a Tines / Splunk SOAR alternative that is built for builders and allows you to experiment for free. You can deploy Tracecat on your own infrastructure or use Tracecat Cloud with no maintenance overhead. Tracecat is Apache-2.0 licensed, which means it is open vision, open community, and open development. You can have your say in the future of security automation. Tracecat is no-code first, but you can also code as well. You can build automations fast with no-code and customize without vendor lock-in using Python. Tracecat has a click-and-drag workflow builder that allows you to automate SecOps using pre-built actions (API calls, webhooks, data transforms, AI tasks, and more) combined into workflows. No code is required. Tracecat also has a built-in case management system that allows you to open cases directly from workflows and track and manage security incidents all in one platform.

DATAFOREST is an AI-powered data engineering company that offers a wide range of services including generative AI, data science, web and mobile development, DevOps, cloud solutions, digital transformation, and more. They provide custom data-driven solutions for small and medium-sized businesses, focusing on efficiency improvement, revenue growth, and cost reduction. With over 15 years of experience, DATAFOREST helps businesses automate complex tasks, enhance decision-making, boost productivity, and streamline operations through AI and machine learning technologies.

Maige is an open-source infrastructure designed to run natural language workflows on your codebase. It allows users to connect their repository, define rules for handling issues and pull requests, and monitor the workflow execution through a dashboard. Maige leverages AI capabilities to label, assign, comment, review code, and execute simple code snippets, all while being customizable and flexible with the GitHub API.

CommandAI is a powerful command line utility tool that leverages the capabilities of artificial intelligence to enhance user experience and productivity. It allows users to interact with the command line interface using natural language commands, making it easier for both beginners and experienced users to perform complex tasks efficiently. With CommandAI, users can streamline their workflow, automate repetitive tasks, and access advanced features through simple text-based interactions. The tool is designed to simplify the command line experience and provide intelligent assistance to users in executing commands and managing their system effectively.

La Terminal is a fully-native, first-class touch experience for command-line hackers on iPhone and iPad. It provides a secure, open-source, and feature-rich environment for managing remote servers, automating tasks, and exploring the command line. With AI assistance from El Copiloto, La Terminal makes it easy to find and execute commands, even for beginners.

Start Left® Security is an AI-driven application security posture management platform that empowers product teams to automate secure-by-design software from people to cloud. The platform integrates security into every facet of the organization, offering a unified solution that aligns with business goals, fosters continuous improvement, and drives innovation. Start Left® Security provides a gamified DevSecOps experience with comprehensive security capabilities like SCA, SBOM, SAST, DAST, Container Security, IaC security, ASPM, and more.

Bash Senpai is a terminal assistant powered by ChatGPT that transforms instructions into ready-to-use commands. It provides convenience by allowing users to get answers without leaving the terminal and offers better answers by providing context with questions. The tool also incorporates self-reflection to improve the quality of its responses.

Qodo is a quality-first generative AI coding platform that helps developers write, test, and review code within IDE and Git. The platform offers automated code reviews, contextual suggestions, and comprehensive test generation, ensuring robust, reliable software development. Qodo integrates seamlessly to maintain high standards of code quality and integrity throughout the development process.

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.

CodePal is a comprehensive platform that offers a range of coding helpers and tools to assist developers. It includes AI-powered code generators that can translate plain words into computer code, helping users automate tasks, improve code quality, and enhance productivity. CodePal supports various programming languages and technologies, making it a versatile tool for developers of all levels.

Fine is an AI-powered software development tool that automates mundane and complex tasks, allowing developers to focus on driving innovation. Its AI agents integrate seamlessly into your team and toolset, transforming your development workflow by automating tasks such as transforming Jira tickets into pull requests, streamlining code reviews, and simplifying migrations.

DevOps Security Platform is an AI-native security tool designed to automate security requirements definition, enforcement, risk assessments, and compliance assessments. It helps companies secure their applications by identifying risks at the beginning of the Software Development Lifecycle and enforcing them before go-live. The platform offers innovative features, AI-generated questionnaires, and the ability to customize, automate, and integrate security processes. DevOps Security Platform aims to empower security champions and prevent security vulnerabilities in applications and DevOps environments.

Hoop.dev is an AI-powered application that provides live data masking in Rails console sessions. It offers shielded Rails console access, automated employee onboarding and off-boarding, and AI data masking to protect sensitive information. The application allows for passwordless authentication via Google SSO with MFA, auditability of console operations, and compliance with various security controls and regulations. Hoop.dev aims to streamline Rails console operations, reduce manual workflows, and enhance security measures for user convenience and data protection.

Pulumi is an AI-powered infrastructure as code tool that allows engineers to manage cloud infrastructure using various programming languages like Node.js, Python, Go, .NET, Java, and YAML. It offers features such as generative AI-powered cloud management, security enforcement through policies, automated deployment workflows, asset management, compliance remediation, and AI insights over the cloud. Pulumi helps teams provision, automate, and evolve cloud infrastructure, centralize and secure secrets management, and gain security, compliance, and cost insights across all cloud assets.

n8n is a powerful workflow automation software and tool that offers advanced AI capabilities. It is a popular platform for technical teams to automate workflows, integrate various services, and build autonomous agents. With over 400 integrations, n8n enables users to save time, streamline operations, and enhance security through AI-powered solutions. The tool supports self-hosting, external libraries, and a user-friendly interface for both coding and non-coding users.

Goast.ai is an AI assistant designed to help engineering teams resolve errors and exceptions faster by automatically analyzing and fixing issues from error logs. It offers real-time bug fixes, root cause analysis, and automated bug fixing processes, ultimately saving time and improving productivity for development teams. Goast integrates with popular observability tools, supports various frameworks and languages, and provides a user-friendly interface for seamless collaboration and feedback.

DevOpsGPT is a revolutionary tool designed to streamline your workflow and empower you to build systems and automate tasks with ease. Tired of spending hours on repetitive DevOps tasks? DevOpsGPT is here to help! Whether you're setting up infrastructure, speeding up deployments, or tackling any other DevOps challenge, our app can make your life easier and more productive. With DevOpsGPT, you can expect faster task completion, simplified workflows, and increased efficiency. Ready to experience the DevOpsGPT difference? Visit our website, sign in or create an account, start exploring the features, and share your feedback to help us improve. DevOpsGPT will become an essential tool in your DevOps toolkit.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

DevOpsGPT is an AI-driven software development automation solution that combines Large Language Models (LLM) with DevOps tools to convert natural language requirements into working software. It improves development efficiency by eliminating the need for tedious requirement documentation, shortens development cycles, reduces communication costs, and ensures high-quality deliverables. The Enterprise Edition offers features like existing project analysis, professional model selection, and support for more DevOps platforms. The tool automates requirement development, generates interface documentation, provides pseudocode based on existing projects, facilitates code refinement, enables continuous integration, and supports software version release. Users can run DevOpsGPT with source code or Docker, and the tool comes with limitations in precise documentation generation and understanding existing project code. The product roadmap includes accurate requirement decomposition, rapid import of development requirements, and integration of more software engineering and professional tools for efficient software development tasks under AI planning and execution.

SuperCoder is an open-source autonomous software development system that leverages advanced AI tools and agents to streamline and automate coding, testing, and deployment tasks, enhancing efficiency and reliability. It supports a variety of languages and frameworks for diverse development needs. Users can set up the environment variables, build and run the Go server, Asynq worker, and Postgres using Docker and Docker Compose. The project is under active development and may still have issues, but users can seek help and support from the Discord community or by creating new issues on GitHub.

Ragna is a RAG orchestration framework designed for managing workflows and orchestrating tasks. It provides a comprehensive set of features for users to streamline their processes and automate repetitive tasks. With Ragna, users can easily create, schedule, and monitor workflows, making it an ideal tool for teams and individuals looking to improve their productivity and efficiency. The framework offers extensive documentation, community support, and a user-friendly interface, making it accessible to users of all skill levels. Whether you are a developer, data scientist, or project manager, Ragna can help you simplify your workflow management and boost your overall performance.

PatchWork is an open-source framework designed for automating development tasks using large language models. It enables users to automate workflows such as PR reviews, bug fixing, security patching, and more through a self-hosted CLI agent and preferred LLMs. The framework consists of reusable atomic actions called Steps, customizable LLM prompts known as Prompt Templates, and LLM-assisted automations called Patchflows. Users can run Patchflows locally in their CLI/IDE or as part of CI/CD pipelines. PatchWork offers predefined patchflows like AutoFix, PRReview, GenerateREADME, DependencyUpgrade, and ResolveIssue, with the flexibility to create custom patchflows. Prompt templates are used to pass queries to LLMs and can be customized. Contributions to new patchflows, steps, and the core framework are encouraged, with chat assistants available to aid in the process. The roadmap includes expanding the patchflow library, introducing a debugger and validation module, supporting large-scale code embeddings, parallelization, fine-tuned models, and an open-source GUI. PatchWork is licensed under AGPL-3.0 terms, while custom patchflows and steps can be shared using the Apache-2.0 licensed patchwork template repository.

Tegon is an open-source AI-First issue tracking tool designed for engineering teams. It aims to simplify task management by leveraging AI and integrations to automate task creation, prioritize tasks, and enhance bug resolution. Tegon offers features like issues tracking, automatic title generation, AI-generated labels and assignees, custom views, and upcoming features like sprints and task prioritization. It integrates with GitHub, Slack, and Sentry to streamline issue tracking processes. Tegon also plans to introduce AI Agents like PR Agent and Bug Agent to enhance product management and bug resolution. Contributions are welcome, and the product is licensed under the MIT License.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

Inferable is an open source platform that helps users build reliable LLM-powered agentic automations at scale. It offers a managed agent runtime, durable tool calling, zero network configuration, multiple language support, and is fully open source under the MIT license. Users can define functions, register them with Inferable, and create runs that utilize these functions to automate tasks. The platform supports Node.js/TypeScript, Go, .NET, and React, and provides SDKs, core services, and bootstrap templates for various languages.

PR Pilot is an AI-powered tool designed to assist users in their daily workflow by delegating routine work to AI with confidence and predictability. It integrates seamlessly with popular development tools and allows users to interact with it through a Command-Line Interface, Python SDK, REST API, and Smart Workflows. Users can automate tasks such as generating PR titles and descriptions, summarizing and posting issues, and formatting README files. The tool aims to save time and enhance productivity by providing AI-powered solutions for common development tasks.

CoolCline is a proactive programming assistant that combines the best features of Cline, Roo Code, and Bao Cline. It seamlessly collaborates with your command line interface and editor, providing the most powerful AI development experience. It optimizes queries, allows quick switching of LLM Providers, and offers auto-approve options for actions. Users can configure LLM Providers, select different chat modes, perform file and editor operations, integrate with the command line, automate browser tasks, and extend capabilities through the Model Context Protocol (MCP). Context mentions help provide explicit context, and installation is easy through the editor's extension panel or by dragging and dropping the `.vsix` file. Local setup and development instructions are available for contributors.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

Awesome AI-Powered Developer Tools is a curated list of AI-powered developer tools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and more. The repository includes a wide range of tools, from IDEs and Git clients to assistants, agents, app generators, UI generators, snippet generators, documentation tools, code generation tools, agent platforms, OpenAI plugins, search tools, and testing tools. These tools are designed to enhance developer productivity and streamline various development tasks by integrating AI capabilities.

GenAIScript is a scripting environment designed to facilitate file ingestion, prompt development, and structured data extraction. Users can define metadata and model configurations, specify data sources, and define tasks to extract specific information. The tool provides a convenient way to analyze files and extract desired content in a structured format. It offers a user-friendly interface for working with data and automating data extraction processes, making it suitable for various data processing tasks.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Hercules is the world’s first open-source testing agent designed to handle the toughest testing tasks for modern web applications. It turns simple Gherkin steps into fully automated end-to-end tests, making testing simple, reliable, and efficient. Hercules adapts to various platforms like Salesforce and is suitable for CI/CD pipelines. It aims to democratize and disrupt test automation, making top-tier testing accessible to everyone. The tool is transparent, reliable, and community-driven, empowering teams to deliver better software. Hercules offers multiple ways to get started, including using PyPI package, Docker, or building and running from source code. It supports various AI models, provides detailed installation and usage instructions, and integrates with Nuclei for security testing and WCAG for accessibility testing. The tool is production-ready, open core, and open source, with plans for enhanced LLM support, advanced tooling, improved DOM distillation, community contributions, extensive documentation, and a bounty program.

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.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Here we will keep track of the AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. 🔥 * Tool (AI LLM) * Game (Agent) * Code * Framework * Writer * Image * Texture * Shader * 3D Model * Avatar * Animation * Video * Audio * Music * Singing Voice * Speech * Analytics * Video Tool

BashEmulator GPT: A Virtualized Bash Environment for Linux Command Line Interaction. It virtualized all network interfaces and local network

Advanced DevOps Guru with Linux distro and cloud-native tech expertise.

DevOps and Python mentor, explores the internet for you!

Your Personal Cloud DevOps Mentor

I'm Alice, your go-to guide for DevOps fun and detailed coding solutions!

Open Source Prompt: https://github.com/mleoca/Bash-Scripting-GPT

Your personal Jenkins assistant and code generator with a focus on responsive, efficient, and scalable automations.

コード例示のシェルスクリプトGPT

stunspot's Shell Scripter Extrordinaire!

Expert in shell scripting, offering guidance, best practices, and solutions.

Creates full bash scripts for web apps with user guidance.

Expert in Windows PowerShell and scripting guidance.

A GPT Agent that connects to your server via SSH

Assists in enhancing StackStorm packs with new actions and features.

Safety-aware, example-rich zsh guide.

Expert in bash, zsh, PowerShell commands

Assistant for kubernetes environments managed by gitops

Learn Linux by Hands-on Labs and AI

Guides from Terraform install to script deployment.

Adaptive and clear Bash guide with command execution. Learn by poking around in the code interpreter's isolated Kubernetes container!