Discover how state and local agencies use Google Cloud AI to break data silos and modernize public services. Join us at the GPS Summit Oct 20.

Learn to design a database caching system with cache-aside, TTL, invalidation, single-flight and jitter to prevent cache stampedes.

A hybrid cloud architecture pattern for modernizing medical imaging on AWS. Learn how multi-hospital networks can centralize PACS archives, enable cross-facility interoperability, and use Amazon S3 storage tiers to manage cost and retention at scale.

Amazon SageMaker HyperPod Inference Gateway is a Kubernetes-native, GPU-aware routing add-on for Amazon EKS. It uses real-time GPU signals to send each inference request to the best-suited pod, cutting first-token latency by up to 82% with no changes to your model servers or client applications.

Combine zero-shot forecasting with Amazon Chronos2 and multi-agent orchestration on Amazon Bedrock AgentCore to turn demand forecasts into validated purchase orders. No per-product model training, with business rules, auditability, and cost that scales to zero.

Learn how researchers at CSIRO, Australia's national science agency, built Serverless Beacon (sBeacon), a scalable serverless solution for securely querying genomic variant data on AWS. sBeacon implements the GA4GH Beacon standard using Amazon S3, AWS Lambda, Amazon DynamoDB, and Amazon Athena to support production-scale clinical and research applications.

Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants. Gartner placed Google in the Leaders quadrant for its evaluation across both Completeness of Vision and Ability to Execute.

Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This approach improved person detection by up to 160% without manual annotation or hazardous data collection near heavy machinery.

AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills across 11 HCLS domains that close this gap, with installation steps, three worked use cases, and a 410-prompt evaluation showing a 70-86% win rate.

Equinix, the world's digital infrastructure company, built a shared services architecture on Amazon EKS to eliminate the operational sprawl of its self-managed Kubernetes environment. Learn how a multi-account North Star architecture centralized governance and shared services, delivering 4x faster deployments and 40% less operational overhead.

Learn how DHI Group partnered with AWS to move generative AI workloads from idea to production using a structured hackathon. This post covers the Hackathon Acceleration Package, the winning ClearanceJobs and AgileATS agentic architecture on Amazon Bedrock AgentCore, and the principles that make hackathons a repeatable path to production.

The M4N machine series is now GA, providing high per-core IOPS and throughput, and over 20% TCO reduction for Oracle databases.

Recent features and capabilities in Dataflow improve developer productivity and accelerate batch and streaming AI workloads.

Learn how Kubernetes works, from the control plane and scheduler to kubelet, pods, and Services, with simple answers to interview questions.

Researchers designed an AI-driven system that could boost the safety and speed of minimally invasive surgical procedures by rapidly matching X-rays captured during surgery with a patient’s preoperative 3D medical scan.

Learn how Abnormal AI deployed Amazon Bedrock AgentCore Code Interpreter as an ephemeral compute scratch pad for the agents behind its real-time email threat detection at billion-message scale, plus the sandbox design decisions and practical lessons for builders deploying Code Interpreter in production.

Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda. A custom blueprint redacts sensitive fields with field-level precision, and a token matching quality check raises recall across degraded and handwritten documents.

TwelveLabs Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, bringing fully managed natural language search to video, image, and audio content. This walkthrough shows how to build a knowledge base powered by Marengo 3.0 and run semantic queries against your media.

Learn how MRH Trowe, one of Germany's leading commercial and industrial insurance brokers, gave about 400 employees secure, self-service access to AI agents in its first month of production - using Strands Agents, Amazon Bedrock AgentCore, and LibreChat to meet the security, data residency, and compliance requirements of the German financial sector.

Learn how to build a multilingual text classification pipeline using multilingual LLM embeddings and Scikit-learn, without training separate models for each language.

Agent Substrate is an open source, high-density agent runtime that can run scale to millions of sandboxes on a single cluster.

Learn how to design zone-resilient Azure workloads by choosing the right availability zone strategy for each component, balancing reliability, cost, and operational complexity.

Learn how Distributed GraphFlow scales GNNs for Autonomous Network Operations. Simplify your end-to-end GNN modeling with Google’s new open-source library.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Comparing models on dollars per million tokens misses what production workloads actually pay for: outcomes. This post shares an open-source benchmarking harness that measures cost per correct answer, agent trajectory cost, and rubric-graded deliverable quality across OpenAI models on Amazon Bedrock.

A Blog post by IBM Research on Hugging Face

Deploy a customer-operated LiteLLM gateway on Amazon ECS with AWS Fargate, connect it to an OpenAI model on Amazon Bedrock, and configure Codex to route requests through the gateway's Responses API with scoped identities, budgets, rate limits, and telemetry. We also compare direct IAM Identity Center access and a managed Portkey deployment.

Learn how Azure Local and Azure Arc help manage infrastructure across edge locations, multi-cloud environments, and sovereign deployments.

AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt optimizer's reflector engine works and shares benchmark results for the Single Agent and Sub-Agent Reflectors.

Learn what happens when you run a Docker container. Understand image layers, namespaces, cgroups, and networking to prepare for Docker interviews

Retrying a failed call sounds simple until you retry the wrong error, or every client retries at the same moment. Both cost more than the original failure did.

Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconciles demand surges against live supplier availability and places replenishment orders unattended, escalating to a human only when no supplier can cover a surge.

TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers, and serving layer already assembled. This post walks through deploying a vision-language model on Amazon EKS using the Ray Serve DLC on a single GPU node.

One sentence in a prompt stopped a model inventing answers entirely. Adding citations on top made it slightly worse, and the citations it did produce could not be trusted without checking them.

Amazon SageMaker Feature Store now supports feature-level writes. With the new UpdateRecord API, you can update one or more feature values in a single call without reading or rewriting the entire record. It is available for both the Standard (Amazon DynamoDB) and In-Memory (Amazon ElastiCache) online store tiers.

Amazon SageMaker AI now offers instance preference lists for training and processing jobs. Specify an ordered list of up to five instance types, and SageMaker AI automatically launches on the first type with available capacity, eliminating manual retry loops and capacity-watching scripts.

Amazon SageMaker HyperPod now supports model caching for inference, which pre-loads model weights and container images onto cluster nodes so pods read from local NVMe storage instead of downloading over the network. Learn how model caching cuts cold starts from tens of minutes to seconds, how it works, and how to enable it.

This November, the cloud native community is heading to Salt Lake City. From November 9–12, 2026, KubeCon + CloudNativeCon North America will bring together adopters and technologists from across open…

“A sales guy writing code” used to be the lead-up to a joke. But now no one’s laughing. Designers used to sit meekly waiting for the high priests of code to make their designs real. Now they don’t…