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By SteveGJones
Delegate cloud infrastructure planning, multi-cloud architecture design, Kubernetes deployments, container security hardening, cost optimization, and SRE reliability engineering including SLIs/SLOs and chaos experiments to specialized AI agents.
npx claudepluginhub stevegjones/ai-first-sdlc-practices --plugin sdlc-team-cloudExpert in multi-cloud strategy, service selection, IaC patterns, cost optimization, and cloud-native architecture across AWS, Azure, and GCP with focus on serverless, managed services, and well-architected principles.
Expert in Docker, Kubernetes, Helm, container security, service mesh (Istio/Linkerd), GitOps workflows, and platform engineering for scalable containerized applications.
Expert in SLO frameworks, incident response, chaos engineering, production reliability, and operational excellence. Use for defining SLIs/SLOs/error budgets, designing incident runbooks, implementing chaos testing, reducing operational toil, and e...
Uses power tools
Uses Bash, Write, or Edit tools
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Use this agent when setting up CI/CD pipelines, configuring Docker containers, deploying applications to cloud platforms, setting up Kubernetes clusters, implementing infrastructure as code, or automating deployment workflows. Examples: <example>Context: User is setting up a new project and needs deployment automation. user: "I've built a FastAPI application and need to deploy it to production with proper CI/CD" assistant: "I'll use the deployment-engineer agent to set up a complete deployment pipeline with Docker, GitHub Actions, and production-ready configurations."</example> <example>Context: User mentions containerization or deployment issues. user: "Our deployment process is manual and error-prone. We need to automate it." assistant: "Let me use the deployment-engineer agent to design an automated CI/CD pipeline that eliminates manual steps and ensures reliable deployments."</example>
DevOps, cloud, and deployment specialists - Kubernetes, Terraform, AWS, Azure, GCP, and SRE
Deployment engineering with Terraform and infrastructure as code
Cross-cutting specialist agents — architects, researchers, performance engineers
Enhances web_search Skill by researching best practices and deploying infrastructure automatically
Agents specialized in infrastructure management, DevOps, and site reliability engineering. Focuses on deployment, monitoring, and system operations.
AI/ML specialist agents — architects, prompt engineers, RAG designers
Full-stack agents — frontend, backend, API, DevOps architects
AI-First SDLC — zero-debt development with validators, enforcement, and workflows
Python-specific validation, patterns, and expert agents
Project management agents — agile coach, delivery manager, progress tracking
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