Microservices Programming Tutorials & Engineering Articles

This article discusses the implementation of horizontal autoscaling for Retrieval-Augmented Generation (RAG) components on Kubernetes, focusing on NVIDIA's microservices architecture.

The article discusses the creation of privacy-preserving evaluation benchmarks using synthetic data, particularly in regulated domains like healthcare.

The NVIDIA Grace CPU, launched in 2023, integrates Arm Neoverse cores with advanced memory and interconnect technologies to deliver high bandwidth and energy efficiency for modern data centers.

The article discusses the use of AI Model Distillation to create efficient financial data workflows, focusing on the optimization of large language models (LLMs) for applications in quantitative fi...

The article discusses the evolution and modernization of Viaduct, Airbnb's data-oriented service mesh, highlighting its transition to open-source software.

The article discusses the deployment of scalable AI inference using NVIDIA NIM Operator 3. 0. 0, highlighting its capabilities in managing AI inference pipelines across Kubernetes environments.

The article discusses the evolution of AI agents from relying on static training data to utilizing dynamic knowledge through Retrieval-Augmented Generation (RAG) and AI query engines.

The article discusses the integration of NVIDIA BlueField-3 Data Processing Units (DPUs) with F5 BIG-IP Next for Kubernetes to enhance the deployment of agentic AI applications in cloud environment...

The article discusses NVIDIA's ITMonitron, a tool designed to enhance real-time IT incident detection by integrating various monitoring signals into actionable intelligence.

The article discusses the operational challenges of deploying large language models (LLMs) and introduces LLMOps as a framework for managing their lifecycle.

The article discusses the integration of NVIDIA NIM microservices into Azure AI Foundry, highlighting how this collaboration enhances enterprise AI development by enabling efficient deployment of A...

The article discusses the release of NVIDIA NIM Operator 2. 0, which enhances AI deployment by supporting NVIDIA NeMo microservices.

This article discusses the importance of data flywheels in maintaining the accuracy of AI systems over time, particularly in enterprise settings.

The article discusses the launch of NVIDIA NIM microservices designed to enhance AI development on NVIDIA RTX AI PCs and workstations.

The article discusses how to enhance AI agent performance using NVIDIA NeMo microservices and a data flywheel strategy.

The article discusses how NVIDIA Holoscan for Media and NVIDIA NIM enhance live media workflows through AI and microservices.

The article discusses the use of NVIDIA NIM microservices to accelerate the process of systematic literature reviews through the application of large language models (LLMs).

This article discusses the horizontal autoscaling of NVIDIA NIM microservices on Kubernetes, focusing on how to set up Kubernetes Horizontal Pod Autoscaling (HPA) based on custom metrics like GPU c...

The article discusses the integration of generative AI and NVIDIA NIM microservices to create a medical device training assistant.

The article highlights significant advancements in NVIDIA technologies throughout 2024, focusing on NVIDIA NIM, breakthroughs in large language models (LLMs), and optimizations in data science.

This article discusses data access patterns for integrating with Stripe, emphasizing the importance of choosing the right data storage strategy to enhance security, performance, and scalability.

This article provides a comprehensive guide on building a human-in-the-loop AI agent using NVIDIA NIM microservices.

The article discusses the creation of retrieval augmented generation (RAG)-based question-and-answer workflows at NVIDIA, highlighting the integration of various technologies like LlamaIndex, NVIDI...

The article discusses the integration of NVIDIA NIM with Google Kubernetes Engine (GKE) to enhance AI inference capabilities.

The article discusses advanced Retrieval-Augmented Generation (RAG) techniques applied to telecommunications standards, specifically O-RAN, using NVIDIA NIM microservices.

The article discusses the NVIDIA Grace CPU, designed for high-performance data center computing with a focus on energy efficiency and performance optimization.

The article discusses the integration of large language models (LLMs) into enterprise applications using NVIDIA NIM and Outerbounds, emphasizing the importance of secure deployment, continuous impr...

Montai Therapeutics is leveraging NVIDIA BioNeMo to develop a multimodal AI platform for drug discovery, focusing on Anthromolecule chemistry.

The article discusses Preon, a microservice developed by Uber for intelligent and efficient query analysis using the Presto SQL engine.

The article discusses NVIDIA NIM microservices, which enable developers to integrate GPU-accelerated speech recognition and translation capabilities into applications.

The article discusses the NVIDIA Maxine AI developer platform, which provides a suite of microservices and SDKs for enhancing real-time video and audio applications.

The article discusses how xpander AI enhances NVIDIA NIM applications by providing agentic tools that facilitate real-time data fetching and interaction with external systems.

This article discusses the process of camera calibration to enhance AI-powered multi-camera tracking using NVIDIA Metropolis.

The article discusses optimizing inference efficiency for large language models (LLMs) using NVIDIA NIM microservices.

The article discusses how to build AI agents using NVIDIA NIM microservices in conjunction with LangChain, focusing on the capabilities of the Llama 3. 1 model.

The article discusses the NVIDIA Grace family of CPUs, designed to enhance data center efficiency amidst rising data processing demands.

NVIDIA showcases advancements in the Maxine AI developer platform at SIGGRAPH 2024, focusing on features that enhance audio and video quality, including Maxine Video Relighting and Eye Contact micr...

The article discusses the importance of fine-tuning AI models with synthetic data to enhance multi-camera tracking accuracy. It highlights the use of NVIDIA Isaac Sim and the Omni. Replicator.

The article discusses how NVIDIA NIM can transform financial analysis by enabling faster and more accurate insights extraction from earnings call transcripts.

The article discusses NVIDIA Metropolis, a platform for real-time vision AI that streamlines deployment through microservices and workflows.

This article discusses the implementation of Intelligent Transportation Systems (ITS) using YOLOv8 and NVIDIA JetPack 6. 0.

NVIDIA JetPack 6. 0 introduces significant enhancements for building cloud-native microservices on Jetson devices, focusing on flexibility, scalability, and AI application development.

NVIDIA ACE, a suite of generative AI-enabled digital human technologies, is now generally available for developers.

This article introduces the multi-camera tracking workflow developed by NVIDIA, aimed at optimizing processes in large spaces such as warehouses and airports.

The article discusses the NVIDIA DeepStream 7. 0 SDK release, highlighting its capabilities for building end-to-end vision AI pipelines with GPU acceleration.

This article provides a detailed guide on customizing Neural Machine Translation (NMT) models using NVIDIA NeMo, focusing on curating a custom dataset and fine-tuning the model.

The article discusses the development of the Video Encoding Service (VES) as part of Netflix's Cosmos microservice architecture, detailing its design, implementation, and the lessons learned throug...

The article discusses the NVIDIA NeMo Evaluator, a cloud-native microservice designed to streamline the evaluation of Large Language Models (LLMs) for accuracy.

The article discusses the NVIDIA NeMo microservices, which simplify the development of custom generative AI models for enterprises.

NVIDIA NIM is a set of optimized cloud-native microservices designed to facilitate the deployment of AI models at scale, addressing the complexities of AI model development and integration into ent...