Nathaniel (Niel) Bornstein

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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Market Context: Kubernetes, Hyperscalers, and Red Hat OpenShift My take on the news announcing the integration of Red Hat OpenShift on Oracle Cloud Infrastructure (OCI), merging a leading Kubernetes platform with a top distributed cloud. This collaboration supports configurations of Red Hat OpenShift on OCI, providing customers with flexible, cost-effective, and secure deployment options across multiple cloud environments. The partnership enhances enterprise capabilities for managing scalable, distributed applications, and supports AI and ML workloads, signifying a substantial advancement in cloud computing and container orchestration technologies. Read the full article here 👇 https://lnkd.in/eheeyHmG

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Still doesn't do distributed tracing like I built at AppDynamics. Dynatrace also has tracing. This new Elastic solution lacks it. The rest of it looks pretty comprehensive > Elastic's full-stack observability experience for your SAP workloads

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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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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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DB2 modernization is as easy as …..

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That explains the Terraform's license changes from Opensource to BSL - Hashicorp acquired by IBM (~ $6.4B). Considerations for technology leaders: 🔹 Impact on IaC automation strategy using Terraform or OpenTofu (Opensource fork of Terraform), or Opensource solution like Pulumi? 🔹 Integration of Terraform with Red Hat OpenShift and Ansible Automation Platform: considering both are under the same umbrella 🔹IBM Cloud Integration - will Terraform continue to have similar support for other Cloud providers? 🔹 Terraform Cloud: will AWS remain the primary hosting provider or long-term shift towards IBM Cloud? 🔹Will you open up for another Cloud provider with IBM Cloud Services as cross-sell opportunities?

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Oracle Identity Governance versus Oracle Access Governance. 👉 Similarities, differentiators, and resources: https://lnkd.in/gAjvte4G

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https://lnkd.in/gKBfKEeq "In a first among database vendors, Oracle has added support for LLMs inside a database, analysts said. HeatWave Gen AI’s in-database LLM support, which leverages smaller LLMs with fewer parameters such as Mistral-7B and Meta’s Llama 3-8B running inside the database, is expected to reduce infrastructure cost for enterprises..." #HeatWave #GenAI #GenerativeAI #OCI #OracleCloudInfrastructure #Vector #VectorProcessing #VectorDB #RAG #SimilaritySearch #LLM #LLMs #InDatabase #Oracle #MySQL #AWS #Snowflake #BigQuery #Databricks #integrated #automated #AI

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Where do you start with adopting #Kubernetes? How do you successfully navigate the path to Red Hat OpenShift? On the blog, Thomas Keenan turns to Capgemini CTO Jonathan Le Lous for his adoption advice – Read on!

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After the adquisition of Hashicorp by IBM, I think we are going to see many movements aimed at a purely opensource approach.

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Are you struggling to architect and efficiently manage #ApacheSpark in a Red Hat #OpenShift environment? Check out this blog to learn how the NetApp Instaclustr enterprise support team of Spark experts can help. Red Hat Partners

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Image mode for Red Hat Enterprise Linux allows you to use the same tools, skills and patterns as containerized apps, so ops and infrastructure teams can speak the same dialect as developers. Get your hands on AI-ready Linux: #RHSummit #AnsibleFest

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In the world of storage for EDA, what matters is time it takes to complete scheduled jobs reliably and *consistently*, not how many iops on spec sheets. Talk to us if you want to know more. #ontap #eda

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How has cloud native technology evolved? What challenges face platform engineering today? Alexis Richardson discusses these critical topics in Giant Swarm's new #GiantConversations episode - https://lnkd.in/d-RU2xpn #platformengineering #kubernetes #cloudnative #opensource

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New Episode: 266: AWS Billing Finally Comes into FOCUS https://bit.ly/3VSrOsh Episode 265 of The Cloud Pod podcast, bringing you all the latest news from Cloud and AI including AWS Billing, Azure, Google, Kubernetes, FinOps, FOCUS, and WWDC #aws #gcp #azure #cloud #cloudpodcast #podcast

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Learn how to optimise Apache Kafka Consumers for better performance and cost efficiency. Discover key configurations, metrics, and practical tuning strategies.

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