Best AI tools for< Monitor Cloud-native Applications >

api4ai is a cloud-native AI application that offers image processing APIs powered by artificial intelligence. It provides affordable and personalized solutions for businesses, empowering them with computer vision and machine learning capabilities. The application allows users to monitor visitor statistics, expand product identification apps, integrate background removal algorithms, estimate marketing campaign effectiveness, automate production processes, manage clothing stocktaking, enhance car dealership ads, ensure workplace safety, and extract information for enterprises, startups, and developers. With a wide range of ready-to-use APIs and customization options, api4ai simplifies the implementation of AI solutions across various industries.

Traceable is an AI-driven application designed to enhance API security for Cloud-Native Apps. It collects API traffic across the application landscape and utilizes advanced context-based behavioral analytics AI engine to provide insights on APIs, data exposure, threat analytics, and forensics. The platform offers features for API cataloging, activity monitoring, endpoint details, ownership, vulnerabilities, protection against security events, testing, analytics, and more. Traceable also allows for role-based access control, policy configuration, data classification, and integration with third-party solutions for data collection and security. It is a comprehensive tool for API security and threat detection in modern cloud environments.

Picterra is a geospatial AI platform that offers reliable solutions for sustainability, compliance, monitoring, and verification. It provides an all-in-one plot monitoring system, professional services, and interactive tours. Users can build custom AI models to detect objects, changes, or patterns using various geospatial imagery data. Picterra aims to revolutionize geospatial analysis with its category-leading AI technology, enabling users to solve challenges swiftly, collaborate more effectively, and scale further.

Lightup is a cloud data quality monitoring tool with AI-powered anomaly detection, incident alerts, and data remediation capabilities for modern enterprise data stacks. It specializes in helping large organizations implement successful and sustainable data quality programs quickly and easily. Lightup's pushdown architecture allows for monitoring data content at massive scale without moving or copying data, providing extreme scalability and optimal automation. The tool empowers business users with democratized data quality checks and enables automatic fixing of bad data at enterprise scale.

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.

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.

Arize AI is an AI observability tool designed to monitor and troubleshoot AI models in production. It provides configurable and sophisticated observability features to ensure the performance and reliability of next-gen AI stacks. With a focus on ML observability, Arize offers automated setup, a simple API, and a lightweight package for tracking model performance over time. The tool is trusted by top companies for its ability to surface insights, simplify issue root causing, and provide a dedicated customer success manager. Arize is battle-hardened for real-world scenarios, offering unparalleled performance, scalability, security, and compliance with industry standards like SOC 2 Type II and HIPAA.

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.

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.

Modal is a high-performance cloud platform designed for developers, AI data, and ML teams. It offers a serverless environment for running generative AI models, large-scale batch jobs, job queues, and more. With Modal, users can bring their own code and leverage the platform's optimized container file system for fast cold boots and seamless autoscaling. The platform is engineered for large-scale workloads, allowing users to scale to hundreds of GPUs, pay only for what they use, and deploy functions to the cloud in seconds without the need for YAML or Dockerfiles. Modal also provides features for job scheduling, web endpoints, observability, and security compliance.

Gamma.AI is a cloud-based data loss prevention (DLP) solution that uses artificial intelligence (AI) to protect sensitive data in SaaS applications. It provides real-time data discovery and classification, user behavior analytics, and automated remediation capabilities. Gamma.AI is designed to help organizations meet compliance requirements and protect their data from unauthorized access, theft, and loss.

DRYiCE is an AI foundation for the digital enterprise, offering a range of AI ops products and solutions to transform and simplify IT and business operations by leveraging AI and Cloud technologies. With a diverse portfolio including DRYiCE iAutomate, DRYiCE AEX, DRYiCE MyCloud, DRYiCE MyXalytics, and more, DRYiCE aims to enhance service orchestration, observability, and business flow management across various industries such as energy, healthcare, financial services, and manufacturing. The platform boasts over 12 years of experience in AI-led R&D, serving 283 customers globally and holding 30 patents.

Coram AI is a modern business video security platform that offers AI-powered solutions for various industries such as warehouse, manufacturing, healthcare, education, and more. It provides advanced features like gun detection, productivity alerts, facial recognition, and safety alerts to enhance security and operations. Coram AI's flexible architecture allows users to seamlessly integrate with any IP camera and scale effortlessly to meet their demands. With natural language search capabilities, users can quickly find relevant footage and improve decision-making. Trusted by local businesses and Fortune 500 companies, Coram AI delivers real business value through innovative AI tools and reliable customer support.

UpTrain is a full-stack LLMOps platform designed to help users confidently scale AI by providing a comprehensive solution for all production needs, from evaluation to experimentation to improvement. It offers diverse evaluations, automated regression testing, enriched datasets, and innovative techniques to generate high-quality scores. UpTrain is built for developers, compliant to data governance needs, cost-efficient, remarkably reliable, and open-source. It provides precision metrics, task understanding, safeguard systems, and covers a wide range of language features and quality aspects. The platform is suitable for developers, product managers, and business leaders looking to enhance their LLM applications.

Seldon is an MLOps platform that helps enterprises deploy, monitor, and manage machine learning models at scale. It provides a range of features to help organizations accelerate model deployment, optimize infrastructure resource allocation, and manage models and risk. Seldon is trusted by the world's leading MLOps teams and has been used to install and manage over 10 million ML models. With Seldon, organizations can reduce deployment time from months to minutes, increase efficiency, and reduce infrastructure and cloud costs.

Jyotax.ai is an AI-powered tax solution that revolutionizes tax compliance by simplifying the tax process with advanced AI solutions. It offers comprehensive bookkeeping, payroll processing, worldwide tax returns and filing automation, profit recovery, contract compliance, and financial modeling and budgeting services. The platform ensures accurate reporting, real-time compliance monitoring, global tax solutions, customizable tax tools, and seamless data integration. Jyotax.ai optimizes tax workflows, ensures compliance with precise AI tax calculations, and simplifies global tax operations through innovative AI solutions.

OctoEverywhere is a free cloud service designed for the 3D printing community, offering remote access and AI print failure detection capabilities. Users can monitor their 3D printers, receive notifications, and stream live webcam feeds. The platform aims to empower users with tools like Gadget, an AI assistant that detects common printing failures and helps save time and money. OctoEverywhere ensures privacy and security, with end-to-end encryption and a commitment to data protection. The service is community-funded and offers both free and supporter perks tiers for enhanced features.

VOLT AI is a cloud-based enterprise security application that utilizes advanced AI technology to intercept threats in real-time. The application offers solutions for various industries such as education, corporate, and cities, focusing on perimeter security, medical emergencies, and weapons detection. VOLT AI provides features like unified cameras, video intelligence, real-time notifications, automated escalations, and digital twin creation for advanced situational awareness. The application aims to enhance safety and security by detecting security risks and notifying users promptly.

Spot AI is a Video AI platform that transforms cameras into intelligent tools to secure, protect, and optimize operations. It offers features such as real-time visibility, incident resolution, worker safety, and training. The platform includes AI agents, semantic search, and state-of-the-art video AI models to drive business outcomes and enhance productivity. Spot AI is trusted by over 1,000 organizations to reduce workplace injuries, improve incident resolution time, and increase operational throughput.

Meysey is an AI fraud protection application designed for accountants and IT managed service providers. It offers automated fraud scanning using financial and operational data to help organizations prosper against the evolving fraud landscape. Meysey provides scalable solutions with seamless deployment and tailored pricing, enabling users to gain visibility of bribery and corruption risk, identify conflicts of interest, baseline financial patterns, and comply with fraud legislation. The application integrates with finance and business operations tools to analyze data across the commercial landscape, providing actionable insights to enhance business resilience and reduce fraud risk.

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

HoloInsight is a cloud-native observability platform that provides low-cost and high-performance monitoring services for cloud-native applications. It offers deep insights through real-time log analysis and AI integration. The platform is designed to help users gain a comprehensive understanding of their applications' performance and behavior in the cloud environment. HoloInsight is easy to deploy using Docker and Kubernetes, making it a versatile tool for monitoring and optimizing cloud-native applications. With a focus on scalability and efficiency, HoloInsight is suitable for organizations looking to enhance their observability and monitoring capabilities in the cloud.

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.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

DeepFlow is an open-source project that provides deep observability for complex cloud-native and AI applications. It offers Zero Code data collection with eBPF for metrics, distributed tracing, request logs, and function profiling. DeepFlow is integrated with SmartEncoding to achieve Full Stack correlation and efficient access to all observability data. With DeepFlow, cloud-native and AI applications automatically gain deep observability, removing the burden of developers continually instrumenting code and providing monitoring and diagnostic capabilities covering everything from code to infrastructure for DevOps/SRE teams.

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. For more architecture details, see Milvus Architecture Overview. Milvus was released under the open-source Apache License 2.0 in October 2019. It is currently a graduate project under LF AI & Data Foundation.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

This repository serves as a personal knowledge base for the owner's reference and use. It covers a wide range of topics including cloud-native operations, Kubernetes ecosystem, networking, cloud services, telemetry, CI/CD, electronic engineering, hardware projects, operating systems, homelab setups, high-performance computing applications, openwrt router usage, programming languages, music theory, blockchain, distributed systems principles, and various other knowledge domains. The content is periodically refined and published on the owner's blog for maintenance purposes.

AppBuilder SDK is a one-stop development tool for AI native applications, providing basic cloud resources, AI capability engine, Qianfan large model, and related capability components to improve the development efficiency of AI native applications.

E.D.D.I (Enhanced Dialog Driven Interface) is an enterprise-certified chatbot middleware that offers advanced prompt and conversation management for Conversational AI APIs. Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. E.D.D.I is highly scalable and designed to efficiently manage conversations in AI-driven applications, with seamless API integration capabilities. Notable features include configurable NLP and Behavior rules, support for multiple chatbots running concurrently, and integration with MongoDB, OAuth 2.0, and HTML/CSS/JavaScript for UI. The project requires Java 21, Maven 3.8.4, and MongoDB >= 5.0 to run. It can be built as a Docker image and deployed using Docker or Kubernetes, with additional support for integration testing and monitoring through Prometheus and Kubernetes endpoints.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

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).

AGiXT is a dynamic Artificial Intelligence Automation Platform engineered to orchestrate efficient AI instruction management and task execution across a multitude of providers. Our solution infuses adaptive memory handling with a broad spectrum of commands to enhance AI's understanding and responsiveness, leading to improved task completion. The platform's smart features, like Smart Instruct and Smart Chat, seamlessly integrate web search, planning strategies, and conversation continuity, transforming the interaction between users and AI. By leveraging a powerful plugin system that includes web browsing and command execution, AGiXT stands as a versatile bridge between AI models and users. With an expanding roster of AI providers, code evaluation capabilities, comprehensive chain management, and platform interoperability, AGiXT is consistently evolving to drive a multitude of applications, affirming its place at the forefront of AI technology.

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.

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.

Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

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.

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