Victor Rojo

The first version of the new Dynatrace Distributed Tracing app allows you to easily analyze trace data with: Enhanced visualization for deeper insights Automatic data capture for seamless analysis OpenTelemetry integration for better trace data utilization Kayla Bondy and Thomas Rothschaedl provide a walkthrough of our latest app here.

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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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Straight from Mexico to Brazil. Obrigado por me receberem aqui hoje, Sao Paolo! Following Microsoft’s Mexico City AI Tour, today marked another great AI Tour in Sao Paulo, Brazil and my first visit ever to South America and Latin America’s largest economy. Our CEO, Satya Nadella, once again opened the day with a powerful reinforcement for the Microsoft Mais Brazil program (originally announced in 2020). Over the next three years Microsoft will invest $2.7B in Brazil to enhance its cloud infrastructure and AI, as well as offer AI training to 5 million people. With Brazil on track to become one of the world’s largest GitHub communities, I was very excited to speak more about what it takes deliver value from intelligent apps. Joined onstage by Paulo Cocato, Head of Artificial Intelligence at Vivo, Telefónica’s Group commercial trademark in Brazil, we discussed how AI can: - reshape business processes and operations to be more efficient and more intelligent.  - enrich the employee experience.  - ensure customer and partner experiences more engaging and personal.  - accelerate product innovation to deliver completely new experiences and solutions for end users. In his keynote, Satya reinforced our commitment "to supporting the AI transformation in Brazil and ensuring it benefits everyone.” Brazil has been at the forefront of every major wave of technology, from web to mobile to cloud. Surely it will once again be a strong leader in the shift to AI.

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Microsoft's AI model, Aurora, quickly predicts levels of six major air pollutants worldwide, including carbon monoxide and particulate matter. Read more in this article from Nature. #msftadvocate #ai https://lnkd.in/g-AppzdB

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Graphs offer unparalleled potential for uncovering and leveraging intricate data relationships, driving deeper insights. However, the management of separate graph databases has historically hindered the realization of comprehensive, integrated analytics. Spanner Graph promises to revolutionize this landscape by seamlessly incorporating graph capabilities, thereby unlocking new avenues for data-driven value creation. #graphdatabases #googlecloud https://lnkd.in/dbkYMGYA

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Being here at "Google for Brazil" this week, one thing is clear - the region's growing digital footprint is palpable. However, with this global attention, Brazil has also caught the eye of more cybercriminals - including targeting from government-backed groups from the People’s Republic of China, Russia, and North Korea. That's why today Google security teams TAG and Mandiant (part of Google Cloud) have released a new blog detailing their collective understanding of the Brazilian threat landscape. Our hope is that by sharing our global perspective, we can enable greater resiliency in mitigating these threats: https://lnkd.in/edWKd9MV

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Redshift Serverless just became better with the GA of AI scaling and optimizations.

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In 2013, Jay Kreps introduced the concept of the log as a fundamental abstraction for real-time data streaming, paving the way for platforms like #ApacheKafka. Over the past decade, the data streaming landscape has undergone a remarkable transformation, particularly with the rise of cloud-native environments and the integration of scalable object storage solutions like Amazon S3. This evolution has given rise to platforms like #ApachePulsar, each offering innovative approaches to log storage and data streaming. In our latest blog post, we explore the evolution of log storage implementations in data streaming and categorize this architectural journey into three distinct stages: 💡 Leader-Based Architecture Leader-based architectures form the foundation of most data streaming technologies used today. Traditional message queues rely on single-node brokers with primary-backup setups for high availability (HA). Kafka was the first distributed implementation, but it remains leader-based, where a designated leader manages replication. Pulsar advanced this by decoupling compute and storage, but it still follows the leader-based model. This approach works exceptionally well for scenarios requiring ultra-low latency (e.g., milliseconds). For such use cases, sending data through a leader remains unavoidable. 💡 Leaderless Architecture The emergence of S3 as a primary storage layer has triggered a shift toward leaderless architectures. Instead of treating S3 as just a tiered storage solution, it now serves as the main storage layer. In this model, brokers become leaderless, meaning any broker can handle reads and writes. Platforms like WarpStream, Confluent Freight Cluster, and StreamNative’s Ursa Engine are adopting this approach, reflecting the growing trend toward distributed and flexible architectures. 💡 Brokerless / Headless Architecture The next frontier is headless (or brokerless) architectures, where metadata and data are entirely decoupled: Data resides in S3, while metadata is managed by a separate metadata or catalog service. With a standard specification in place, operations no longer need to flow through brokers. Vendors can simply adhere to the standard and build their solutions accordingly. This approach can enable seamless scalability and interoperability. Our Ursa Engine is heading toward this exciting future. Explore the full blog post to dive deeper into these trends and the journey from leader-based to brokerless architectures: https://lnkd.in/gCcmv3rU You can also watch our keynote presentation at Data Streaming Summit: https://lnkd.in/g6a3wHrC

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Fine tuning an LLM (Large Language Model) means adapting it to specific data and tasks with the goal of improving performance on those and similar tasks. In a new blog post, my colleagues describe a set of best practices for fine-tuning Anthropic Claude 3 Haiku on Amazon Bedrock: 1 - Choose a suitable use case per the guidelines in the post. 2 - Gather a clean, high-quality data set and structure it for efficient training, with an optional system prompt. 3 - Customize and run the fine-tuning job. 4 - Assess the fine-tuned model's performance against relevant metrics and against the base model. 5 - Iterate and deploy. Read the entire post at https://lnkd.in/gAT6kzHK to learn a lot more!

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Numerical Weather Prediction has been one of the standard workloads of #hpc for decades. And my Colorado neighbors over at NSF NCAR - The National Center for Atmospheric Research have been key to advancing research in this area. One of their most popular developments in support of these efforts is the open source Weather Research and Forecasting (WRF) model, with > 50k users from over 160 countries. See below for detailed instructions on how you can perform your own #weather prediction on Amazon Web Services (AWS) using AWS ParallelCluster, Amazon FSx for Lustre, and WRF.

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Want to build search experiences that understand natural language and user meaning? In this webinar, get started on your journey to semantic search and set yourself up for success with generative AI. https://lnkd.in/gghqPrJM

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Announcing the 11th Annual Flare-On Challenge https://ift.tt/ZvE2Asz Written by: Nick Harbour When it's pumpkin spice season, that means it's also Flare-On Challenge season. The Flare-On Challenge is a reverse engineering contest held every year by the FLARE team, and this marks its eleventh year running. It draws thousands of players from around the world every year, and is the foremost single-player CTF-style challenge for current and aspiring reverse engineers. It provides individual players with a gauntlet of increasingly challenging puzzles to test their ability, and earn a position in our hall of fame. Veteran competitors who have been following the live countdown over at flare-on.com may have already marked their calendar for the contest launch at 8:00pm ET on Sept. 27th, 2024. It will run for six weeks, ending at 8:00pm ET on Nov. 8th, 2024. The Flare-On contest always features a diverse array of architectures, but with a strong representation of Windows binaries. This year’s contest may be the most diverse ever, with 10 challenges covering architectures including Windows, Linux, JavaScript, .NET, YARA, UEFI, Verilog, and Web3. Yes, you read that correctly, there is a YARA challenge this year. The challenges are often designed to represent Reverse Engineering challenges the FLARE team has encountered on the frontlines of cybersecurity. If you successfully crush all 10 challenges you will be eligible to receive a prize, which will be revealed later. This crucial bit of gear will distinguish you from your colleagues who have not mastered the arcane art of Reverse Engineering, and will thus be an object of their envy. Your name or handle, should you choose to be included, will be permanently etched into the Hall of Fame on the Flare-On website.  Please check the Flare-On website for the live countdown and, upon launch, the link to the game server. Early account registration will open approximately two days before launch. While you’re there, check out last year’s challenges and official solutions to prepare yourself. For official news and information, we will be using the Twitter hashtag #flareon11. via Threat Intelligence https://ift.tt/ehOMwd0 September 13, 2024 at 10:00AM

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🤔 Unlock revenue tied to data streaming or keep your focus on the rest of your roadmap? Good news: that’s a choice you no longer need to make—the Confluent OEM Program is here to empower you to do both! MSPs, CSPs, and ISVs, don’t miss out—learn more about the program on our blog!

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📅 *Today* - Tuesday, October 22nd, 2024 11:00 AM PT [▶][▶] 👨‍💻👨‍💻Join Abhishek Narain and Wilson Lee for "Unlocking AI at Scale with Data Factory in Microsoft Fabric"! 📊 Efficiently managing high-volume, complex data is critical for building scalable AI solutions. Data Factory in Microsoft Fabric streamlines the process of ingesting, transforming, and orchestrating data, making it easier to prepare and integrate diverse data sources for AI applications 🔬Join this session to explore how Data Factory can help automate data workflows, enabling seamless data preparation for AI models. Learn how to design scalable data pipelines, automate data transformation, and optimize data integration, all within the Microsoft Fabric ecosystem. This is your chance to unlock the full potential of AI using Data Factory!. 🚀🔥Don’t miss this opportunity to learn and do more with AI in Microsoft Fabric. Register now for the Microsoft Fabric & AI Learning Hackathon and livestream series! Check out the "Microsoft Fabric & AI Learning Hackathon" on Devpost: https://lnkd.in/gwSAyWhE See the full "Microsoft Fabric & AI Learning Hackathon" livestream schedule on the MS Reactor: https://aka.ms/fabrichack Watch today's livestream event on-demand on YouTube: https://lnkd.in/gbN9qFTr

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New Report: #platformEngineering is equally relevant to #appmodernization and #cloudmigration to greenfield app development. Modernization and migration efforts are frequently fragmented and uneven and vary widely across the organization. Secure? Maybe. Can Platform Engineering help?https://lnkd.in/ggmtmYr6 Check out my PulseMeter #analystReport - Platform Engineering, App Modernization and Cloud Migration, including insights collected from Techstrong's DevOps.com and Cloud Native Now online communities. Developed in collaboration with Amazon Web Services (AWS) and Effectual. Techstrong Group The Futurum Group

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Now you can govern Kafka topics from Amazon MSK in DataZone, store metadata including data lineage, schema, and data format in DataZone's business catalog, and subscribe to MSK topics using the DataZone subscription and fulfillment workflows. #DataStreaming #realtimedata #data #datagovernance #AWS

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