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.

Teleport is a modern access platform for infrastructure that provides on-demand, least privileged access with cryptographic identity and zero trust. It offers solutions for improving engineer productivity, protecting infrastructure, meeting compliance requirements, and preventing identity provider compromise. Teleport is trusted by market leaders for its secure and efficient access management capabilities.

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 the infrastructure to speed up onboarding and understand complex resource relationships for effective troubleshooting. With seamless integration, users can effortlessly update documentation via CI pipeline integration. Meet the founders Antoine Descamps, Cofounder and CEO, and Alberto Schillaci, Cofounder and CTO. Inkdrop is trusted by partners who believe in its mission.

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.

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 a Training Data Platform designed to make data safe for use with AI while keeping it cost-efficient. It offers state-of-the-art accuracy, cost-efficient data optimization, data visibility insights, and cloud cost savings. The platform helps in protecting data privacy, optimizing data costs, and gaining data visibility for AI teams to achieve big results while minimizing privacy risk.

Pulumi is an AI-powered infrastructure as code platform that allows engineers to manage cloud infrastructure using various programming languages like Node.js, Python, Go, .NET, Java, and YAML. It offers capabilities such as generative AI-powered cloud management, security enforcement through policies, and automated deployment workflows. Pulumi Insights enables faster infrastructure code authoring through AI, while Pulumi Cloud provides managed services for infrastructure as code and secrets management. The platform is praised for its ease of use, developer experience, and ability to centralize and secure secrets management.

unSkript is an AI-powered infrastructure health intelligence tool designed to ensure the health of your application infrastructure. It uses Generative AI and Intelligent Health Checks to proactively find, diagnose, and fix issues in your application infrastructure. With features like Proactive Health Checks, Generative AI based RCA, and Continuous Learning, unSkript helps streamline processes for cloud-operations teams and software teams. By leveraging AI technology, unSkript aims to minimize downtime, deliver real-time troubleshooting, and allow users to focus on strategic tasks.

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.

Evervault provides developers with world-class infrastructure to solve complex data security and compliance problems in days, not months. It offers four simple primitives: Relay, Functions, UI Components, and Enclaves. These primitives can be used to build a variety of data security and compliance solutions, such as PCI DSS compliance, HIPAA compliance, and GDPR compliance. Evervault is secure by default, fundamentally configurable, and ultra-low latency. It is also compliant with PCI DSS, HIPAA, GDPR, and SOC2.

Algolia is an AI-powered search engine that helps businesses improve the customer experience on their websites and apps. It offers a range of features, including AI-powered search, AI-powered recommendations, and merchandising studio. Algolia is used by over 17,000 customers across 150+ countries, including The Times, LTK, Swedol, Hershey's, and Shoe Carnival.

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 wide range of features including infrastructure monitoring, network monitoring, server monitoring, remote monitoring, virtual machine monitoring, SD-WAN monitoring, database monitoring, storage monitoring, configuration monitoring, cloud monitoring, container monitoring, AWS Monitoring, GCP Monitoring, Azure Monitoring, digital experience SaaS monitoring, website monitoring, APM, AIOPS, Dexda Integrations, security dashboards, and platform demo logs. LogicMonitor's AI-driven hybrid observability helps organizations simplify complex IT ecosystems, accelerate incident response, and thrive in the digital landscape.

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.

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.

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.

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.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

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.

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.

This repository contains a Docker image with ZeroTier One and ztncui to set up a standalone ZeroTier network controller with a web user interface. It provides features like Golang auto-mkworld for generating a planet file, supports local persistent storage configuration, and includes a public file server. Users can build the Docker image, set up the container with specific environment variables, and manage the ZeroTier network controller through the web interface.

LitServe is a high-throughput serving engine designed for deploying AI models at scale. It generates an API endpoint for models, handles batching, streaming, and autoscaling across CPU/GPUs. LitServe is built for enterprise scale with a focus on minimal, hackable code-base without bloat. It supports various model types like LLMs, vision, time-series, and works with frameworks like PyTorch, JAX, Tensorflow, and more. The tool allows users to focus on model performance rather than serving boilerplate, providing full control and flexibility.

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.

Vidur is a high-fidelity and extensible LLM inference simulator designed for capacity planning, deployment configuration optimization, testing new research ideas, and studying system performance of models under different workloads and configurations. It supports various models and devices, offers chrome trace exports, and can be set up using mamba, venv, or conda. Users can run the simulator with various parameters and monitor metrics using wandb. Contributions are welcome, subject to a Contributor License Agreement and adherence to the Microsoft Open Source Code of Conduct.

The Google Cloud Applied AI Engineering repository provides reference guides, blueprints, code samples, and hands-on labs developed by the Google Cloud Applied AI Engineering team. It contains resources for Generative AI on Vertex AI, including code samples and hands-on labs demonstrating the use of Generative AI models and tools in Vertex AI. Additionally, it offers reference guides and blueprints that compile best practices and prescriptive guidance for running large-scale AI/ML workloads on Google Cloud AI/ML infrastructure.

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.

EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.

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.