Leah Shalev

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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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/eSnkkSX9

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This was great InfoQ reporting on Karpenter 1.0 from Matt Saunders: "Karpenter automatically provisions new nodes as needed, responding to unschedulable pods in real-time. By dynamically adjusting cluster compute capacity, it optimizes both performance and cost-effectiveness." https://lnkd.in/ezJYJUJN

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🎙️Got a chance to chat with Gwen (Chen) Shapira on building Nile, a multi-tenant *first* database. This was such a fun conversation: ranging from the architecture of Nile to tackle the ubiquitous problem of multi-tenant sharding in a scalable way, Gwen's experience building cloud services at Confluent, and what it means to build a database to support modern RAG techniques in the age of AI. Full episode in the comments!

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We’re excited to announce vector search on both the new Memorystore for Valkey and Memorystore for Redis Cluster, combining 1) ultra-low latency in-memory vector search, with 2) zero-downtime scalability (in or out), and 3) powerful high performance vector search across millions or billions of vectors. #databases #valkey #redis Google Cloud

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Just in time for #Climateweek2024! Thank you to the The New York Times for spending some time with me and Pure Storage to discuss how the global hunger for #AI is driving a need for new ways of recording, storing and managing data. It is all going to come down to #efficiency and using better science to solve hard problems. "As the leaders of business in this new era, we have a responsibility to build A.I. in a way that is sustainable, responsible and scalable to support our future." #ESG #DataPlatform https://lnkd.in/gBBZ3Q7p

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In another galaxy IBM acquired Broadcom 😀 , but in MilkyWay Galaxy IBM will acquire Hashi for $6.4 billion 🤑 well, Terraform has a new home, will this be terrifying or justifying for Hashi Customers? we can have some delays but hope Apache V2.O will be the future of Terraform or we can see a drift detection of Terraform with Crossplane. Looking forward to an insightful conversation in the comments, well I believe with this move IBM is a Redbull of Platform Engineering Formula 1. I'll be up in the move to cover some grounds and will get back with some more insights while talking to subject matter expert guests and kind of a good space to get in touch with experts for a podcast, don't be terrified of IBM terraforming the terraform. Read more: https://lnkd.in/dwj_2kBJ #hashicorp #ibm #terraform #opensource

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This is a very good talk of a practical example of using formal methods in AWS.

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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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For those interested in how cloud scale database systems work, below is a deep dive on Amazon MemoryDB. MemoryDB delivers microsecond-level read latencies, and throughput in the hundreds of millions of queries per second, while offering multi-AZ durability with automatic failover.

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JFrog and NVIDIA to deliver a single source of truth for your NIM models

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The job roles below will be in demand again. Innovations like #containers, #eBPF, #webassembly, #unikernel, #microVM, #k8s, etc., made running infrastructure in a #baremetal environment as feasible as a cloud. Architectures like microservices, atomic components, zero-trust, CDI (composable disaggregated infrastructure), etc., made it possible to efficiently handle bare metal. New Technologies like LLMs and the increased need for traditional ML are creating the need for heavy machines with GPUs, TPUs, etc. You got the point! So, if you want job security and a long-term fun hands-on job, these roles/duties will be to your advantage, and you’ll start seeing more demand again for these roles: - Data Center Engineer (both hardware and software) - Systems Engineer / Infrastructure Engineer - Automation (IaC) Engineers (alias devops/devsecops) who know how to write IaC code with Ansible, Nix, Terraform, Pulumi, Python, Go Lang, Rust, Rix - Automation Testing using concepts and tools like, testcontainers, chaos engineering, security chaos engineering, and the ability to build testing frameworks - ML & LLM developers in Python and Rust (more towards using Rust for the future) - platform / infra / systems engineers who can write automation using golang, rust, and python It’s never too late to learn something new and change your job, especially if you have industry experience. Use it to your advantage first! #devops #devsecops #kubernetes #cloudnative #softwaresupplychainsecurity #jobmarket #softwareengineer #aisoftwareengineer #capten #captenai #agnosticengineer #enableengineer #iac #infrastructureascode #platformengineering

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Thr `jets exec` command runs bash commands in the deployed AWS Lambda env. It’s like a REPL for lambda. It’s useful for debugging https://lnkd.in/gQ4Gnfig #rubyonjets #rails #aws #serverless

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AWS Graviton4-powered R8g instances are now GA! I did some tests on these back in February, with .NET 8 (specifically ASP.NET Core), and as with Graviton3, it shines under heavy load with multi-threaded workloads (like web apps built on ASP NET Core). Graviton4 is faster, with better cache performance, and is based on arm's Demeter V2 core. R8g instances also support up to 50 Gbps enhanced networking bandwidth, and lots of other spec bumps besides. Do some comparison testing for your memory-intensive apps! https://lnkd.in/gRqmYGv6

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New to OCI #AI Infrastructure: Midrange #OCI Bare Metal Compute with NVIDIA L40S and VMs with NVIDIA H100/A100: https://lnkd.in/eHVhC-nr

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