Karl Rautenstrauch

Today at #ReutersNEXT, moderator and broadcast journalist Richelle Carey sat down with NetApp Senior Vice President & General Manager, Krish Vitaldevara on the crucial role data infrastructure plays in shaping the future of business. In today's rapidly evolving industry landscape, data has emerged as the primary catalyst for innovation. However, the true challenge is in preparing data to be AI-ready. During the interview, Krish discussed the transformative role that intelligent data infrastructure plays in enabling businesses to take advantage of #AI and drive growth: https://ntap.com/3ORh8qC #IntelligentDataInfrastructure #GenAI #NetApp

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Customers have been asking for governance around data in motion. Now, Amazon Kinesis Data Streams supports data plane logging to AWS CloudTrail: https://lnkd.in/e5EEJE9x #governance #datainmotion #data #datagovernance #Kinesis

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Incredibly proud of the latest Kinesis Client Library version (3.0) which, when compared to previous KCL versions, reduces compute costs by up to 33%. KCL 3.0 introduces an enhanced load balancing algorithm that continuously monitors resource utilization of the stream processing workers and automatically redistributes the load from over-utilized workers to other underutilized workers. This ensures even CPU utilization across workers and removes the need to over-provision the stream processing compute workers which reduces cost. Additionally, KCL 3.0 is built with the AWS SDK for Java 2.x for improved performance and security features, fully removing the dependency on the AWS SDK for Java 1.x. #Kinesis #DataStreaming #KCL

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Learn how to deploy fine-tuned #LLM inference containers on #OKE, an #OCI managed #Kubernetes service that simplifies deployments and operations at scale for enterprises. https://lnkd.in/gpHuUa8F

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In my latest blog post, Brent Eager (from StormForge) and I talk about how they use Amazon Managed Service for Prometheus to manage their Optimize Live solution. https://lnkd.in/gFXUzX9n

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If you missed our live session with Jon Fortt of CNBC, here is another chance to check it out. Pure Storage CEO and Chairman, Charles Giancarlo and LandingAI CEO, Andrew Ng, talked about our partnership, and what it will mean for the future of Large Vision Models. #data #DataCenter #AI #ML #LLMs #LVMs #DataAnalytics

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Andrew Ng, Jon Fortt, and Charles Giancarlo discuss AI innovations! Discover more about Pure Storage's strategic investment in LandingAI and their collaboration on multi-modal Large Vision Models (LVM) to advance vision AI for enterprises. Watch below!

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Anton Weiss has written an excellent article that dives deep into its value, implications, and trade-offs. https://hubs.la/Q02-HysL0 #Kubernetes #AWS #EKS #CloudOptimization #awsreinvent #awspartner

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We're hosting a free event in Atlanta on June 18th on how to improve resilience, security and costs on your AWS accounts. The post below has more information and registration for this event! Look forward to seeing you! Amazon Web Services (AWS), #cloudcomputing, #cloudresilience, #cloudsecurity, #cloudoptimization Sailesh Kadam, Agasthi Kothurkar

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Are you an AI Leader or AI Laggard? NetApp's just-released 2024 Cloud Complexity Report offers some surprising insights into how enterprise IT is adapting the challenges of AI - I take a look in my latest on Forbes. https://lnkd.in/gUtR2rMn

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How does data fuel AI? George Kurian identified three key patterns in this recent video on the NetApp Q4 earnings: 1. TRAINING: AI training environments require large scale data storage to train the models. Business often use multiple models, and will want versioning, controlled access, and identification of which data sets were used for training for regulatory and compliance purposes. 2. GENERATIVE AI: Generating data (e.g. GenAI) requires high performance data storage, but any business knows that this can get expensive, fast. IT leaders will look to run cost effective data infrastructure that is not only highly performant, but also highly secure. 3. INFERENCING: Inferencing is the future of AI. Businesses will want to integrate their AI models across the edge/cloud/datacentre to access enterprise data to better serve customers. Data security and data access is key here as AI provides a serious competitive advantage to those organisations who get it right. While the world is talking about GPUs and compute (and lack of), data storage is the fuel that feeds the machine. Which of these three patterns are most useful to your business? #NTAP #ArtificialIntelligence #IntelligentDataInfrastructure

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Stack Your Enterprise's Odds for Success: From Pilot to Production with Chad Hendren | Consulting Field Solutions Architect @ Pure Storage. Join us for this can't-miss session as Chad delves into turning your AI initiatives from experiments into scalable solutions that drive tangible results. 🗓️ Date: Oct 11 🕒 Time: 11:15 AM - 11:35 AM ET 👉 Register here: https://lnkd.in/eDPSxQjA #AI #AIProduction #ExecutiveAI #DataDriven #COLLIDE2024 Data Science Connect

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These CloudOps and Security sessions are really good. If you are an AWS Cloud Ops partner, you should definitely check these out!

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I have been speaking at the openshift commons about cloud provider failures and how to survive them. Have a look at the video below

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Data Classification excellent for customers and so easy to demo! Other solutions take months and tens of thousands in services to roll out.

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Exodus from the Cloud environments is real. Companies can save millions by doing this, so yeah, it's a viable strategy. From this perspective it does seem that hard coupling to a specific Cloud managed services like AWS Lambdas or Azure Functions and many others looks like a bad architectural decision. I mean, you want to be able to swap tour Cloud provider, not your database (as many developers still like to believe). https://lnkd.in/dfcUDCNa

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