Considerations for Deploying a Next.js Community Project with Docker
Technical trends, engineering practices, and an independent developer perspective on DevOps and Next.js.
#DevOps #Next.js♥ 290 comments
云原生
DevOps、Docker、Kubernetes、可观测性
Collection
This collection features articles and community discussions in the 云原生 space, focusing on real-world engineering scenarios, tool selection, practical paths, and risk boundaries.
The page is continuously updated and serves as a learning roadmap, technology selection reference, and technical review entry point.
How Can OpenTelemetry Help You Observe AI Applications?
Technical trends, engineering practices, and an independent developer's perspective on DevOps and AI.
#DevOps #AI♥ 300 comments
AI Application Observability: From a Single Answer Trace to a Quality and Cost Feedback Loop
"Failures in AI applications are rarely service outages; they are more often retrieval errors, wrong tool choices, answer degradation, or runaway costs. This article designs an observability solution covering traces, tokens, tool calls, evaluation feedback, and privacy governance."
#AI Agent #DevOps♥ 180 comments
Docker Multi-Stage Builds and Image Optimization
A Node.js image can shrink from 1.2GB to 150MB with a few fundamentals, not magic. This guide covers multi-stage builds, separating build and runtime stages, choosing distroless or Alpine base images, .dockerignore, layer-cache reuse, and Next.js standalone for smaller, faster, safer images.
#DevOps♥ 250 comments
Kubernetes from Basics to Practice: Core Concepts in Plain English
K8s documentation can feel impenetrable, but its core concepts are not complicated. This guide explains in plain English what Pod, Deployment, Service, and Ingress do, how they work together to run a web application, hands-on practice with kind/minikube, and when you really do or do not need K8s.
#DevOps♥ 260 comments
GitHub Actions CI/CD in Practice
GitHub Actions is one of the easiest CI/CD platforms for developers to adopt, but using it well takes care. This article covers workflow structure, triggers, jobs, steps, matrices, caching, artifacts, secrets, concurrency, costs, and a practical "frontend + backend + deployment" workflow for fast, reliable, quota-efficient CI.
#DevOps♥ 270 comments
AI Agent Observability: Loops, Tool Calls, and Budget Guardrails
Agent failures are usually not service crashes, but wrong tool selection, stalled loops, permission waits, or runaway budgets. This article designs a replayable Agent observability solution around task traces, step status, toolchains, manual confirmation, and runtime budgets.
#AI Agent #DevOps♥ 180 comments
AI Cloud Control Plane Audit Integrity: Independent Aggregation, Digest Verification, and Retention Locks
Recording model deployments and IAM changes is not enough—attackers may disable logs, tamper with objects, or shorten retention periods. This article establishes an independent security domain, a digest chain, and gap detection.
#AI #LLM #DevOps♥ 270 comments
Prometheus + Grafana: Building Observability
Your service is running, but is it healthy or slow? This guide explains the classic Prometheus + Grafana stack: metric types, the pull model, PromQL fundamentals, application instrumentation, Grafana dashboards and alerts, and how logs and traces complete the three pillars of observability.
#DevOps♥ 300 comments
AI Cloud Workload Identity Federation: Binding SPIFFE, OIDC, and STS Exchange Boundaries
Inference workers, evaluation jobs, and model builders should not share cloud keys. This article separates the audiences of source credentials, exchange requests, and output tokens, and uses profiles and resource policies to block identity confusion.
#AI #LLM #DevOps♥ 280 comments
Nginx Reverse Proxying in Practice
Nginx is the most common reverse proxy and gateway in deployments, yet many developers only know how to copy a configuration snippet. This guide covers location matching, proxy_pass, X-Forwarded-* headers, load balancing, HTTPS/TLS, worker/buffer/gzip tuning, and common WebSocket, large-upload, and streaming pitfalls.
#DevOps♥ 310 comments
System Design: Why Message Queues Are Needed and How to Choose One
Message queues are the shock absorbers of distributed systems, smoothing traffic spikes, decoupling services, and enabling asynchronous work. This article covers their use cases, core models, reliability guarantees, ordering and duplication, and how to choose among Kafka, RabbitMQ, Redis Streams, RocketMQ, and Pulsar.
#DevOps♥ 340 comments