Nicolas A Perez

RAG applications break in mysterious ways. Slow retrieval because your vector store is overloaded. Bad answers because retrieval returned irrelevant docs. Silent API failures breaking your pipeline. Without observability, you're debugging blind. LlamaIndex + OpenTelemetry + SigNoz gives you end-to-end visibility. See exactly where time goes: document chunking, embeddings, retrieval, or LLM generation. Track what matters: embedding batch durations, retrieval similarity scores, token usage, user feedback. Get connected traces showing complete request flows instead of scattered logs. Includes a demo RAG chatbot built with our docs to show the instrumentation in action.

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In-memory databases are the architectural backbone of real-time AI. They’re a necessary advantage for memory-intensive workloads that rely on instant access to context. Modern systems like Redis blend durability, multi-model flexibility (JSON, vectors, time-series), and tiered storage to deliver the speed of memory with the reliability of disk. The result? Real-time analytics, instant personalization, and AI systems that actually feel intelligent. Here’s how we deliver the speed of memory with the reliability of disk: https://lnkd.in/gSm65kdB

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If your team is building with LLMs, you know the value of clean, retrievable data. That's why we're teaming up with Unstructured to streamline one of the hardest parts of AI development. This integration removes friction across the AI stack—from unstructured ingestion to semantic retrieval—so your teams can focus on building. Read more from our Product Marketing Managers, Rini Vasan and Jim Allen Wallace, and Unstructured’s Head of Developer Relations, Maria Khalusova here: https://lnkd.in/e98QqXAB

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Enterprise systems don’t run on SQL alone. That’s why your AI Agent now works with Redis. Build things like: > Prompt cache inspectors > AI cost dashboards > Queue monitoring panels Inspect live state. Control operational layers. Ship internal control planes in hours.

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Cloud bills aren’t about storage. They’re about compute. Rocket engineers design AWS architectures that minimize redundant requests, optimize edge caching and cut unnecessary data transfer. The result: faster performance and lower costs—without ripping and replacing your stack.

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Kubernetes is powerful. It doesn’t have to be painful. Explore how Ori Serverless Kubernetes gives you the speed and stability required for production #AI inference, minus the complexity.

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JFrog Fly is redefining how engineering teams manage artifacts in an AI-driven world. As software delivery becomes faster, distributed, and increasingly automated by AI, traditional artifact management can’t keep up. JFrog Fly introduces a smarter, globally scalable way to store, replicate, and deliver artifacts—built for modern engineering velocity. 🔗 Read the full blog to explore what this shift means for your DevOps pipeline. Link - https://lnkd.in/dUK_UFd8 #JFrog #AI #DevOps #SoftwareDelivery #CloudNative

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Are you running Postgres, Mongo, and Redis on separate cloud platforms? Or handling all the setup operations yourself? Not anymore. With Shard, a few simple prompts or clicks and it’s ready in seconds.

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💡 Curious how to optimize Kubernetes spend without sacrificing performance? At SlickFinch, we start with precise metrics and autoscaling best practices that balance both efficiency and reliability. Save this post to use as a quick reference! 🔍

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"Pull all siloed AI projects into a one-page chart. Focus on the ones aligned with strategic goals, pause the rest, assign owners, remove roadblocks, and make clear what business value each delivers." – Julian Tang, AI Champion, BlackRock In this Pure Storage–sponsored episode of the #AIinBusinessPodcast, Julian Tang joins Emerj Artificial Intelligence Research Editorial Director Matthew DeMello to break down how enterprises can operationalize AI, align projects with strategy, and accelerate measurable outcomes. Retail and CPG leaders can uncover actionable frameworks to integrate AI into workflows, prioritize initiatives, and unlock ROI with greater clarity and speed. Listen to the full episode to discover actionable strategies for aligning AI projects with business goals and accelerating real results: https://lnkd.in/dxxHiDGU #EnterpriseAI #AIGovernance #AIWorkflow

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🚩Feature Flags: How to Ship Faster, Safer, and Smarter 🚩 Dinesh A., Principal Engineer at Wells Fargo, is breaking down feature flags at Code Remix Summit. Not just what they are, but how to actually use them without creating chaos. Get best practices that prevent flag sprawl and technical debt. Hear real case studies showing how companies are using flags to ship with confidence. 👍 https://lnkd.in/g5r2MUSJ #CodeRemixSummit #FeatureFlags #WellsFargo #ContinuousDelivery #DevOps

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