Leo M.

I want to talk about Team Nightwatch: Rolando Maradiaga, Christhian Flores, André Velásquez and Jean Pierre Santos At MoxieThon Panama 2026, while my team was heads-down on billing automation, these four were quietly building something that stopped everyone in the room during the final presentation. MoxieReport — a module that replaces one of the most painful parts of healthcare operations: manual report generation and auditing. If you've ever worked in a clinical setting, you know what that looks like. Spreadsheets. Back-and-forth reviews. Data gaps nobody catches until it's too late. Their system automates all of it. Identifies gaps in real time. Generates reports automatically. And then — the detail that stood out — a One-Click Notify that alerts practitioners via email and WhatsApp the moment new census data is created. They also shipped an AI assistant that lets you ask natural-language questions about your report data and get charts back instantly. Three days. Four engineers. First place. Well deserved. This is what happens when talented engineers are given a real problem and the space to solve it. Thank you to The Moxie Health Group and Gustavo Ferrer MD, FCCP, MBA for creating this space. Competing alongside this level of talent doesn't happen by accident — it takes a company that actually invests in its people. #MoxieThon #HealthcareAI #MoxieLink #TeamNightwatch #Healthtech #EngineeringLeadership #Panama

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This guide gives CIOs, CTOs, and VPs of Engineering the insights to: * Evaluate the strengths and risks of nearshore delivery vs. offshore or onshore. * Justify the nearshore decision internally with CFOs, security, and procurement stakeholders. * Choose the right nearshore partner with confidence. * Understand the most common pitfalls—and how to avoid them. Download today and walk away with a clear, strategic view of how nearshoring works, when it works best, and what it takes to get it right. https://lnkd.in/d7kYcUbs

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Your code is only as good as your input. Guillermo Rauch, Vercel's CEO, posted that code should be treated as an output, and we should be turning our attention to production inputs. I agree. No amount of context in a system message will replace giving your coding agents access to production traces. Your agents need to see how real users actually hit your APIs. Which means looking at full request/response bodies, database calls, cache hits, etc. How we do it: - Record live traffic down to individual spans (with PII redacted) - Pipe traces to a coding agent via MCP so it can debug with real payloads - Replay traffic as a test suite in CI to diff API responses against user behavior Your app already knows what to test. You just didn't have something listening back then.

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🚀 Highly efficient CI/CD is not just a technical detail - it’s one of the most impactful levers an engineering leader can pull. Guillermo Rauch, CEO of Vercel, shared this during his conversation on Uncapped with Jack Altman: “The one thing I did that was revolutionary for my team was spending a lot of time in getting the CI/CD process… as efficient as possible. Imagine that you’re almost editing the internet in real time. That was the feeling that I wanted to give my employees.” 🧑‍💻 For engineers, this means a workflow where pushing a small feature to Git immediately triggers a deployment - feedback is nearly instantaneous, and iteration becomes natural. 🧑‍💼 For engineering managers, it’s about deployment velocity. The faster your team can ship safely, the more they can stay in flow, experiment, and innovate. Velocity compounds into business value. ✨ Guillermo compares it to setting up a new Apple laptop: everything “just works” out of the box. That’s the developer experience goal - no wasted cycles on painful environment setup, just pure focus on building. 💡 The real takeaway: Efficient CI/CD is a business strategy. Happy developers build better products, and organizations that can “edit the internet in real time” will outpace those still stuck in quarterly deployments and code freezes. #SoftwareEngineering #DevOps #DeveloperExperience

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12 Architectural Concepts Developers Should Know By Alex Xu 12 Architectural Concepts Developers Should Know 1 - Load Balancing: Distributed incoming traffic across multiple servers to ensure no single node is overwhelmed. 2 - Caching: Stores frequently accessed data in memory to reduce latency. 3 - Content Delivery Network (CDN): Stores static assets across geographically distributed edge servers so users download content from the nearest location. 4 - Message Queue: Decouples components by letting producers enqueue messages that consumers process asynchronously. 5 - Publish-Subscribe: Enables multiple consumers to receive messages from a topic. 6 - API Gateway: Acts as a single entry point for client requests, handling routing, authentication, rate limiting, and protocol translation. 7 - Circuit Breaker: Monitors downstream service calls and stops attempts when failures exceed a threshold. 8 - Service Discovery: Automatically tracks available service instances so components can locate and communicate with each other dynamically. 9 - Sharding: Splits large datasets across multiple nodes based on a specific shard key. 10 - Rate Limiting: Controls the number of requests a client can make in a given time window to protect services from overload. 11 - Consistent Hashing: Distributes data across nodes in a way that minimizes reorganization when nodes join or leave. 12 - Auto Scaling: Automatically adds or removes compute resources based on defined metrics.

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Organizing cross-functional, multi-faceted teams requires a. Structuring them to address mixed priorities originating from their respective streams. b. Establishing an enabling task force to support stream-aligned teams, and c.Managing the complex subsystems within them. Navigating these complexities without a proper framework can be challenging; I recently encountered the works of Team Topologies - https://lnkd.in/g3pT878f. Their approach helps create a mental model and aids in identifying inherent patterns within the teams to: a. Understand the natural flow of work within the teams and maximize the flow. b. Establish a shared vocabulary, both internally (vertically) and externally(horizontally), for discussing the team's structure and roles. Useful videos - https://lnkd.in/gMemdB7C https://lnkd.in/g_mvhkHt

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General info. Technical details. Affected sites. Here we go: A few days ago Amazon Web Services (AWS) experienced a major disruption in its U.S. East (N. Virginia, us-east-1) region, affecting 142 regional and some global services for several hours. The issue lowered AWS’s uptime in this region for October below its usual 99.99% reliability target (which varies by service). Lots of green days, two red ones, and back to green. AWS has since resolved the problem, added stronger safeguards, and committed to improving testing and recovery to prevent similar outages. The full post-mortem is linked in the comments. From a technical standpoint, the outage was triggered by a DNS automation race-condition fault within Amazon DynamoDB’s DNS management system. This created incorrect DNS records that caused endpoint resolution failures, impacting dependent services such as EC2 instance launches, Network Load Balancer (NLB) health checks, and Lambda functions. Such issues usually occur due to a specific chain of events, and honestly, they can happen even in the most well-designed systems. AWS engineers disabled the faulty automation, deployed new recovery and throttling controls, strengthened failure isolation, and enhanced resilience testing across large-scale systems. Many well-known companies were affected. Most likely, most of them didn’t want to reveal their infrastructure dependencies, but that information was exposed unintentionally. Snapchat, Reddit, Canva, Duolingo, The New York Times, Fortnite, Apple TV, McDonald’s, OpenAI, Vimeo, Twitch, Shopify, Google Maps, reCAPTCHA, YouTube, Spotify, Discord, Google, Cloudflare, Mailchimp, WhatsApp, Airbnb, and Disney+. What do you think?

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KCD Mexico 2025: Advancing Cloud-Native Innovation KCD Mexico 2025 in Guadalajara brought together over 200 cloud computing and Kubernetes professionals to explore the latest advancements in cloud-native technology. The event featured more than 30 international speakers who shared insights on Kubernetes optimization, security, and scalability. Key sessions included intelligent autoscaling with Karpenter and Amazon EKS, security hardening for compliance with PCI DSS and GDPR, enhanced visibility with API Gateway and OpenTelemetry, and the integration of Istio with KubeVirt for hybrid architectures. Additionally, discussions on cloud-native CI/CD migrations and sustainable green infrastructure practices highlighted practical strategies for maximizing cloud efficiency. This collaborative environment fostered innovation and knowledge sharing, reinforcing Guadalajara’s status as a burgeoning tech hub in Latin America. Author: Rodolfo Martinez, KCD Organizer

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It's not every day that I get to quote Dave Thomas—the founder of Wendy's, not the author of The Pragmatic Programmer—but I do in this podcast with Roberto Perez. Dave Thomas said that the most important bites of a burger are the first bite and the last bite. Those are the bites you remember. Those are the bites that influence your reaction to eating that burger—in other words, will you get another in the future. LLMs, it turns out, do something similar. They tend to remember stuff at the beginning of the context and the stuff at the end of the context. And sometimes struggle with the in the middle stuff. So keeping context small matters. The less middle you have, the less chance the middle is missed. And, of course, a smaller context is cheaper and faster too. Fewer tokens. Less time spent processing them. So smaller contexts are, generally speaking, better. Of course, just dropping messages off the back of the conversation to keep a small context doesn't solve the problem. The context needs to be tight, not truncated. To do this, you need Agentic Memory. In the podcast, I demo a simple chatbot that uses Agent Memory Server to provide just that. Watch it for all the details: https://lnkd.in/eBFACpYb

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We just published a new post on the Tensor9 blog about a problem that comes up in almost every vendor conversation we have: what happens when your application depends on a managed service like DocumentDB, and your customer can't run on AWS. https://lnkd.in/gzamYh2d

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Really excited about this one: Confluent is teaming up with the Visa Cash App RB F1 Team! As someone who gets to see firsthand how powerful real-time data can be, it’ll be amazing to see it fuel faster race-day calls, engineering breakthroughs, and even fan experiences. Read more here: https://cnfl.io/46LDD8Z

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When was the last time you typed just “Peru travel guide” into a search bar? It's likely that you asked a longer question, such as a complete sentence. That shift, powered by large language models and vector search, is reshaping how we find information. The future of search isn’t purely about AI models or keyword search alone — it’s about hybrid search, so results are smarter and more relevant. This MongoDB blog explains what to look for when choosing a hybrid search solution and why it’s becoming essential. https://lnkd.in/gkr8kuyS

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Lambda Durable Functions were developed to address the need for pausing a Lambda execution while allowing external work, such as an LLM generating a response, to continue without incurring idle VM costs or losing execution state. This challenge is not new. It’s not a “which is better” post it walks through the same real use case implemented both ways and looks at where complexity and cost actually live. https://lnkd.in/dBDdk94z #AWS #Serverless #CloudArchitecture #StepFunctions #AI

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If you're a dev or work in ops and you are not maxing out a $20 a month claude code subscription, you are failing behind rapidly.

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I’m intentionally expanding my network with people who run or lead outsourced software teams: development agencies nearshore/offshore delivery partners fractional engineering firms I’m building DevHawk, a product focused on delivery visibility inside engineering organizations — largely because most of the tools we all use today are built for reporting activity, not understanding how work actually moves through a team. They look busy. They don’t show friction. What I care about is how outsourced teams really operate: how work gets handed off, where reviews slow things down, how QA queues form, and what actually determines whether a project ships smoothly or quietly drifts. If you’re in this world, feel free to connect. This isn’t about exposing problems or “fixing” anyone — it’s about learning from operators who already know how hard delivery is at scale. Even if we never work together, I’d value being in the same network.

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We at cloudEQ enable faster, safer deliveries by combining standardization and governance to cut manual fixes, elastic agents with self-healing to remove delays, and GitOps with observability to ensure resilient, visible, and secure deployments. #Automation #DevSecOps #GitOps #AIOps #Observability

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Abre has 200% growth since I joined 2 years ago and still proudly running our main application as a giant monolith 💪 🎉 What are we focused on this year? - Shipping key features that solve major problems for our clients - Refactoring legacy code so we can ship and debug faster - Code consolidation to reduce trips to our main database - Optimizing our main database for speed and performance - Adding caching - Optimizing image storage and rendering - Reducing latency What we are avoiding: - Refactoring into microservices - Overengineering - Kubernetes clusters and container orchestration - Expensive infrastructure - Adding complexity just because someone thinks it’s a good idea - Rewriting our application code in GO or Rust When you have a small team and a growing company, speed and optimization is more important than anything. Unnecessarily adding complexity creates barriers when solving problems for customers needs to be the number one focus!

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🤩 Stoked to see a new major release of Middy supporting already many of the most recent announcements in #AWS #Lambda. This includes: - Durable Functions 🔥 - Tenant Isolation Mode - Multi Concurrency on Lambda Managed Instances - And even LLRT! ⚡️ #serverless #opensource #oss

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