Kafka Crash Course: A Beginner’s Guide to Distributed Event Streaming
- Frank
- August 20, 2026
- apache kafka
- Apache Kafka crash course
- Apache Kafka tutorial for beginners
- Big Data
- distributed streaming platform
- distributed systems
- event streaming
- event streaming tutorial
- Kafka basics
- Kafka crash course
- Kafka for beginners
- Kafka fundamentals
- Kafka messaging system
- Kafka topics producers consumers
- learn Kafka
Apache Kafka stands out as a fundamental pillar for managing the flow of real-time data across different components. Originally known as a distributed event log, it serves as a robust backbone for event streaming platforms. For complete beginners stepping into this world, understanding Kafka’s role, its essential terminologies, and application setup is crucial. This blog […]
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Unveiling the Invisible: Finding Bugs in Non-Existent Systems with Formal Methods
Understanding and identifying bugs in software systems is often a daunting task, especially when the systems don’t physically exist yet. In a riveting talk by Hillel Wayne at SSW 2026, we’re introduced to the intriguing concept of using formal methods for early detection of bugs in distributed systems. Formal methods—a discipline that employs mathematical reasoning […]
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Unlocking the Potential of Agentic AI: Communication, Governance, and Guardrails for Multi-Agent Systems
- Frank
- June 8, 2026
- A2A protocol
- Agentic AI
- AgenticAI
- AI Agents
- AI communication
- ai engineering
- ai governance
- AI Infrastructure
- AI observability
- aiagents
- artificial intelligence podcast
- ArtificialIntelligence
- autonomous agents
- band ai
- Data Driven Podcast
- DataDriven
- distributed systems
- Enterprise AI
- enterprise architecture
- EnterpriseAI
- LLM Agents
- MCP protocol
- multi agent systems
- vlad luzin
As the world of artificial intelligence continues to expand, a new concept is gaining traction—Agentic AI. But what exactly does it mean, and how does it relate to the broader AI landscape? In a captivating episode of the Data Driven podcast, Frank La Vigne and Andy Leonard delve into these questions with Vlad Luzin, Co-Founder […]
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Running Large AI Models on Consumer Hardware: The Magic of Decoupling Attention
In artificial intelligence, adaptability and optimization are key. This is especially true when it comes to running large-scale models like Gemma 4 26B. Traditionally, deploying such models required significant GPU resources, but as Chris Hay illustrates, there’s a groundbreaking way to manage this using LARQL and the vindex format. This innovative approach allows massive models […]
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Revolutionizing Enterprise AI Agents with Google’s gRPC Transport Layer for MCP
- Frank
- April 17, 2026
- A2A
- Agent to Agent Protocol
- Agentic AI
- AI agent
- AI Agents
- AI Infrastructure
- AI Protocols
- AI Tool Integration
- anthropic code leak
- Anthropic MCP
- bytemonk
- Claude Code
- distributed systems
- Enterprise AI
- FAANG
- gRPC
- HTTP
- LLM Tools
- MCP protocol
- Model Context Protocol
- multi agent systems
Google has made a groundbreaking move that’s poised to transform the way AI agents function in production environments. They are introducing a gRPC transport layer for the Model Context Protocol (MCP), which was initially designed to alleviate the complex integration issues between AI agents and various tools. Let’s break down what this means and why […]
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How to Boost LLM Performance with llm-d: A Deep Dive into the Kubernetes-native Framework | Ep 140
When you think about orchestrating AI workloads at an enterprise level, Kubernetes often springs to mind. It’s the go-to for deploying and managing containerized applications, after all. But as we delve into the nuances and specific demands of modern AI, particularly with large language models (LLMs), the limitations of Kubernetes alone become evident. It’s akin […]
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Inside distributed inference with llm-d ft. Carlos Costa
Imagine you’ve just managed to tame a high-performance race car, finely tuning its engine and chassis to handle blistering speeds on a smooth, circular track. But then, the challenge evolves: you’re no longer racing on this predictable path; instead, you face the Pikes Peak Hill Climb, complete with its punishing turns, inclines, and diverse road […]
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Introducing llm-d: Distributed AI Inference on Kubernetes
Imagine you’re building a skyscraper. Now, think of the complex foundation that needs to support not just the physical weight of the structure but also its functionality—like electrical and plumbing systems integrated throughout. The same level of complexity and precision applies when deploying large-scale artificial intelligence (AI) systems, particularly those involving large language models (LLMs). […]
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