Luis Pineda

I'm thrilled to announce that I'll be speaking at DevOps Dreamin' in Chicago next month! 🎉. Not sure why they invited me based on this clip from a recent Elements.cloud IMPACT event!!! 👉 Register for DevOps Dreamin': https://lnkd.in/g8VUGwDb I do think DevOps can make a huge difference, but there are some critical points for both DevOps teams and Business Analysts: For DevOps: Ensure you have a complete user story before you begin building. Push back if the specifications aren't clear. For Business Analysts: Understand the core needs. Distinguish between what users say they want and what they truly need before passing anything to DevOps. 🤔 Curious about these insights? Check out my talk at the event! 💬 What challenges have you encountered in specification clarity and requirement understanding in your projects?

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This is the initial infrastructure Tradescoop was built on. A few things have changed, some additions and removals; for example, we’ve gone from MongoDB on Digital Ocean to Mongo Atlas, Redis cloud to Memorystore, but the general appraoch remains. Simplicity. Shouts to Karl Obinna Amalu, CSM for cleaning it up and adding color ✨ #gcp #infrastructure #devops

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Amazon Web Services (AWS) recently the availability of Anthropic’s Claude 3 Opus on Amazon Bedrock, the most intelligent Claude 3 model, with best-in-market performance on highly complex tasks. It can navigate open-ended prompts and sight-unseen scenarios with remarkable fluency and human-like understanding, leading the frontier of general intelligence. So what are the top 3 things to know? 👇🏽 Watch this short clip by Du'An Lightfoot to learn more. #aiml #generativeAI

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We are excited to announce the launch of Ursa engine, our Kafka API-compatible data streaming engine that is built on top of Lakehouse. Ursa is not something entirely new; it is built on our many years of experience building and operating #ApachePulsar and #ApacheKafka. To learn more about the #Ursa engine, I recommend our #PulsarSummit keynote presentation and announcement blog post. Here, I’d like to delve deeper into some of its features: 1. Making Kafka API a first-class citizen: In #ApachePulsar, we developed a unified messaging model combining queuing and streaming semantics into one protocol, aimed at enhancing data sharing between business applications. Although powerful and increasingly adopted by enterprises and unicorns, the requirement for application rewrites is impractical in today’s economy. Instead of building data gravity around a protocol, we open up access to the robust stream storage layer by extending support to the Kafka protocol, transitioning from a single protocol to a multi-protocol platform, facilitating greater flexibility and integration. 2. Achieve Stream-Table duality via Lakehouse Storage: Data streams commonly end up in data lakehouses, where integrating and maintaining them can be complex and resource-intensive. Ursa simplifies this by storing data streams as lakehouse tables in object storage. This integration not only streamlines operations but also allows seamless access to operational data for analytical processes. Thanks to its multi-modal storage engine which fosters data sharing across teams and departments. 3. Object storage as the primary storage solution: To better align with cloud economics, particularly for large workloads, Ursa makes ZooKeeper and BookKeeper optional and utilizes a cost-optimized write-ahead log based solely on object storage with leaderless and stateless brokers. This architecture leverages object storage for both data replication and storage, minimizing inter-AZ data transfers and reducing costs for latency-relaxed, high-volume workloads. By integrating these features at the multi-tenant level rather than at isolated cluster levels, Ursa eliminates costly data duplication and movement across clusters, allowing teams to map directly to tenants and be able to share data across teams and departments more efficiently. We believe that the future of data streaming platforms lies in being open and multi-faceted, fundamentally different from traditional data platforms. They are designed not just to store and process data, but to enhance organizational capabilities by fostering data sharing across the organization and integration with other systems. More and more data streaming platforms will look more like Ursa, with multi-protocol, multi-tenant, and multi-modal capabilities. Check out our announcement blog post about Ursa: https://lnkd.in/ghEKTYE6 #ApacheKafka #Lakehouse #DataStreaming

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🤖🐍 A.I., Snake Oil, and Miracle-Cure Expectations https://lnkd.in/emSQAHzE Here's Josh Clark with a fantastic call for more nuance around how we think about machine learning and AI. These things are tools — not panaceas — and we need to be able to discern how best to put them to work. "The best response to failed experiments is not, 'What a dumb idea, there’s nothing here.' For what it’s worth, I prefer: 'What can we learn from this? What’s next?'" I'm so grateful to have a partner with such a reasoned perspective on all of this. Thanks to Josh I've been able to become more curious and excited about these technologies without losing my sense of (what I feel to be) warranted skepticism and anxiety. #ai #machinelearning #ux #design #snakeoil

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Anthropic’s Claude 3 Opus foundation model, the most advanced and intelligent model in the Claude 3 Family, is now available on Amazon Bedrock. Claude 3 Opus is Anthropic’s most intelligent model, with best-in-market performance on highly complex tasks. It can navigate open-ended prompts and sight-unseen scenarios with superior fluency and human-like understanding. With Claude 3 Opus on Amazon Bedrock, you can execute complex actions, interactive coding, research review, hypothesis generation, drug discovery, advanced analysis of financials and market trends, and forecasting. Just like the other Claude 3 models, Claude 3 Opus has state-of-the-art vision capabilities that can process and analyze images. These models were trained to be extremely capable at understanding photos, charts, graphs, technical diagrams, and optical character recognition (OCR).

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New post on what happens after you add a control plane and local storage for observability: you get 1000x the telemetry when it matters. https://lnkd.in/gAvkk-qP

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In these times of economic uncertainty, why would you focus on database clustering? Here are a few reasons: ➡ High-risk industries like banking, finance, government, healthcare, and manufacturing face downtime costs of up to $85,000 per minute ➡ For enterprises heavily reliant on data centers, such as telecommunications or e-commerce, a single event's downtime cost can exceed $1 million ➡ The average cost of downtime across all industries has risen to about $9,000 per minute, with variations based on business size and industry ➡ Beyond immediate financial losses, downtime costs include lost productivity, recovery costs, and intangible costs like damage to reputation, loss of business, opportunity cost, poor user experience Clustering your database for high availability shields you from such hefty consequences. Henrietta Dombrovskaya has been kind enough to invite me to speak on this topic at the DRW Training Center as part of the Chicago PostgreSQL User Group meetup on Wednesday, 15th May. Attendance is free - I'd love to meet and discuss!

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Fellow in-house taxonomists, ontologists, metadata managers, and semantic wizards: what is the name of the team or business unit that you work within? I have the good fortune of getting to rename the "Content Standards" program I lead at Kaiser Permanente IT. My team has determined that the name is too vague to convey the core activities of the program, and leads to confusion with the cross-functional teams we collaborate with. I'm looking for a clear name that will resonate with stakeholders within my org. So I've got a very classic taxonomist question: What to call the program? 🤔 For some context... What my program is responsible for: - Defining and governing standards for metadata, structured data, taxonomy, and ontology for classifying/structuring digital content - Implementing processes and platforms to good metadata hygiene - Assessment and remediation of content metadata What my program doesn't cover: - Writing or editorial style guides - Content design - Content strategy - Site maps or navigational structure - Data governance Any ideas are most welcome!

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Fully Local LLMs with Web interface on your device: If you have free time to learn AND you have a Windows Desktop with an NVIDIA card, then my recommendation is to run Ollama and Open-WebUI in docker containers on a WSL Ubuntu24.04 Distribution. How do you do that?

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Extracting Entities and Relationships from your unstructured data are just some of the things we do. Check us out on #awsmarketplace!

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What’s Next: RunWhen's Kyle Forster talks open source and microservices SDxCentral CEO Matt Palmer speaks with RunWhen's Kyle Forster about a better way for companies to support gigantic code bases.

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Another great article by Pete Flint, Anna Piñol and the NFX team: https://lnkd.in/g8XKjGdX. One big takeaway is AI-first B2B software will necessarily expand and fuse with knowledge workers, which not only creates tremendous opportunities for new AI-first companies (“AI Colleagues” or “AI Vendors”), but also necessitates every organization to adopt AI to remain competitive (and more frankly, to remain alive). Favorite quote of the article, “In the long term, software with a soul may endure far beyond software that seeks to automate repetitive tasks." At Glowing.io, we strongly encourage (and moving towards requiring) everyone on our team to leverage AI tools in a growing percentage of their work in order to free up more time on creating impactful and delightful solutions for our customers.

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AWS continues to add capabilities to Amazon Bedrock that make it the easiest way to build high quality, low latency, and cost-effective GenAI applications. Today the team announced:   - Custom Model Import, which lets customers easily bring their own models (from SageMaker and S3) to Bedrock to leverage its leading GenAI features, such as RAG, agents, Knowledge Bases (guardrails), inference deployment, and advanced customization to keep teaching and refining models.   - Model Evaluation, which lets customers quickly select predefined evaluation criteria (like accuracy and robustness) and run reports that help them understand which is the best model for them.   - Meta’s new Llama 3 models, now available on Bedrock and can support a wide range of use cases including text summarization and classification, sentiment analysis, language translation, and code generation.   - New Cohere Models, Command R and R+, are state-of-the-art FMs customers can use to build enterprise-grade generative AI applications with advanced RAG capabilities, in 10 languages, to support their global business operations. These will arrive on Bedrock in the coming weeks.   - New Amazon Titan models with Amazon Titan Image Generator (GA today) helping customers produce studio-quality images, at low cost, using natural language prompts (and applies an invisible watermark to help reduce the spread of disinformation)… along with Amazon Titan Text Embeddings V2 model, which reduces storage and compute costs, while out-performing other leading models on text embeddings.   Tens of thousands of customers are already building real-world production-ready GenAI apps and we're excited for even more customers to get started. https://lnkd.in/g4rkak47

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Looking to get started with in-database machine learning with MySQL HeatWave? This guide will help get you on the right path. https://lnkd.in/gPjuJU9g

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EKS Anywhere removed support for Bottlerocket because "Bottlerocket's image-based architecture and constrained surface area do not align with these bare metal use cases" Meanwhile at Sidero we're putting Talos on Oxide Computer Company racks, Ampere gear, Raspberry Pi's, and a ton of other hardware. Talos is both smaller, more secure, and more usable than Bottlerocket will ever be. This isn't a technical problem, it's a business model problem because AWS can't compete with itself. They have to artificially limit their products to not steal from existing revenue streams. https://lnkd.in/e8-cRy_W

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