AI DevOps Korea
Aidevops.kr covers LLMOps, RAG, agents, observability, evaluation, and cost-performance optimization for production AI services.
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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.
Preview environments accelerate feedback, but without lifecycle rules they can quickly become an expensive form of shadow production.
A failed deployment is manageable. A team that cannot decide when to roll back is much more dangerous.
Supply-chain security is not complete when an attestation exists. It matters when provenance becomes part of deployment policy.
Deployment once felt like a tense event. Containers and Kubernetes helped turn it into something more repeatable, automated, and systematized.
A practical guide to using Docker Desktop as a local development standard through Compose, volume strategy, resource tuning, Dev Containers, and onboarding design.
A deployment pipeline does not only move code. It moves trust. This guide explains how to define promotion contracts across dev, staging, and production.
A practical DevOps roadmap from container and CI/CD basics to observability, release control, and on-call operations.
How strong teams prepare code, operations, and rollback plans before a high-risk release freeze window.
What makes an operational runbook actually usable during incidents instead of just technically complete.
A practical introduction to SBOMs, provenance, attestations, and release verification for teams hardening modern delivery pipelines.
A practical reading of Kubernetes v1.34 for platform teams, focusing on the changes that most affect operations, workload design, and cluster governance.
A practical guide to choosing a Git branching strategy based on release cadence, CI maturity, hotfix handling, and team size. Compare Git Flow, GitHub Flow, and trunk-based development from an operational point of view.
A practical guide to using k6 as a tool for validating performance hypotheses. Covers scenario design, thresholds, think time, workload modeling, CI integration, and common mistakes.
As of April 21, 2026, Kubernetes officially maintains 1.35, 1.34, and 1.33. The real trend is not feature volume but lower disruption, simpler configuration, and better cost control.
A practical guide to combining blue-green deployment, canary rollout, and feature flags to reduce release risk in production.
A practical guide to treating observability as an incident response system, covering metrics-log-trace correlation, alert quality, runbooks, SLOs, dashboards, and postmortem feedback loops.
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 explains how to design reliable CI/CD pipelines with GitHub Actions, covering test separation, caching strategy, environment promotion, secret management, and deployment stability from a practical engineering perspective.
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 covers the core decisions required when operating Nginx as a reverse proxy, static file server, and SSL termination point, including upstreams, caching, timeouts, security headers, and common failure points.
This article explains Prometheus and Grafana from an observability design perspective rather than as an installation guide. Using Spring Boot as the baseline, it covers metric collection, label strategy, PromQL, dashboards, alerting, and common anti-patterns.
This article summarizes the core design points for managing AWS infrastructure with Terraform, covering state files, modularization, environment separation, change management, and operational risk from a practical perspective.
This article organizes the core security baseline for running Linux servers safely in production, covering SSH hardening, least privilege, patching, firewalls, audit logs, and operating procedures in a checklist-oriented way.
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.