Cloud Combinator’s Post

🚀 🎉 Introducing Vertical Relevance's Dependency Mapper: a fast way to make complex codebases transparent—mapping real dependencies, surfacing hotspots, and generating living documentation so teams can #modernize, #migrate, and #refactor with confidence! Powered by Amazon Web Services (AWS) Bedrock, it layers secure #GenAI on top of deep #codeanalysis to recommend refactors, flag risks, and auto‑produce architecture summaries. The business impact: ✅ shorter timelines, ✅ fewer regressions, ✅ lower TCO , and ✅ faster onboarding across teams! https://lnkd.in/dgnmmMxF Amazon Web Services (AWS) | AWS for Financial Services | AWS Partners | #AWS | #GenAI | #amazonbedrock | #bedrock | #AI | #AppMod | #migrations | #APNProud | #data | #financialservices | #verticalrelevance | #Premiertier

Simpler, Safer AWS Integration for Generative AI Lab Users. With Generative AI Lab 7.5, managing data on AWS just got easier. The platform now supports EC2 instance role–based access to Amazon S3, meaning users no longer have to enter or store S3 credentials when importing or exporting data. With Generative AI Lab on AWS, the platform now authenticates automatically using your EC2 instance’s IAM role, the same secure method AWS services use internally. This means... It's more More secure – eliminates the risk of exposed credentials. A simpler setup – no manual configuration or key management. You get AWS-native workflow – seamless, permission-based access to your S3 buckets. This small change makes a big difference: faster setup, fewer errors, and one less thing for teams to worry about when running Generative AI Lab on AWS. #GenerativeAI #AWS #AWSPartners #AmazonS3 #AmazonEC2 #AIonAWS #MLOps #CloudSecurity #JohnSnowLabs #AWSIntegration #HealthcareAI

Azure Container Storage v2.0 is 7x Faster, Open Source, and optimised for AI & databases. Azure Container Storage has just received a significant performance boost. With v2.0, Kubernetes workloads now benefit from up to 7 times higher IOPS, 4 times lower latency, and improved efficiency on local NVMe drives. Whether you’re running databases, AI inference, or development and test environments, this release delivers enterprise-grade storage performance with cloud-native simplicity. Read on for more: https://lnkd.in/ez9Dzhfw #Azure #AI #Databases #OpenSource

🚀Unlock seamless deployment for your PyTorch models with TorchServe! 🚀 ✨️If you've built a powerful PyTorch model but struggle to launch it into production, TorchServe is the robust solution trusted by industry leaders for scalable AI model serving. Backed by AWS and the PyTorch team, TorchServe streamlines everything from model management to scalable, production-ready inference. 💢Key Benefits of TorchServe: ✅️REST APIs & Batch Inference: Easily access your models through standard APIs, with batch support for high-volume use cases. ✅️Dynamic Model Management: Versioning, monitoring, and seamless updates—no server restart needed. ✅️Production-Ready Scalability: Run multiple models and versions, A/B test, and auto-scale with Kubernetes or your favorite cloud provider. ✅️Custom Workflows: Integrate custom handlers for pre/post processing, add business logic, and support for both TorchScript and eager execution modes. ✅️Metrics & Monitoring: Built-in health checks, Prometheus-compatible logging, real-time stats, and easy troubleshooting. 🌀TorchServe can be deployed on AWS SageMaker, Azure ML, Google Cloud, or any containerized/self-managed infrastructure, making it highly adaptable to various business needs. Whether you’re scaling up to millions of users or running experiments in the lab, TorchServe makes PyTorch deployment hassle-free. 🌀Supercharge your AI journey—deploy smarter, scale faster, and manage effortlessly with TorchServe. #PyTorch #TorchServe #AIDeployment #ModelServing #MachineLearning #AIProduction #AWS #OpenSource

Amazon Web Services (AWS) and OpenAI have entered a $38B multi-year strategic partnership under which OpenAI will leverage AWS’s world-class infrastructure. It reaffirms the strategic role AWS is playing in supporting frontier AI innovation while signalling that the compute demand of tomorrow’s models is already here — and we are building to support it. For our customers and partners, this is a powerful message: when you’re looking to build and scale next-generation AI, AWS is the platform of choice. https://lnkd.in/ew3ijTmE

Amazon Bedrock is not just another cloud service, it's set to revolutionize AWS as we know it 💥 AWS's new leader in the AI race, Bedrock, has the audacity to challenge EC2—the very backbone of AWS—with its potential to create a tectonic shift across industries. As AWS invests heavily in AI infrastructure, doubling its power capacity every five years and rolling out the next-gen Trainium 3 chip, Bedrock stands out, offering a smorgasbord of AI models from OpenAI, Anthropic to Mistral, that's not just flexible but downright formidable. It's like comparing a finely-tuned orchestra to a single, albeit powerful, instrument. Here's the rundown: 🟠 **Potential Juggernaut**: AWS CEO sees Bedrock matching or even outgrowing EC2's monumental footprint. 🟠 **Model Diversity**: A vibrant ecosystem featuring AI from OpenAI, Anthropic, and Mistral, promising tailored solutions for complex business challenges. 🟠 **Infrastructure Independence**: Built on AWS's custom Trainium chips, ready to empower businesses with more bang for their buck and bigger workloads. 🟠 **Strategic Investment**: Overhauling infrastructure with double power to support AI vision—Bedrock's steely growth plans are no pipe dream. Is Bedrock the revolution AWS has been brewing, or just another buzzword-laden attempt at glory? Is it time for us to re-think what the real heavyweight machinery at AWS might become? 🤔 #AWS #AmazonBedrock #AITransformation #CloudComputing #InnovateOrDie 🔗https://lnkd.in/epWwdT5s 👉 Post of the day: https://lnkd.in/dACBEQnZ 👈

AI and AWS light up Amazon’s Q3 — but there’s more behind the numbers. Read the full story. Link in comment. Andy Jassy #e4m #Amazon #AWS #ArtificialIntelligence #Earnings #Q3Results #BigTech #CloudComputing #AIInnovation #BusinessGrowth

Amazon Web Services (AWS) has launched microcredentials on AWS Skill Builder, a new way to validate hands-on skills through real world, lab-based assessments. I tried the Agentic AI Microcredential today, focused on building intelligent, goal-driven agents using Amazon Bedrock and AWS Lambda. As a Technical Account Manager, I really value this approach. No multiple choice, just practical labs that mirror real customer use cases. It’s all about learning by doing, something I strongly believe in, and a great way to keep technical skills sharp. If you’re curious about Agentic AI or want to test your hands-on expertise, check it out on AWS Skill Builder. https://lnkd.in/daGcJ7br. #AWS #AgenticAI #Microcredential #AWSTAM #Serverless #Bedrock #AWSCommunity #CloudComputing

Amazon Web Services (AWS) has added interactive incident reporting to Amazon CloudWatch, giving engineers an AI-assisted way to investigate, analyze, and document system events. The new capability automatically gathers telemetry, correlates data, and generates detailed post-incident reports with timelines, impact assessments, and actionable recommendations. Learn how AWS is using AI to streamline post-incident analysis and improve operational health: https://lnkd.in/dFStbbtx #AWS #CloudComputing #Observability #AIOps #CloudWatch

Amazon Web Services (AWS) just released two new microcredentials: AWS Agentic AI and AWS Serverless - both are 90-minute hands-on labs. Just passed the Agentic AI one! It covers Bedrock agents and multi-agent collaboration. In my opinion, much more interesting than traditional multiple-choice - you actually build and fix real systems under realistic, work-like pressure. The Serverless one is next on my list. So far, I can recommend this practical format over memorizing theory. 🔗 Agentic AI: https://lnkd.in/dJfWufi4 🔗 Serverless: https://lnkd.in/de74NkKa #ContinuousLearning #AWS #GenerativeAI #AgenticAI