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Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.
Integrate Bunny.net services (CDN, Storage, Stream, DNS, Edge Scripting, Shield, Magic Containers, Optimizer, Database). Use when building with Bunny.net APIs, deploying to Bunny CDN, uploading files to Edge Storage, managing video streaming, configuring DNS zones, writing edge scripts, setting up WAF/DDoS protection, deploying containers, or optimizing images. Triggers on "bunny", "bunnycdn", "b-cdn", "pull zone", "edge storage", "bunny stream".
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Build 3D web apps with Three.js (WebGL/WebGPU). Use for 3D scenes, animations, custom shaders, PBR materials, VR/XR experiences, games, data visualizations, product configurators.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Web testing with Playwright, Vitest, k6. E2E/unit/integration/load/security/visual/a11y testing. Use for test automation, flakiness, Core Web Vitals, mobile gestures, cross-browser.
Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
| name | devops |
| description | Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit. |
| license | MIT |
| version | 2.0.0 |
Deploy and manage cloud infrastructure across Cloudflare, Docker, Google Cloud, and Kubernetes.
| Need | Choose |
|---|---|
| Sub-50ms latency globally | Cloudflare Workers |
| Large file storage (zero egress) | Cloudflare R2 |
| SQL database (global reads) | Cloudflare D1 |
| Containerized workloads | Docker + Cloud Run/GKE |
| Enterprise Kubernetes | GKE |
| Managed relational DB | Cloud SQL |
| Static site + API | Cloudflare Pages |
| Container orchestration | Kubernetes |
| Package management for K8s | Helm |
# Cloudflare Worker
wrangler init my-worker && cd my-worker && wrangler deploy
# Docker
docker build -t myapp . && docker run -p 3000:3000 myapp
# GCP Cloud Run
gcloud run deploy my-service --image gcr.io/project/image --region us-central1
# Kubernetes
kubectl apply -f manifests/ && kubectl get pods
cloudflare-platform.md - Edge computing overviewcloudflare-workers-basics.md - Handler types, patternscloudflare-workers-advanced.md - Performance, optimizationcloudflare-workers-apis.md - Runtime APIs, bindingscloudflare-r2-storage.md - Object storage, S3 compatibilitycloudflare-d1-kv.md - D1 SQLite, KV storebrowser-rendering.md - Puppeteer automationdocker-basics.md - Dockerfile, images, containersdocker-compose.md - Multi-container appsgcloud-platform.md - gcloud CLI, authenticationgcloud-services.md - Compute Engine, GKE, Cloud Runkubernetes-basics.md - Core concepts, architecture, workloadskubernetes-kubectl.md - Essential commands, debugging workflowkubernetes-helm.md / kubernetes-helm-advanced.md - Helm charts, templateskubernetes-security.md / kubernetes-security-advanced.md - RBAC, secretskubernetes-workflows.md / kubernetes-workflows-advanced.md - GitOps, CI/CDkubernetes-troubleshooting.md / kubernetes-troubleshooting-advanced.md - Debugscripts/cloudflare-deploy.py - Automate Worker deploymentsscripts/docker-optimize.py - Analyze DockerfilesSecurity: Non-root containers, RBAC, secrets in env vars, image scanning Performance: Multi-stage builds, edge caching, resource limits Cost: R2 for large egress, caching, right-size resources Development: Docker Compose local dev, wrangler dev, version control IaC