Azure Programming Tutorials & Engineering Articles

Enterprise Java developers have a new superpower—drive GitHub Copilot from idiomatic Java code with annotations, virtual threads, and more.

This release brings speedups for GROUP BY ... ORDER BY ... LIMIT, three JOIN improvements, four vector search improvements, position-aware phrase search, EXPLAIN ANALYZE, unified URL access, and more!

Ten best practices for getting the most out of ClickHouse, from primary key design and data types to materialized views, ReplacingMergeTree, and join optimization — illustrated with benchmarks on a 150M row dataset.

chDB embeds a full ClickHouse query engine inside an agent's own process, turning data access, memory, and federation into local function calls instead of network round trips, cutting the latency, retries, and token waste that come with remote queries.

Using population-level analysis to debug tricky crashes in our data infrastructure.

AI agents are quickly moving beyond chat. They inspect code, run tests, read documents, search knowledge bases, query internal systems, and operate for hours on…

AI agents are a powerful tool for synthesizing data to accelerate research, summarize information, and help teams make decisions faster.

MRC’s support for multi-plane networks means we can connect over a hundred thousand GPUs with only two tiers of switches. This reduces the power required, the number of components that can fail, and the total cost of the network compared to conventional approaches.

Agentic systems often reason across screens, documents, audio, video, and text within a single perception‑to‑action loop. However, they still rely on fragmented…

AI integration is redefining mainstream enterprise applications, from productivity software like Microsoft Office to more complex design and engineering tools.

Physical AI—AI systems that perceive, reason, and act in physically grounded simulated environments—is changing how teams design and validate robots and…

Reasoning models are growing rapidly in size and are increasingly being integrated into agentic AI workflows that interact with other models and external tools.

Deploying large language models (LLMs) requires large-scale distributed inference, which spreads model computation and request handling across many GPUs and…

The article discusses the development of the Microsoft Learn Model Context Protocol (MCP) Server, launched in June 2025, aimed at facilitating AI agents' access to Microsoft Learn documentation.

This article explains the core agent loop architecture behind OpenAI's Codex CLI, detailing how it orchestrates interactions between users, LLM models, and tools to perform software engineering tas...

OpenAI details how they scaled PostgreSQL to support 800 million ChatGPT users, achieving millions of queries per second through a single-primary architecture with nearly 50 read replicas across mu...

This article details how Uber built and scaled Apache Hudi to power one of the world's largest data lakes, managing 19,500 datasets with trillions of records across a multi-hundred-petabyte reposit...

The article discusses how to build and orchestrate end-to-end synthetic data generation (SDG) workflows using NVIDIA Isaac Sim and NVIDIA OSMO.

The article discusses the development of scientific AI agents using reinforcement learning (RL) techniques, specifically through the NVIDIA NeMo framework.

The 2025 Cloudflare Radar Year in Review highlights significant trends in internet traffic, the rise of AI, post-quantum encryption, and the increase in DDoS attacks.

This article provides a detailed analysis of how the five major cloud data warehouses—Snowflake, Databricks, ClickHouse Cloud, Google BigQuery, and Amazon Redshift Serverless—calculate compute cost...

The article discusses the integration of NVIDIA Nemotron RAG with Microsoft SQL Server 2025, showcasing how this collaboration enables the development of scalable AI applications on enterprise data.

This article details the transformation of ClickHouse's internal data warehouse from a traditional BI-first approach to an AI-first model, significantly enhancing user accessibility to analytics.

The article discusses how NVIDIA Run:ai enhances AI infrastructure management on Microsoft Azure by optimizing GPU utilization and simplifying workload orchestration.

The article discusses the potential of lakehouses using open table formats like Apache Iceberg and Delta Lake for observability, highlighting their advantages in scalability, cost-effectiveness, an...

The article discusses the modernization of the LDAP and Kerberos infrastructure that secures Hadoop at LinkedIn, detailing the transition from a legacy setup to a highly available, automated system...

Litestream v0. 5.

ClickHouse Release 25. 9 introduces significant enhancements, including 25 new features, 22 performance optimizations, and 83 bug fixes.

ClickHouse version 25. 8 introduces 45 new features, 47 performance optimizations, and 119 bug fixes, enhancing its capabilities as a high-performance analytical database.

The article discusses NVIDIA Omniverse Kit App Streaming, a solution for deploying and streaming 3D applications built with NVIDIA's SDKs directly to browsers.

The article discusses the release of NVIDIA vGPU 19. 0, which enhances graphics and AI virtualization on NVIDIA Blackwell GPUs, specifically the RTX PRO 6000 series.

The article discusses the deployment of a serverless, distributed data processing architecture using Apache Spark and NVIDIA AI on Azure.

Google Cloud has donated the Agent2Agent (A2A) protocol to the Linux Foundation, marking a significant step towards creating an open and interoperable ecosystem for AI agents.

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

Conservationists have developed an AI tool, GhostNetZero. ai, to identify and locate dangerous abandoned fishing nets, known as ghost nets, using underwater imaging data.

The article discusses the latest enhancements in RAPIDS, including zero-code-change acceleration for Python machine learning, significant IO performance improvements, and out-of-core XGBoost capabi...

The article discusses the collaboration between Iguazio and NVIDIA, focusing on how their combined technologies, MLRun and NVIDIA NIM, enable organizations to build scalable and observable AI solut...

This article discusses the development of a distributed cache for ClickHouse Cloud, aimed at providing low-latency access to hot data across compute nodes.

The article discusses how Atgenomix SeqsLab leverages NVIDIA technologies to enhance health omics analysis for precision medicine.

The article discusses significant updates to Google's intelligent agent ecosystem, focusing on the Agent Development Kit (ADK), the Agent Engine UI, and enhancements to the Agent2Agent (A2A) protoc...

The article discusses the advancements in video analytics through the NVIDIA AI Blueprint for Video Search and Summarization (VSS), highlighting the integration of Vision Language Models (VLMs), La...

The article discusses the use of GPU acceleration to enhance performance in Apache Spark applications, highlighting the challenges of migrating workloads from CPUs to GPUs.

The article discusses how to leverage NVIDIA CUDA-X and Coiled to simplify data science workflows in the cloud, particularly for analyzing large datasets like NYC ride-share journeys.

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 how to accelerate Deep Learning (DL) and Large Language Model (LLM) inference using Apache Spark in cloud environments.

The article discusses how ClickHouse efficiently queries Parquet files, a key storage format for Lakehouse architectures, without requiring data ingestion.

This article provides a simplified introduction to CUDA, NVIDIA's parallel computing platform, and programming model.

NVIDIA has announced the general availability of Secure AI, focusing on protecting data and code during AI training and inference, particularly for large language models (LLMs).

The article discusses the increasing demand for NVIDIA accelerated computing in enterprise AI workloads and how Rafay's platform-as-a-service (PaaS) model addresses the challenges of building self-...