Jignesh Shah

Get to know Gemini in Databases: an #AI-powered assistant that helps across all stages of the database journey and simplifies all aspects of database operations with features like Database Insights, Database Migration Service, and more. #GoogleCloudNext

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Elevate your Elastic game with our webinar focused on migrating from Elastic Cloud Enterprise (ECE) to Elastic Cloud on Kubernetes (ECK). ☁️ Learn migration strategies, advantages of managed Kubernetes platforms, live demos, and post-migration best practices. https://gag.gl/bodqQv #ECE #ECK #Webinar

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New Episode: 260: Amazon Dispatches AWS CEO Adam Selipsky with Prime 2-day delivery Episode 260 of The Cloud Pod podcast, bringing you all the latest news from Cloud and AI including AWS, Azure, Google, OCI, GPT-4.o, C7i-flex, AWS CEO Changes and Amazon Polly #aws #gcp #azure #cloud #cloudpodcast #podcast

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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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Discover the benefits of using Kubernetes-based Horizontal Pod Autoscaling (HPA) in CloudHub 2.0 to automatically adjust the number of pod replicas based on workload demands, ensuring optimal resource utilization.

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Learn how #AutonomousDatabase fits in a multicloud architecture with the new Oracle Database@Azure and discover its openness and ability to simplify and accelerate application development. https://lnkd.in/gJ5uYgYV

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With AWS Machine Learning capabilities now easily accessible, individuals can build cutting-edge models that deliver real value with minimal effort. However, once you’ve proven a small use case, how do you scale and operationalize your models for enterprise use? To take a project from concept to production-ready, organizations need to incorporate enterprise-grade functionality—like tracking code changes, enforcing security standards, and ensuring policy and governance compliance. Using Terraform to build and manage the lifecycle of an ML/AI platform on AWS provides a scalable approach to address these requirements. Terraform can help orchestrate your infrastructure, ensuring your ML models are production-ready and enterprise-compliant. #MachineLearning #AWS #Terraform #AIOps #DevOps #CloudInnovation

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Cheaper, Faster *and* Fully Managed ! Sounds too good to be true ? Check out how AlloyDB for PostgreSQL delivers 2x price/performance and 4x performance compared to Self-managed PostgreSQL. #alloydb #gcp #postgresql

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Super cool News in this August 1st! Snowflake Snowpark Container Services is out in GA on AWS, and on Preview on Azure. What is Snowpark Container Services? ❇ A fully managed container offering designed to facilitate the deployment, management, and scaling of containerized applications within the Snowflake ecosystem. ❇ Enables users to run containerized workloads directly within Snowflake, ensuring that data doesn’t need to be moved out of the Snowflake environment for processing. ❇ Allows for the seamless execution of OCI images, leveraging Snowflake’s robust data platform. This is a nice news as it allows many use cases in Production, your applications and LLMs inside your own container and Snowflake applications that use SCS. Well, you can now compute pretty much anything close to the data. No more data moving around. #snowflake #infostrux #datasuperhero #snowflake_advocate #containers #kubernetes https://lnkd.in/gefkeh_M

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My newest blog post describes how we still work to improve the performance, security, and internal efficiency of the very first #AWS service: "Optimizing Amazon Simple Queue Service (SQS) for speed and scale" - https://lnkd.in/gjjk76Bn

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If you'll be at the #DataAISummit, join Ashok Singamaneni and myself (Scott Haines) as we teach you the ropes of building "Effective Lakehouse Streaming with Delta Lake and Friends". https://lnkd.in/gqmcJmRC We'll be teaching lessons learned (the hard way), and showing how streaming-first is the correct fit for "most" if not all your workflows. Learn to leverage #DeltaLake like an expert, and we'll introduce you to some effortless patterns for making your streaming journey a breeze. You'll also hear from Ashok Singamaneni as we talk about how to leverage painless workflow orchestration with #brickflow, and how to build data trust-networks using #sparkexpectations. #spark #deltalake #sparkexpectations #brickflow #nike #oss #dataai

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Oracle Database 23ai, previously known as Oracle Database 23c, is now Generally Available. Get an inside look at some of the major features and learn where you can download the software. https://lnkd.in/gzdApb57

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Scale at ease, Lower cost & Future proof

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Cloud Compute Costs giving you a pain in the neck? Xosphere is the cure. Typical customer savings is 50-80%. For a consultation and savings analysis, visit: https://lnkd.in/g-JegB6F #ec2 #aws #kubernetes #k8s #costoptimization #finops #gcp #googlecloud #SpotVM #GoogleCloudConsulting Xosphere FinOps Foundation

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Thrilled to share our latest blog from OCI Data Science Team! In this post, we walk through how we built a state-of-the-art enterprise chatbot using the cutting-edge capabilities of OCI Data Science, Oracle Database 23ai, and Oracle Digital Assistant, backed by LLM models with the LangChain pipeline for RAG. From foundational AI models to creating a seamless conversational experience, this blog covers it all. Special thanks to Piyush Gajjariya (Thacker), Tzvi Keisar, Ashutosh Kumar Jha and SriRanjith R from OCI Data Science. Check it out here: [https://lnkd.in/dAudXG4J] #AI #Chatbots #OCIDatascience #EnterpriseAI #Oracle, #OCI, #oracle_database_23ai, #oda, #langchain, #rag, #LLM

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