Jason Smith

Super excited about this talk! I'm going to dive into some of the work we've done under the covers in AWS, in services like Lambda, Aurora, and DynamoDB, to make them even more resilient, and how to apply those same techniques in your own systems.

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Google Cloud Vertex AI is rolling out multiple updates to make AI accessible for every enterprise. Up to 85% lower input costs and 80% lower output costs, and 100+ new languages coming to Gemini 1.5. #GoogleCloud #VertexAI #Gemini

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With MongoDB, we help engineering leaders get off the modernization hamster wheel and embrace predictable, optimised spending that fuels their most ambitious initiatives. With powerful features like automated cluster sizing, on-demand pausing, and granular spend visibility, MongoDB Atlas helps you right-size your data infrastructure and take complete control of your IT costs. Perfect way to break free from the constraints of economic uncertainty and get easier budget approvals. This blog helps you understand how MongoDB Atlas can help you take better control of your data costs. #MongoDB #cloud #innovation

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Google Cloud Vertex AI is rolling out multiple updates to make AI accessible for every enterprise. Up to 85% lower input costs and 80% lower output costs, and 100+ new languages coming to Gemini 1.5. #GoogleCloud #VertexAI #Gemini

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Google Cloud Vertex AI is rolling out multiple updates to make AI accessible for every enterprise. Up to 85% lower input costs and 80% lower output costs, and 100+ new languages coming to Gemini 1.5. #GoogleCloud #VertexAI #Gemini

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Introducing the Google Cloud Private Marketplace, now generally available. Private Marketplace allows cloud administrators to create a curated collection of vetted software and solutions that integrate with Google Cloud and align with your organization’s cost, security, and compliance policies. Empower your end users to explore pre-approved tools without compromising on governance and cost control. Read the blog to learn more. #GoogleCloudMarketplace

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No one wants to get Coinbase’s $65 million observability bill in the future. Sure, observability comes with a necessary cost. But that cost cannot exceed the concrete and perceived value on balance sheets and leaders' minds. sofia fosdick shares practical insights on curbing high observability costs. She’s a senior account executive at Honeycomb.io and has held similar titles at Turbunomic, Dynatrace, and Grafana. Check out what she had to say via: https://lnkd.in/geB3MucE #observability #sitereliabilityengineering #devops #platformengineering

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This was a great episode of the Continuous Delivery Foundation CD Pipeline. Check out this clip and then get yourself over to the full recording https://lnkd.in/eyxikhX7

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When I first got into 𝐠𝐫𝐚𝐩𝐡 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬 a very smart engineer explained to me why the combination of 𝐠𝐫𝐚𝐩𝐡 and 𝐬𝐞𝐚𝐫𝐜𝐡 is a match made in heaven. This is one of the reasons I love the work the Spanner team is doing in bringing some of Google's differentiated text search capabilities to Spanner Graph! Read about it in the following blog post... #databases #graph /cc Google Cloud

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Planning to be in #NYC for the #AWS Summit? Here is an opportunity you won't want to miss. Bloomberg is hosting a hands-on workshop, together with Amazon Web Services (AWS), where you can learn how to build a compute intensive workflow natively in the Cloud. You'll learn the fundamentals of how the Bloomberg API integrates natively in the cloud and how to create a robust and scalable reference architecture using AWS services which is capable of handling a large volume of #streaming data. This event will focus on Options and Implied Volatility but the integration and architecture is applicable across multiple use-cases. #Data #StreamingData #DataStreaming #AWSSummit Register here: https://lnkd.in/gRgA83ar

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It has been a week since Amazon Web Services (AWS) announced our AWS Generative AI Accelerator and applications have been flying in 🚀🚀🚀 I can't share how many startups have applied, but it definitely has been the most active and exciting of our accelerator launches 🤩 What is awesome about this accelerator is that it's truly global, so startups from anywhere around the global can apply 🌐 As long as your startup is building a tech or tech-enabled product, has a tech lead, a working product, and is still early stage (not raised a Series A), then you are eligible for the program ✍️ Learn more about the program and apply using the link in the post below and remember to submit your application before 11:59 PM ET July 19 📌 #startups #AWS #GenerativeAI #accelerator

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This is a must see - 5mins of clear articulation of how and why Google Cloud differentiates in #GenAI with an unique approach and strategy relative to competitive #hyperscalers https://lnkd.in/gywMw7Dp

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My first boss at Amazon was Anurag Gupta. When he was leaving Amazon he asked me to write two papers: one that describes the “new” Amazon Redshift after we completely changed the architecture of the system, and one that presents how a typical cloud data warehouse workload looks like. We did write the Amazon Redshift ReInvented paper that presents the “new” Redshift and published it at SIGMOD’22 (https://lnkd.in/gK3J_CZQ), but we didn’t get to write the second one. I am pleased to say that Tim Kraska and his team, Dominik Horn, Pascal Pfeil et al, wrote the second one and they published it at the upcoming VLDB’24 conference: https://lnkd.in/gC3kcWsZ . This paper is an important scientific contribution as it anaylzes the production workload of a major analytics system, such as Amazon Redshift, and quantitatively compares the real world against the standard industry benchmarks (TPC-DS and TPC-H). There are so many interesting insights from this paper. For example, in the real world only a little less than 50% of the executed statements are read-only SELECTs, whereas in the benchmarks the SELECTs are between 75% to 80%. If you are attending VLDB’24 make sure to attend the presentation of this paper. To further help the scientific community, along with the paper the team is releasing the Redset, which is a dataset containing three months worth of user query metadata that ran on a selected sample of instances in the Amazon Redshift Provisioned and Serverless fleet: https://lnkd.in/gCcyyhZT . Looking forward to seeing how the community will use these traces. #vldb24 #redset #redshift #realworkloads #tpc

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Welcome to #GoogleCloudNext! Read Google Cloud CEO Thomas Kurian's blog for an overview of all the important advances and significant announcements across every aspect of Google Cloud.

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Excited to present insights from Jay Kreps, our CEO of Confluent and co-creator of Apache Kafka, on the transformative power of data streaming: - Data streaming is revolutionizing business operations, with 72% of IT leaders already leveraging it for mission-critical systems. - Apache Kafka addresses pivotal challenges in data integration and streaming, providing a scalable platform to break data silos. - Real-time AI applications depend on data streaming for cutting-edge capabilities, impacting bottom lines by optimizing operations and enhancing customer experiences. Stay tuned for more insights! #DataStreaming #ApacheKafka #RealTimeAnalytics #AI #ConfluentLeadership

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The speed at which these models improve is staggering, so is the cost to build them. Only way to keep up is to leverage principles such as AWS Bedrock so you have the flexibility you need to quickly select the model that works best for your task. https://lnkd.in/gNAR63YC https://lnkd.in/g_FtP6e9

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