AI DevOps Korea
Aidevops.kr covers LLMOps, RAG, agents, observability, evaluation, and cost-performance optimization for production AI services.
This group clusters posts that are best read together inside the DevOps category, so the learning path feels more intentional.
This group currently contains 5 posts.
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This article explains Kubernetes operations not as a collection of settings but from the perspective of resource placement and resilience. It covers when and how to use requests/limits, HPA, affinity, taints, PDBs, and probes in real environments.
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This article explains Kubernetes operations not as a collection of settings but from the perspective of resource placement and resilience. It covers when and how to use requests/limits, HPA, affinity, taints, PDBs, and probes in real environments.
This article explains Kubernetes Pods, Deployments, and Services not as isolated object definitions but through the lens of an operating model. It covers declarative deployment, network abstraction, configuration separation, and practical adoption concerns.
This article looks at Docker from a practical engineering perspective, beyond basic container concepts, covering image design, layer caching, volumes, networking, and operational pitfalls.
This article explains how to use Docker Compose to improve local development productivity. It covers service boundaries, volumes, networks, dependency management, and the differences from production environments from a practical engineering perspective.
This article frames ArgoCD from an operating model perspective rather than as an installation guide. It covers what GitOps means, Application structure, automatic sync, drift recovery, promotion strategy, and multi-environment operations in practical terms.