Best AI tools for< Monitor Cluster Resources >

Pulse is a world-class expert support tool for BigData stacks, specifically focusing on ensuring the stability and performance of Elasticsearch and OpenSearch clusters. It offers early issue detection, AI-generated insights, and expert support to optimize performance, reduce costs, and align with user needs. Pulse leverages AI for issue detection and root-cause analysis, complemented by real human expertise, making it a strategic ally in search cluster management.

Meticulous is an AI tool that revolutionizes frontend testing by automatically generating and maintaining test suites for web applications. It eliminates the need for manual test writing and maintenance, ensuring comprehensive test coverage without the hassle. Meticulous uses AI to monitor user interactions, generate test suites, and provide visual end-to-end testing capabilities. It offers lightning-fast testing, parallelized across a compute cluster, and integrates seamlessly with existing test suites. The tool is battle-tested to handle complex applications and provides developers with confidence in their code changes.

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.

The website is a platform that seems to be encountering a client-side exception error. Users are prompted to check the browser console for more information. The site may be experiencing technical issues that need to be resolved to ensure proper functionality.

The website seems to be encountering a 403 Forbidden error, which indicates that the server is refusing to respond to the request. This error is often caused by incorrect permissions on the server or misconfigured security settings. The message '403 Forbidden' is a standard HTTP status code that indicates the server understood the request but refuses to authorize it. Users encountering this error may need to contact the website administrator for assistance in resolving the issue.

LLMMM is an AI tool designed to monitor how AI models perceive and present brands. It offers real-time monitoring and cross-model insights to help brands understand their digital presence across various leading AI platforms. With automated analysis and lightning-fast results, LLMMM provides immediate visibility into how AI chatbots interpret brands. The tool focuses on brand intelligence, brand safety monitoring, misalignment detection, and cross-model brand intelligence. Users can create an account in minutes and access a range of features to track and analyze their brand's performance in the AI landscape.

New Relic is an AI monitoring platform that offers an all-in-one observability solution for monitoring, debugging, and improving the entire technology stack. With over 30 capabilities and 750+ integrations, New Relic provides the power of AI to help users gain insights and optimize performance across various aspects of their infrastructure, applications, and digital experiences.

Browse AI is an AI-powered data extraction and monitoring platform that allows users to scrape and monitor data from any website without the need for coding. It offers a full suite of features for stress-free data extraction, including turning websites into APIs, monitoring for changes, and extracting specific data effortlessly. With Browse AI, users can extract product data for e-commerce, property listings for real estate, job listings for recruitment, and stay updated on financial market moves for investors & VCs. The platform is designed to be easy to use, reliable, and scalable, making it a valuable tool for various industries and use cases.

Arize AI is an AI Observability & LLM Evaluation Platform that helps you monitor, troubleshoot, and evaluate your machine learning models. With Arize, you can catch model issues, troubleshoot root causes, and continuously improve performance. Arize is used by top AI companies to surface, resolve, and improve their models.

Devi is an AI-powered social media lead generation and outreach tool that helps businesses find and engage with potential customers on Facebook, LinkedIn, Twitter, Reddit, and other platforms. It uses artificial intelligence to monitor keywords and identify high-intent leads, and then provides users with tools to reach out to those leads and build relationships. Devi also offers a variety of other features, such as AI-generated content, scheduling, and analytics.

Hexowatch is an AI-powered website monitoring and archiving tool that helps businesses track changes to any website, including visual, content, source code, technology, availability, or price changes. It provides detailed change reports, archives snapshots of pages, and offers side-by-side comparisons and diff reports to highlight changes. Hexowatch also allows users to access monitored data fields as a downloadable CSV file, Google Sheet, RSS feed, or sync any update via Zapier to over 2000 different applications.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

KWatch.io is a social listening tool that helps businesses monitor keywords on social media platforms like LinkedIn, Twitter, Reddit, and Hacker News. It uses AI to analyze the sentiment around keywords and provides real-time alerts when specific keywords are mentioned. KWatch.io can be used for a variety of purposes, including attracting customers, getting feedback, watching competitors, conducting market intelligence, and providing customer support. It offers various plans, including a free plan, an essential plan for $19/month, a business plan for $79/month, and an enterprise plan for $199/month.

AI Spend is an AI application designed to help users monitor their AI costs and prevent surprises. It allows users to keep track of their OpenAI usage and costs, providing fast insights, a beautiful dashboard, cost insights, notifications, usage analytics, and details on models and tokens. The application ensures simple pricing with no additional costs and securely stores API keys. Users can easily remove their data if needed, emphasizing privacy and security.

Google Cloud Service Health Console provides status information on the services that are part of Google Cloud. It allows users to check the current status of services, view detailed overviews of incidents affecting their Google Cloud projects, and access custom alerts, API data, and logs through the Personalized Service Health dashboard. The console also offers a global view of the status of specific globally distributed services and allows users to check the status by product and location.

WhenX is an AI tool designed to create robots that monitor the web for users. It allows users to create Semantic Alerts by asking questions, searching the web for answers, and monitoring for any changes. Users can track updates on their favorite writers, job postings, or new product releases. WhenX is a personal project not intended for commercial use, and it is open source, built by edmar and hosted on Vercel.

Vocera is an AI voice agent testing tool that allows users to test and monitor voice AI agents efficiently. It enables users to launch voice agents in minutes, ensuring a seamless conversational experience. With features like testing against AI-generated datasets, simulating scenarios, and monitoring AI performance, Vocera helps in evaluating and improving voice agent interactions. The tool provides real-time insights, detailed logs, and trend analysis for optimal performance, along with instant notifications for errors and failures. Vocera is designed to work for everyone, offering an intuitive dashboard and data-driven decision-making for continuous improvement.

The website offers Full-Stack Cloud Observability services with a focus on Middleware. It provides comprehensive monitoring and analysis tools to ensure optimal performance and reliability of cloud-based applications. Users can gain insights into their middleware components and infrastructure to troubleshoot issues and improve overall system efficiency.

Fiddler AI is an AI Observability platform that provides tools for monitoring, explaining, and improving the performance of AI models. It offers a range of capabilities, including explainable AI, NLP and CV model monitoring, LLMOps, and security features. Fiddler AI helps businesses to build and deploy high-performing AI solutions at scale.

Veriti is an AI-driven platform that proactively monitors and safely remediates exposures across the entire security stack, without disrupting the business. It helps organizations maximize their security posture while ensuring business uptime. Veriti offers solutions for safe remediation, MITRE ATT&CK®, healthcare, MSSPs, and manufacturing. The platform correlates exposures to misconfigurations, continuously assesses exposures, integrates with various security solutions, and prioritizes remediation based on business impact. Veriti is recognized for its role in exposure assessments and remediation, providing a consolidated security platform for businesses to neutralize threats before they happen.

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.

HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

Azure HPC On-Demand Platform (az-hop) provides an end-to-end deployment mechanism for a base HPC infrastructure on Azure. It delivers a complete HPC cluster solution ready for users to run applications, which is easy to deploy and manage for HPC administrators. az-hop leverages various Azure building blocks and can be used as-is or easily customized and extended to meet any uncovered requirements. Industry-standard tools like Terraform, Ansible, and Packer are used to provision and configure this environment, which contains: - An HPC OnDemand Portal for all user access, remote shell access, remote visualization access, job submission, file access, and more - An Active Directory for user authentication and domain control - Open PBS or SLURM as a Job Scheduler - Dynamic resources provisioning and autoscaling is done by Azure CycleCloud pre-configured job queues and integrated health-checks to quickly avoid non-optimal nodes - A Jumpbox to provide admin access - A common shared file system for home directory and applications is delivered by Azure Netapp Files - Grafana dashboards to monitor your cluster - Remote Visualization with noVNC and GPU acceleration with VirtualGL

Sematic is an open-source ML development platform that allows ML Engineers and Data Scientists to write complex end-to-end pipelines with Python. It can be executed locally, on a cloud VM, or on a Kubernetes cluster. Sematic enables chaining data processing jobs with model training into reproducible pipelines that can be monitored and visualized in a web dashboard. It offers features like easy onboarding, local-to-cloud parity, end-to-end traceability, access to heterogeneous compute resources, and reproducibility.

Backend.AI Web UI is a user-friendly web and app interface designed to make AI accessible for end-users, DevOps, and SysAdmins. It provides features for session management, inference service management, pipeline management, storage management, node management, statistics, configurations, license checking, plugins, help & manuals, kernel management, user management, keypair management, manager settings, proxy mode support, service information, and integration with the Backend.AI Web Server. The tool supports various devices, offers a built-in websocket proxy feature, and allows for versatile usage across different platforms. Users can easily manage resources, run environment-supported apps, access a web-based terminal, use Visual Studio Code editor, manage experiments, set up autoscaling, manage pipelines, handle storage, monitor nodes, view statistics, configure settings, and more.

Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs. It allocates and isolates the underlying computing resources for multi-tenant computation sessions on-demand or in batches with customizable job schedulers with its own orchestrator. All its functions are exposed as REST/GraphQL/WebSocket APIs.

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.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

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.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

The AI Horde is an enterprise-level ML-Ops crowdsourced distributed inference cluster for AI Models. This middleware can support both Image and Text generation. It is infinitely scalable and supports seamless drop-in/drop-out of compute resources. The Public version allows people without a powerful GPU to use Stable Diffusion or Large Language Models like Pygmalion/Llama by relying on spare/idle resources provided by the community and also allows non-python clients, such as games and apps, to use AI-provided generations.

Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.

This repository contains reference architectures and test cases for distributed model training with Amazon SageMaker Hyperpod, AWS ParallelCluster, AWS Batch, and Amazon EKS. The test cases cover different types and sizes of models as well as different frameworks and parallel optimizations (Pytorch DDP/FSDP, MegatronLM, NemoMegatron...).

RayLLM (formerly known as Aviary) is an LLM serving solution that makes it easy to deploy and manage a variety of open source LLMs, built on Ray Serve. It provides an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. RayLLM supports Transformer models hosted on Hugging Face Hub or present on local disk. It simplifies the deployment of multiple LLMs, the addition of new LLMs, and offers unique autoscaling support, including scale-to-zero. RayLLM fully supports multi-GPU & multi-node model deployments and offers high performance features like continuous batching, quantization and streaming. It provides a REST API that is similar to OpenAI's to make it easy to migrate and cross test them. RayLLM supports multiple LLM backends out of the box, including vLLM and TensorRT-LLM.

Awesome Generative AI is a curated list of modern Generative Artificial Intelligence projects and services. Generative AI technology creates original content like images, sounds, and texts using machine learning algorithms trained on large data sets. It can produce unique and realistic outputs such as photorealistic images, digital art, music, and writing. The repo covers a wide range of applications in art, entertainment, marketing, academia, and computer science.

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EUR/ZAR analysis with real-time rate and current news focus

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