Best AI tools for< Infrastructure Engineer >

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.

vHive is an autonomous digital twin software that enables users to create a digitized portfolio of global enterprise assets. The platform offers advanced AI analytics and insights to maximize revenue and facilitate exponential growth. With vHive, users can improve operational efficiency, rapidly digitize assets worldwide, ensure security and compliance, and scale their asset portfolio through end-to-end automation. Trusted by leading enterprises, vHive provides a user-friendly platform for collecting data and insights across various use cases, ultimately driving organizational efficiency and innovation.

Engine is an AI software engineer tool designed for teams to streamline software development processes. It connects to popular project management tools like Jira, Trello, Linear, and more, automating tasks such as turning tickets into pull requests. Engine can complete up to 50% of tickets in minutes without supervision, helping teams ship faster and keep backlogs under control. It works seamlessly with existing workflows and tools, providing AI-powered engineering support to improve productivity and efficiency.

Anyscale is a company that provides a scalable compute platform for AI and Python applications. Their platform includes a serverless API for serving and fine-tuning open LLMs, a private cloud solution for data privacy and governance, and an open source framework for training, batch, and real-time workloads. Anyscale's platform is used by companies such as OpenAI, Uber, and Spotify to power their AI workloads.

Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

OmniAI is an AI tool that allows teams to deploy AI applications on their existing infrastructure. It provides a unified API experience for building AI applications and offers a wide selection of industry-leading models. With tools like Llama 3, Claude 3, Mistral Large, and AWS Titan, OmniAI excels in tasks such as natural language understanding, generation, safety, ethical behavior, and context retention. It also enables users to deploy and query the latest AI models quickly and easily within their virtual private cloud environment.

Inkdrop is an AI-powered tool that helps users visualize their cloud infrastructure by automatically generating interactive diagrams of cloud resources and dependencies. It provides a comprehensive overview of infrastructure, aids in understanding complex resource relationships, and seamlessly integrates with CI pipeline for documentation updates.

The DARPA's Artificial Intelligence Cyber Challenge (AIxCC) is an AI-driven cybersecurity tool developed in collaboration with ARPA-H and various industry experts like Anthropic, Google, Microsoft, OpenAI, and others. It aims to safeguard critical software infrastructure by utilizing AI technology to enhance cybersecurity measures. The tool provides a platform for experts in AI and cybersecurity to come together and address the evolving threats in the digital landscape.

Trieve is an AI-first infrastructure API that offers search, recommendations, and RAG capabilities by combining language models with tools for fine-tuning ranking and relevance. It provides features such as semantic vector search, BM25 & SPLADE full-text search, hybrid search, merchandising & relevance tuning, and sub-sentence highlighting. Trieve helps companies build unfair competitive advantages through their search, discovery, and RAG experiences. The platform is built on the best foundations, offering private open-source models, self-hostable options, and easy integration with existing data. With Trieve, users can set up industry-leading search in just 30 minutes and take control of their discovery process.

DataRobot is a leading provider of AI cloud platforms. It offers a range of AI tools and services to help businesses build, deploy, and manage AI models. DataRobot's platform is designed to make AI accessible to businesses of all sizes, regardless of their level of AI expertise. DataRobot's platform includes a variety of features to help businesses build and deploy AI models, including: * A drag-and-drop interface that makes it easy to build AI models, even for users with no coding experience. * A library of pre-built AI models that can be used to solve common business problems. * A set of tools to help businesses monitor and manage their AI models. * A team of AI experts who can provide support and guidance to businesses using the platform.

GooseAI is a fully managed NLP-as-a-Service delivered via API, at 30% the cost of other providers. It offers a variety of NLP models, including GPT-Neo 1.3B, Fairseq 1.3B, GPT-J 6B, Fairseq 6B, Fairseq 13B, and GPT-NeoX 20B. GooseAI is easy to use, with feature parity with industry standard APIs. It is also highly performant, with the industry's fastest generation speeds.

SignalWire is a cloud communications platform that provides a suite of APIs and tools for building voice, messaging, and video applications. With SignalWire, developers can quickly and easily create AI-powered applications without extensive coding. SignalWire's platform is designed to be scalable, reliable, and easy to use, making it a great choice for businesses of all sizes.

Granica AI is an AI Data Readiness Platform that helps users build and manage high-quality data for AI at scale. The platform uses AI to continuously improve the AI-readiness of data, making projects faster and more impactful over time. Granica offers solutions for data cost optimization, data privacy, data selection & curation, and research. The platform is trusted by category-defining companies and has been recognized in various industry awards and publications.

Teleport is a modern access platform for infrastructure that provides on-demand, least privileged access with a focus on cryptographic identity and zero trust security. It simplifies zero trust security for AWS and offers solutions for improving engineer productivity, protecting infrastructure, meeting compliance requirements, and modernizing privileged access management. Teleport is trusted by market leaders and offers more than 170 integrations for accessing clouds, data centers, and various resources.

Palo Alto Networks is a cybersecurity company offering advanced security solutions powered by Precision AI to protect modern enterprises from cyber threats. The company provides network security, cloud security, and AI-driven security operations to defend against AI-generated threats in real time. Palo Alto Networks aims to simplify security and achieve better security outcomes through platformization, intelligence-driven expertise, and proactive monitoring of sophisticated threats.

Seventh Sense is an AI company focused on providing cutting-edge AI solutions for secure and private identity verification. Their innovative technologies, such as SenseCrypt, OpenCV FR, and SenseVantage, offer advanced biometric verification, face recognition, and AI video analysis. With a mission to make self-sovereign identity accessible to all, Seventh Sense ensures privacy, security, and compliance through their AI algorithms and cryptographic solutions.

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.

LogicMonitor is a cloud-based infrastructure monitoring platform that provides real-time insights and automation for comprehensive, seamless monitoring with agentless architecture. It offers a unified platform for monitoring infrastructure, applications, and business services, with advanced features for hybrid observability. LogicMonitor's AI-driven capabilities simplify complex IT ecosystems, accelerate incident response, and empower organizations to thrive in the digital landscape.

Asaria Industries is an AI application that focuses on building intelligent systems to transform industries. They offer system architecture and AI integration services to help modernize enterprise infrastructure and implement intelligent decision systems. With expertise in engineering scalable foundations for complex systems, Asaria Industries aims to turn visions into reality through innovative solutions.

llm-resource is a comprehensive collection of high-quality resources for Large Language Models (LLM). It covers various aspects of LLM including algorithms, training, fine-tuning, alignment, inference, data engineering, compression, evaluation, prompt engineering, AI frameworks, AI basics, AI infrastructure, AI compilers, LLM application development, LLM operations, AI systems, and practical implementations. The repository aims to gather and share valuable resources related to LLM for the community to benefit from.

AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.

Awesome_GPT_Super_Prompting is a repository that provides resources related to Jailbreaks, Leaks, Injections, Libraries, Attack, Defense, and Prompt Engineering. It includes information on ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, and Adversarial Machine Learning. The repository contains curated lists of repositories, tools, and resources related to GPTs, prompt engineering, prompt libraries, and secure prompting. It also offers insights into Cyber-Albsecop GPT Agents and Super Prompts for custom GPT usage.

AIAC is a library and command line tool to generate Infrastructure as Code (IaC) templates, configurations, utilities, queries, and more via LLM providers such as OpenAI, Amazon Bedrock, and Ollama. Users can define multiple 'backends' targeting different LLM providers and environments using a simple configuration file. The tool allows users to ask a model to generate templates for different scenarios and composes an appropriate request to the selected provider, storing the resulting code to a file and/or printing it to standard output.

AIBrix is an open-source initiative providing essential building blocks for scalable GenAI inference infrastructure. It delivers a cloud-native solution optimized for deploying, managing, and scaling large language model (LLM) inference, tailored to enterprise needs. Key features include High-Density LoRA Management, LLM Gateway and Routing, LLM App-Tailored Autoscaler, Unified AI Runtime, Distributed Inference, Distributed KV Cache, Cost-efficient Heterogeneous Serving, and GPU Hardware Failure Detection.

AIOps Modules is a collection of reusable Infrastructure as Code (IAC) modules that work with SeedFarmer CLI. The modules are decoupled and can be aggregated using GitOps principles to achieve desired use cases, removing heavy lifting for end users. They must be generic for reuse in Machine Learning and Foundation Model Operations domain, adhering to SeedFarmer Guide structure. The repository includes deployment steps, project manifests, and various modules for SageMaker, Mlflow, FMOps/LLMOps, MWAA, Step Functions, EKS, and example use cases. It also supports Industry Data Framework (IDF) and Autonomous Driving Data Framework (ADDF) Modules.

AIInfra is an open-source project focused on AI infrastructure, specifically targeting large models in distributed clusters, distributed architecture, distributed training, and algorithms related to large models. The project aims to explore and study system design in artificial intelligence and deep learning, with a focus on the hardware and software stack for building AI large model systems. It provides a comprehensive curriculum covering topics such as AI chip principles, communication and storage, AI clusters, large model training, and inference, as well as algorithms for large models. The course is designed for undergraduate and graduate students, as well as professionals working with AI large model systems, to gain a deep understanding of AI computer system architecture and design.

Well-Architected Infrastructure as Code (IaC) Analyzer is a project demonstrating how generative AI can evaluate infrastructure code for alignment with best practices. It features a modern web application allowing users to upload IaC documents, complete IaC projects, or architecture diagrams for assessment. The tool provides insights into infrastructure code alignment with AWS best practices, offers suggestions for improving cloud architecture designs, and can generate IaC templates from architecture diagrams. Users can analyze CloudFormation, Terraform, or AWS CDK templates, architecture diagrams in PNG or JPEG format, and complete IaC projects with supporting documents. Real-time analysis against Well-Architected best practices, integration with AWS Well-Architected Tool, and export of analysis results and recommendations are included.

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.

Terraform Provider for CAST AI is a tool that allows users to manage their CAST AI resources using Terraform. It provides a seamless integration between Terraform and CAST AI platform, enabling users to define and manage their infrastructure as code. The provider supports various features such as setting up cluster configurations, managing node templates, and configuring autoscaler policies. Users can easily install the provider, pass API keys, and leverage the provider's functionalities to automate the deployment and management of their CAST AI resources.

ChatOpsLLM is a project designed to empower chatbots with effortless DevOps capabilities. It provides an intuitive interface and streamlined workflows for managing and scaling language models. The project incorporates robust MLOps practices, including CI/CD pipelines with Jenkins and Ansible, monitoring with Prometheus and Grafana, and centralized logging with the ELK stack. Developers can find detailed documentation and instructions on the project's website.

Jina is a tool that allows users to build multimodal AI services and pipelines using cloud-native technologies. It provides a Pythonic experience for serving ML models and transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Users can build and serve models for any data type and deep learning framework, design high-performance services with easy scaling, serve LLM models while streaming their output, integrate with Docker containers via Executor Hub, and host on CPU/GPU using Jina AI Cloud. Jina also offers advanced orchestration and scaling capabilities, a smooth transition to the cloud, and easy scalability and concurrency features for applications. Users can deploy to their own cloud or system with Kubernetes and Docker Compose integration, and even deploy to JCloud for autoscaling and monitoring.

This repository is a collection of free resources and a roadmap designed to help individuals learn Machine Learning and Artificial Intelligence concepts by providing key concepts, building blocks, roles, a learning roadmap, courses, certifications, books, tools & frameworks, research blogs, applied blogs, practice problems, communities, YouTube channels, newsletters, and must-read papers. It covers a wide range of topics from supervised learning to MLOps, offering guidance on learning paths, practical experience, and job interview preparation.

Paddler is an open-source load balancer and reverse proxy designed specifically for optimizing servers running llama.cpp. It overcomes typical load balancing challenges by maintaining a stateful load balancer that is aware of each server's available slots, ensuring efficient request distribution. Paddler also supports dynamic addition or removal of servers, enabling integration with autoscaling tools.

AITemplate (AIT) is a Python framework that transforms deep neural networks into CUDA (NVIDIA GPU) / HIP (AMD GPU) C++ code for lightning-fast inference serving. It offers high performance close to roofline fp16 TensorCore (NVIDIA GPU) / MatrixCore (AMD GPU) performance on major models. AITemplate is unified, open, and flexible, supporting a comprehensive range of fusions for both GPU platforms. It provides excellent backward capability, horizontal fusion, vertical fusion, memory fusion, and works with or without PyTorch. FX2AIT is a tool that converts PyTorch models into AIT for fast inference serving, offering easy conversion and expanded support for models with unsupported operators.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

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.

Olah is a self-hosted lightweight Huggingface mirror service that implements mirroring feature for Huggingface resources at file block level, enhancing download speeds and saving bandwidth. It offers cache control policies and allows administrators to configure accessible repositories. Users can install Olah with pip or from source, set up the mirror site, and download models and datasets using huggingface-cli. Olah provides additional configurations through a configuration file for basic setup and accessibility restrictions. Future work includes implementing an administrator and user system, OOS backend support, and mirror update schedule task. Olah is released under the MIT License.

DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

Cloud engineer expert in Terraform for AWS/GCP infrastructures.

Develops, advises and optimizes infrastructure-as-code practices across the organization.

Expert in GPT infrastructure and network systems.

Expert in Linux, DevOps, and Infrastructure as Code

Guides from Terraform install to script deployment.

Introducing IAC Code Guardian: Your Trusted IaC Security Expert in Scanning Opentofu, Terrform, AWS Cloudformation, Pulumi, K8s Yaml & Dockerfile

Advises on geotechnical engineering to enhance infrastructure stability and longevity.

Advises on water resources management and infrastructure development.

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Create UML for flowcharts, Class, Sequence, Use Case, and Activity diagrams using PlantUML. System design and cloud infrastructure diagrams for AWS, Azue and GCP. No login required.

Guides in data engineering tasks with a focus on practical solutions.

Expert in cloud computing, offering insights on services, security, and infrastructure.

Architext is a sophisticated chatbot designed to guide users through the complexities of AWS architecture, leveraging the AWS Well-Architected Framework. It offers real-time, tailored advice, interactive learning, and up-to-date resources for both novices and experts in AWS cloud infrastructure.

Cloud Engineer Expert, guiding in cloud tech, projects, career, and industry trends.

An expert MLOps engineer assisting in DevOps and pipeline optimization.

Senior Java software engineer and cloud expert

Senior DevOps Engineer specializing in Ansible

Expert in CI/CD pipeline configurations and DevOps best practices.

French Linux devops expert aiding in productivity.