AI DevOps: Shipping GenAI Features Without Breaking Production
How to treat LLM apps like real products—CI/CD, evaluation gates, cost controls, and rollback paths that ops teams can trust.
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Insights on AI, DevOps & secure delivery
Practical notes on GenAI platforms, secure CI/CD, platform engineering, and AIOps—written for teams shipping in production.
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AI, DevOps, and secure delivery notes
Short, practical articles from real cloud, GenAI, and DevSecOps work—not trend roundups.
Secure CI/CD Gates That Don’t Slow Your Team Down
SAST, SCA, secrets scanning, and container checks belong in the pipeline—here’s how to make them fast and actionable.
6 min readRunning RAG on Kubernetes: A Production Checklist
Vector search, chunking, GPU serving, and observability—what usually breaks first when RAG leaves the demo environment.
8 min readPlatform Engineering for AI Teams: Paved Roads Over Ticket Queues
Give ML and product teams self-service environments, model registries, and guardrails—without inventing a second cloud.
5 min readFrom Alert Noise to Signal: Practical AIOps for SRE Teams
Correlation, anomaly detection, and runbook hooks that reduce pager fatigue without inventing a black-box ops system.
6 min readWant these practices in your environment?
From secure pipelines to GenAI landing zones—we help you implement what the articles describe.