AI doesn’t need new infrastructure — just smarter use of what you already have. Scale it securely and efficiently using your existing Cisco and VMware infrastructure.
Facing a critical bug in unfamiliar code? Leverage documentation, automation, tests, observability, dependency fakes, policies, and AI to debug efficiently.
Multi-cloud brings resilience but also complexity, drift, security, and cost challenges. IaC, automation, and unified monitoring turn it into an advantage.
This guide covers AI infrastructure, from hardware acceleration and model serving to monitoring and security, with tools, patterns, and strategies proven in production.
This article demonstrates how we can run vLLM on Kubernetes for a centralized LLM serving engine that is production-ready and can be used by multiple applications.
A deep dive into the importance of data quality and strategies for improvement. We also analyze some real-world examples demonstrating the importance of data quality.
Most cloud teams aren’t AI ready: Only 51% of infra is automated, and there are major governance gaps and rising costs. Infra maturity (not GPUs) will decide who thrives.
This article explores the diverse infrastructure options and tools that are available for deploying and optimizing AI agents and large language models (LLMs).
Uptime isn’t luck — it’s engineered. Build it with observability, smart alerts, solid tests, and blameless operations. Reliable systems don’t need heroes.
This guide provides a complete checklist to assess, monitor, and improve data quality for AI success, ensuring accuracy, compliance, and long-term reliability.
Pulumi is an Infrastructure as Code platform that lets developers and teams create, deploy, and manage cloud resources using familiar programming languages.
My ML model misclassified groceries as entertainment. Distributed tracing with OpenTelemetry and Jaeger helped me quickly find a caching bug causing it.
Use Crossplane and kube-green to replace wasteful, always-on cloud environments with on-demand, ephemeral ones, dramatically cutting costs and environmental impact.
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