Top 5 Tips to Win the FutureStack GenAI Hackathon
Your winning strategy for $15,000 in prizes and career opportunities
Your winning strategy for $15,000 in prizes and career opportunities
Vibe coding is the new rhythm of software: start with a fuzzy idea, throw a prompt at an AI, and—boom—a demo runs. The catch? Creation is instant; correctness isn’t. This post unpacks that paradox.
The future of AI isn't about finding the perfect model—it's about orchestrating the right models for the right tasks.
Docker Compose now supports AI models as first-class citizens with the new models top-level element. Adding machine learning capabilities to your applications is now as simple as defining a model and binding it to your services.
The MCP Gateway is Docker’s answer to the growing complexity and security risks of connecting AI agents to MCP servers. By aggregating multiple MCP servers behind a single, secure interface, it gives developers and teams a consistent way to build, scale, and govern agent-based workloads.
Docker Scout reveals the shocking truth: the standard python:3.13 image harbors 152 vulnerabilities across 40 packages. Meanwhile, Docker Hardened Images shows zero detected vulnerabilities. It's the same Python functionality with enterprise-grade security built in
Agentic AI
Discover how Docker's revolutionary cagent framework is transforming AI agent development with simple YAML configurations, multi-agent orchestration, and seamless tool integration.
Learn everything about Docker Hardened Images (DHIs) - secure, minimal, production-ready container images that reduce vulnerabilities by 95%, ensure compliance, and integrate seamlessly into existing workflows.
Model Context Protocol promises seamless AI-tool integration, but real-world vulnerabilities with CVSS scores above 9.0 are compromising everything from GitHub repositories to production databases. Here's how we fix it before it's too late.
Confused about MCP vs RAG? You're not alone. These two AI technologies are transforming how we make language models smarter, but they work in completely different ways.
If you’ve ever spent hours debugging a misconfigured probe or chasing down a rogue config drift, you’re not alone. This post is a no-fluff breakdown of the top Kubernetes headaches every DevOps engineer encounters, paired with proven fixes, pro tips, and real-world examples to save your sanity.
Docker Desktop has evolved far beyond containerization. These 5 features are reshaping development workflows: Model Runner (local AI), MCP Toolkit (secure agents), Docker Offload (cloud GPUs), Debug (enhanced troubleshooting), and Agentic Compose (AI infrastructure).